Citation
Characterization of Risk Factors, Morbidity, and Mortality Associated with Diarrheal Disease among Children under Five (Cu5) in East African Refugee Camps

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Title:
Characterization of Risk Factors, Morbidity, and Mortality Associated with Diarrheal Disease among Children under Five (Cu5) in East African Refugee Camps
Creator:
Atem, Jacob T
Place of Publication:
[Gainesville, Fla.]
Florida
Publisher:
University of Florida
Publication Date:
Language:
english
Physical Description:
1 online resource (148 p.)

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Public Health
Environmental and Global Health
Committee Chair:
MCKUNE,SARAH LINDLEY
Committee Co-Chair:
LIANG,SONG
Committee Members:
OKECH,BERNARD ACHERO
RYAN,SADIE JANE
LESLIE,MICHAEL

Subjects

Subjects / Keywords:
africa -- camps -- characterization -- cu5 -- diarrheal -- east -- factors -- morbidity -- mortality -- refugee -- risk
Environmental and Global Health -- Dissertations, Academic -- UF
Genre:
bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Public Health thesis, Ph.D.

Notes

Abstract:
Diarrheal disease remains the third leading cause of death globally among Children Under Five (CU5), an estimated one in 10 CU5 dies from diarrheal disease. Diarrheal disease is a leading cause of both morbidity and mortality among children living in low-income countries, thus much of the literature focuses on CU5 in developing countries. However, despite the additional vulnerability of refugee status, very little research on diarrheal disease has been conducted within refugee camps. This research reviews relevant data on the risk factors associated with diarrheal disease, as reported the published peer review literature, then using an analysis of United Nation High Commissioner for Refugees (UNHCR) - Health Information System (HIS) data. The objective of the research is to identify-patterns of diarrheal morbidity and mortality among CU5 in East African Refugee camps, and to identify key risk factors associated with this disease, so to better target interventions and improve health outcomes of children in these camps. ( en )
General Note:
In the series University of Florida Digital Collections.
General Note:
Includes vita.
Bibliography:
Includes bibliographical references.
Source of Description:
Description based on online resource; title from PDF title page.
Source of Description:
This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2017.
Local:
Adviser: MCKUNE,SARAH LINDLEY.
Local:
Co-adviser: LIANG,SONG.
Statement of Responsibility:
by Jacob T Atem.

Record Information

Source Institution:
UFRGP
Rights Management:
Applicable rights reserved.
Classification:
LD1780 2017 ( lcc )

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1 CHARACTERIZATION OF R ISK FACTORS, MORBIDITY AND MORTALITY ASSOCIATED WITH DIARRHEAL DISEASE AMONG CHILDREN UNDER FIVE ( C U5 ) IN EAST AFRICAN REFUGEE CAMPS By JACOB THON ATEM A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL O F THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2017

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2 2017 Jacob Thon Atem

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3 To my wife, my children, the United Nation H igh Commissioner for Refugees ( UNHCR) team in Geneva and friends at the University of Florida

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4 ACKNOWLEDGMENTS I offer my sincere thanks to my doctoral committee members: Dr. Sarah McKune (Chair ), Dr. Liang Song, Dr. Okech, Dr. Sadie Ryan and Dr. Mi chael Leslie for mentoring me through this research. Without your su pport, I would not have been able to finish. Global Health for funding me during the last year of my dissertation when I needed it mos t. for the McKnight Dissertation Fellowship, which allowed me to complete my dissertation. Furthermore, thank ful to you my friends family and network supporters, who through crowdsourced financial contributions supported th e completion of my dissertation research Moreover, I am grateful for United Nation High Commissioner for Refugees (UNHCR) for granting me access to the data necessary to complete my dissertation My heartfel t thanks to all of my friends in Dr ab who have answered so appreciative of my friend, Yushuf who trained and taught me STATA in a short span of time, enabling me to complete my dissertation on time. Most importantly, I will be ever grateful to my wife Linda Ach irin James and my boys Samuel Dut and Theodore Yai for the unconditional love and support they gave marriage to Linda James because women like Linda are hard to find. This woman has been the sole provider for our household during my studies and I cannot wait to finish so that I can give her a break from work!

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ ........ 10 LIST OF ABBREVIATIONS ................................ ................................ ........................... 11 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 OPENING REMARKS ................................ ................................ ............................. 13 History and Mandate of United Nations High Commissioner for Refugees (UNHCR) People of Concern. ................................ ................................ .............. 1 3 Refugees in sub Sahara Africa ................................ ................................ ............... 14 Refugees as a Vulnerable Population for Diarrheal Disease ................................ .. 15 Research Questions ................................ ................................ ............................... 18 Research Design ................................ ................................ ................................ .... 19 Data Analysis ................................ ................................ ................................ .......... 20 2 A SYSTEMATIC REVIEW OF THE EXISTING RISK FACTORS FOR DIARRHEAL DISEASE IN REFUGEE CAMPS ................................ ...................... 21 Objectives of the Systematic Review ................................ ................................ ...... 21 Methods for the Systematic Review ................................ ................................ ........ 22 Selection Criteria ................................ ................................ .............................. 22 Summary of Systematic Review Search strategy and Study Selection ............ 23 Data Collection/Extraction ................................ ................................ ................ 24 Quality of the Evidence Using Grades of Recommendation, As sessment, Development, and Evaluation (GRADE) ................................ ....................... 25 Results ................................ ................................ ................................ .................... 25 Study Characteristics ................................ ................................ ....................... 26 Synthesis of Systematic Review for Diarrheal Disease Studies in refugee camps ................................ ................................ ................................ ........... 34 Quality of the GRADE ................................ ................................ ...................... 39 Su mmary of Findings ................................ ................................ .............................. 40 3 CHARACTERIZATION OF DIARRHEA MORBIDITY, AND MORTALITY AMONG CHILDREN UNDER FIVE (CU5) ACROSS EAST AFRICAN REFUGEE CAMPS ................................ ................................ ................................ 58 Background ................................ ................................ ................................ ............. 58

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6 Global Burden of Diarrheal Disease ................................ ................................ 58 Registered Refugees Asylum Seekers in East Africa in 2017 .......................... 59 Vulnerability of Refugee Populations ................................ ................................ 59 UNHCR and HIS ................................ ................................ .............................. 60 Aims of the Research ................................ ................................ .............................. 61 Methods ................................ ................................ ................................ .................. 61 Data ................................ ................................ ................................ .................. 62 HIS Diarrhea Dataset ................................ ................................ ................. 62 HIS Population Mortality Dataset ................................ ............................... 62 Water and Sanitation & Hygiene (WASH) Nutrition Dataset ...................... 63 Case Definitions and Standards ................................ ................................ ............. 63 Data Management and Analysis ................................ ................................ ............. 64 Results ................................ ................................ ................................ .................... 65 Characteristics of East African refugee camps ................................ ................. 65 Number of Camps Studied for Diarrhea Morbidity, Population Mortality, and WASH Nutrition Datasets ................................ ................................ 65 Summary data for diarrheal morbidity data ................................ ................ 65 Summary data for WASH nutrition data ................................ ..................... 66 HFU Rate, and Incidences of Watery and Bloody Diarrhea in CU5 across East African refugee camps: 2006 2016 ................................ ................................ ...... 67 Results of Diarrheal Mortality among CU5 across East African refugee camps: 2006 to 2016 ................................ ................................ ................................ ........ 70 Total counts of cause specific mortality among CU5 by sex across all UNHCR reporting East African refugee camps ................................ ............. 70 Average mean mortality cases of watery, bloody and acute malnutrition among CU5 in East African refugee camps. ................................ ................. 71 Conclusion Remarks ................................ ................................ ............................... 72 4 A CROSS SECTIONAL ANALYSIS OF RISK FACTORS FOR INCIDENCE OF WATERY DIARRHEA AMONG CHILDREN UNDER FIVE (CU5) IN EAST AFRICAN REFUGEE CAMPS IN 2016 ................................ ................................ ... 88 Introduction ................................ ................................ ................................ ............. 88 Global Burden of Diarrhea Disease in CU5 ................................ ...................... 88 Diarrheal in Afri cans refugee camps. ................................ ............................ 88 Rationale for Conducting a Study on Risk Factors for Incidence of Watery Diarrheal among CU5 in East Africans refugee camps in 2016. ................... 89 East Africans Refugee Hosting Countries in 2016 ................................ ............ 91 Research Question ................................ ................................ ................................ 92 Methods ................................ ................................ ................................ .................. 93 Study setting ................................ ................................ ................................ ..... 93 Data ................................ ................................ ................................ .................. 93 Data Analyses ................................ ................................ ................................ .. 95 Results ................................ ................................ ................................ .................... 96 Camp Characteristics of the IVs in East African Refugees Camps in 2016 ...... 96

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7 Sample Sizes of the Multivariate Significant Variables by Hosting refugee Countries in 2016 ................................ ................................ ................................ 99 Mapping the Incidence of Watery Diarrheal among CU5 in East African refugee camps by Country in 2016. ................................ ................................ ................ 100 Five panels map of the average mean and the Standard Error (SE) of the mean for the significant multivariate variables. ................................ ............................ 100 Discussion ................................ ................................ ................................ ............ 101 Analysis of UNHCR Public Health 2016 Annual Global Overview data from 47 East African refugee camps in 4 Countries: Ethiopia, Kenya, South Sudan, and Uganda. ................................ ................................ ................... 101 5 DISCUSSION AND IMPLICATIONS OF RESEARCH FINDINGS ........................ 116 Discussion ................................ ................................ ................................ ............ 116 Outside Information about the author lived experienced ................................ ....... 118 What is missing in HIS datasets ................................ ................................ ........... 119 Recommendations for Future Research ................................ ............................... 120 Who can benefits from this research findings ................................ ....................... 121 APPENDIX A CHECKLIST OF ITEMS TO INCLUDE WHEN REPORTING A SYSTEMATIC REVIEW ................................ ................................ ................................ ................ 123 B FULL DETAILS OF THE SEARCH STRATEGIES FOR SYSTEMATIC REVIEW 127 REFERENCES ................................ ................................ ................................ ............ 142 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 148

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8 LIST OF TABLES Table page 2 1 Inclusion and Exclusion Criteria ................................ ................................ .......... 44 2 2 Characteristics of the 13 articles included in the Systematic Review for existing risk factors for Diarrheal Disease in the refugee camps from 1996 2016. ................................ ................................ ................................ .................. 46 2 3 Synthesis of t he findings of the Systematic Review of risks factors of the diarrheal in refugees camps from 1996 2016. ................................ .................... 51 2 4 Grades of Recommendation Assessment, Development, and Evaluation (GRADE) for Sys tematic Review of the risk factors for diarrheal disease in refugee camps from 1996 2016. ................................ ................................ ......... 56 3 1 Total registered refugees and asylum seekers across East African refugee camps in 2017[39 42] ................................ ................................ ......................... 75 3 2 Geographic breakdown of camp level data included in UNHCR Diarrhea, Mortality, and WASH Nutrition datasets from 2006 2016 ................................ ... 76 3 3 Summary data for diarrheal morbidity in UNHCR East African refugee camps by country level grand mean from 2006 2016 ................................ .................... 76 3 4 Summary data of camp level WASH Nutrition standards met among UNHCR East African refugee camps by country from 2006 2016 ................................ .... 77 3 5 Camps characteristics of UNHCR reporting refugee camps in Ethiopia: 2006 2016 ................................ ................................ ................................ ................... 78 3 6 Camp characteristics of UNHCR reporting refugee camps in Kenya: 2006 2016 ................................ ................................ ................................ ................... 80 3 7 Camp Characteristics of UNHCR reporting refugee camps in South Sudan: 2006 2016 ................................ ................................ ................................ .......... 82 3 8 Camp Characteristics of UNHCR reporting refugee camps in Uganda: 2006 2016 ................................ ................................ ................................ ................... 84 3 9 Total counts of Cause specific Mortality among CU5 by sex across all UNHCR reporting East African refugee camps 2006 2016. ............................... 86 3 10 Child mortality due to watery, bloody diarrhea and acute malnutrition across East African refugee camps by C ountry level grand mean: 2006 2016 .............. 87 4 1 East African Refugee camps hosting Countries reports for 2016 ..................... 105

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9 4 2 Summary of the E xposure variables extracted from East African hosting Countries reports in 2016 ................................ ................................ ................. 108 4 3 Camp characteristics of the Exposure variables in East African refugee camps in 2016 ................................ ................................ ................................ .. 110 4 4 Univariate analysis for selected Demographics, Access and Utilization, Water, Sanitation and Hygiene (WASH) indicators for Incidence of watery Diarrhea among CU5 across East African refugee camps in 2016 ................... 111 4 5 Multivariate Analysis of Incidence of Watery Diarrheal among CU5 across East African refugee camps in 2016 with respect to Demographics, Access, and Utilization, Water, Sanitation and Hygiene (WASH) indicators .................. 112 4 6 Sample size of the multivariate significant variables by hosting refugee countries ................................ ................................ ................................ ........... 113

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10 LIST OF FIGURES Figure page 2 1 Flowchart of identification and selection of studies for systematic review of risk factors for diarrheal disease in the refugee camps: 1996 2016 ................... 45 3 1 Mean incidence of watery and bloody in CU5 across Ethiopian refugee camps: 2006 2016 ................................ ................................ .............................. 79 3 2 Mean incidence of watery and bloody diarrhea i n CU5 in Kenyan refugee camps: 2006 2016 ................................ ................................ .............................. 81 3 3 Mean incidence of watery and bloody diarrhea in CU5 in South Sudan refugee camps: 2006 2016 ................................ ................................ ................. 83 3 4 Mean incidence of watery and bloody diarrhea in CU5 in Ugandans refugee camps: 2006 2016 ................................ ................................ .............................. 85 4 1 Locations of camps with data on the incidence of wate ry diarrhea (cases per 1,000/CU5/month) in CU5 in East African refugee camps in 2016. ................. 114 4 2 The mean and the Standard Error (SE) for the multivariate model significant variables that were associated with incidence of watery diarrheal among CU5 in East African Refugee camps by hosting refugee countries in 2016. ............ 115

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11 LIST OF ABBREVIATIONS CAR Central African Republic CFR Case Fatality Rate CI Confide nce Intervals C U5 Child r en Under Five DRC Democratic Republic of Congo GAM Global Acute Malnutrition GI Gastrointestinal GRADE Grades Recommendation, Assessment, Development and Evaluation (GRADE). HFU Health Facility Utilization HH Household HIS H ealth Information System IDP Internally Displaced People IRC International Rescue Committee IRR Incident Rate Ratio MOR Matched Odds Ration PRISMA Preferred Reporting Items for Systematic Reviews and Meta Analyses UNHCR United Nation High Commissione r for Refugees WASH Water And Sanitation, Hygiene WOS Web of Science

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12 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philos ophy CHARACTERIZATION OF RISK FACTORS, MORBIDITY AND MORTALITY ASSOCIATED WITH DIARRHEAL DISEASE AMONG CHILDREN UNDER FIVE ( C U5 ) IN EAST AFRICAN REFUGEE C AMPS By Jacob Thon Atem December 2017 Chair: Sarah McKune Major: Public Health Diarrheal disease remains the third leading cause of death globally among Children Under Five ( C U5 ), an estimated one in 10 CU5 die s from diarrheal disease. Diarrheal disease is a leading cause of both morbidity and mortality among children living in low income countries, t hus much of the literature focuses on CU5 in develop ing countries. However, despite the additional vulnerability of refugee status, very little research on diarrheal disease has be en conducted within refugee camps This research reviews relevant data on th e risk factors associated with diarrheal disease as reported the published peer review literature then using an analysis of United Nation High Commissioner for Refugees ( UNHCR ) Health Information System (HIS) data. The objective of the research is to identify patterns of diarr heal morbidity and mortality among CU5 in East African Refuge e camps, and to identi f y key ri sk factors associated with this disease, so to better target interventions and improve health outcomes of children in these camps.

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13 CHA PTER 1 OPENING REMARKS History and Mandate of United Nations High Commissioner for Refugees (UNHCR) People of Concern. T he United Nation High Commissioner for Refugees (UNHCR) is authorized by the Uni ted Nations (UN) to lead in the protection of refuge es and coordination of refugee programs worldwide [1] UNHCR was originally e stablished in 1950 to help refugees who had lost homes and fled to neighboring countries for safety [2] For more than 67 years UNHCR has been helping and protecting refugees, having assisted an estimated 65.6 million forcibly displac ed people worldwide [2, 3] UNHCR defines a refugee as someone who meets following criteria : 1) Has been considered a refugee under the arrangements of 12 of May 1926 and 30 June 1928 or under the Conventions of 28 October 1933 and 10 February 1938, the Protocol of 14 September 1939 or the Constitution of the Internation al Refugee Organization [IRO); decisions of non eligibility taken by the [IRO] during the period of its activities shall not prevent the status of refugee being accorded to persons who fulfil the conditions of paragraph 2 of this section [4] 2) As a result of events occurring before 1 January 1951 and o wing to well founded fear of being persecuted for reasons of race, religion, nationality, membership of a particular social group or political opinion is outside the country of his nationality and is unable or owing to such fear. Is unwilling to avail himself of the protection of that country; or who, not having a nationality and being outside the country of his former habitual residence as a result of such events, is unable or owing to such fear, is unwilling to return to it [4] As of 2016, the total number of pe ople forcibly displaced in the world was estimated to be 65.6 million [3] Of these 22.5 million are refugees (17.2 million under UNHCR mandate and 5.3 million Palestinian refugees ) as registered by United Nations Relief and Workers Agency (UNRWA) [5] The remainin g pe ople are largely internally

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14 displaced people (IDP) ( 40.3 million ), which is similar to a refugee but has not crossed an international border and asylum seekers (2.8 million). In the same year 2016, 55 % of refugees came from three countries: South Sudan (1.4 million), Afghanistan (2.5 million), and Syria (5.5 million) [3] .C ountries that hosted the greatest number of refugees in the same year included Ethiopia (791,600), Uganda (940,800), Islamic Republic of Iran (979,400), Lebanon (1.0 million), Pakistan (1.4 million) and Turkey (2.9 mi llion) [3] An estimated 51% of r efugee population are children under 18 years of age [5] Refugees in s ub Sahara Africa UNHCR has documented that sub Saharan Africa is home to the majority of refugees globally, a reality that is largely driven by conflict in the following countrie s: Burundi, the Central African Republic (CAR), the Democratic Republic of the Congo (DRC), Eritrea, Somalia, South Sudan, and Sudan [5] In 2016, the global distribution of displace d people worldwide included those hosted in in Africa (30%), the Mi ddle East and North Africa (26%), Europe (17%), Americas (16%), and Asia and Pacific (11%) [3] In 20 16, conflict s in sub Saharan Africa cause d significant refugee movement in the following countries: Nigeria (64,700), E ritrea (69,600 ) Bur undi (121,700) and South Sudan (737,400) [5] There was a sharp in crease in the number of refugee s coming into Uganda in 2016, with the greatest numbers coming from South Sudan (639,000 people), DRC (205,400), Burundi (41,000), Somalia (30,700), and Rwanda (15,200) [5] Similar ly to Uganda, the number of refugees in Ethiopia increase d tremendously in 2016, with a majority of refugees coming from South Sudan (338,800 ), Eritrea (165,000), and Sudan (39,900) [5]

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15 During the same timeframe, the ref ugee population in Kenya included those fr om South Sudan (87,100), DRC (13,000) and Ethiopia ( 19,100) [5] The DRC hosted an estimated 452,000 refugees in 2016, coming primarily Rwanda (245,100), South Sudan (66,700), and Burundi (36,300) [5] These data illustrate that the ongoing con flict in South Sudan is a major source of displacement for people throughout the region. Regarding South Sudan and the refugee crisis, the UNHCR states the following : The fastest growing refugee population was spurred by the crisis in South Sudan. This gr oup grew by 64% during the second half of 2016 from 854,100 to over 1.4 million, the majority of whom were children [5] There is a growing concern that the number of refugees has and will continue to rise through the end of 2017. Because internal fig hting and civil war conflicts within South Sudan erupt without war ning, refugees are forced to flee to neighboring countries rather than displacing internally [6] It has been projected that ci vil war conflicts in s ub Sahar an Africa wil l continue to displace more refugees if there is no peaceful settlement, which has important implications at national and regional levels, as these refugees return to their country of origin [6] Diarrheal disease is the third leading cause of disease burden and is the cause of death for an estimated 7.6 million CU5 annually [7] A previously noted, 51% of the total refugee population worldwide are CU5. The majority of children who die from dia rrheal diseases reside in sub Saharan Africa and South Asia [8] Thus, the next section will explore refugees as a particularly vulnerable population for diarrheal disease. Refugees as a Vulnerable Population for Diarrheal Disease Much of previous re search on diarrheal disease has been conducted on CU5 in low income countries, but little research has been conducted within refugee camps. As

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16 such, robust data about diarrheal morbidity and mortality among refugee chil dren under five are lacking. It has been estimated that 86% of refugees worldwide are hosted in low income countries [9] and most refugees rely on international aid to provide them with food, safe water, and basic health care delivery [10] In refugee camps, known risk factors for diarrheal disease are common Difficult but typical conditions of camps often include overcrowding, a lack of access to clean water and sanitation, inadequate shelter, and exposure to violence. Because refugee camp popul ations typically come from various g eographic areas, refugee populations within camps risk exposure to new pathogens. Paquet and colleague noted in their 1998 study that because of the push factors associated refugee migration, refugees find themselves in new locations where they are highly vulnerable to pathogens that may have long existed in that area but are new to the refugees [10] T hese factors combine to create a heightened level of biologic vulnerabilit y among refugee populations, both compared to their populations at home, as well as compared to populations surrounding the cam p s in host countries. This can increase the risk of diarrheal disease among refugees living in camps, particularly among CU5 A stud y looking at incidence and risk factors for diarrhea in CU5 in UNHCR camps across 16 countries found that 7% of mortality and 7% of morbidity in CU5 are attributable to diarrheal diseases [11] The researchers analyzed data from UNHCR HIS to estimate the incidence and risk factors for diarrheal disease among CU5 in UNHCR run refu gee camps

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17 A study by Boru et al., ( 2013 ) investigate the etiology of and factors associated with bacterial diarrheal diseases amongst urban refugees in Nairobi, Kenya This study found the following characteristics to be associated with diarrheal disease: c hildren not washing their hands with soap; c hildren not exclusively breastfed; c hildren having eaten food cooked the previous day; neighbors having had diarrhea; children sharing a toilet with a diarrhea patient; and children drink ing water from outside the hom e [12] In the two UNHCR refugee camps in Kenya (Dadaab and Kakuma), conditions match those previously described as promoting increased risk for diarrheal d isease and outbreaks. Overcrowding, insufficient housing, poor nutritional s tatus, and inadequate WASH are rampant [11, 13, 14] In Dadaab, Tepo et al. [15] documented outbreaks of c holera and shigellosis and cholera o utbreak s have also been documented in Kakuma [16, 17] These data su ggest that both outbreaks and endemic sources of diarrheal disease are likely present in refugee camps and driving rates of diarrheal disease. Schultz and colleagues [16] found th at sharing a latrine with three or more households and being a recent arrival in the camp were asso ciated with increased risk for contracting cholera [16] Another example of risk f actors identified within the refugee setting is published by Mahamud and colleagues who found a significant association between the presence of dirty water storage containers and the incidence of cholera [17] Outbreaks of diarrheal disease similar to those seen in Kenya n camps have been observed in other refugee settings in Africa. For instance, during the Rwandan Civil War

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18 in 1994, an estimated 20,000 Rwandan refugees died in the first month due to an outbreak of Shigella dysenteriae type 1 [13] Previous research indicates diarrheal d isease s often occur in refugee settings in the form of a disease outbreak; however, there is a lack of epidemiologic data i ndicating the endemic state of acute watery d i arrhea (AWD) or c holera among CU5 living in an East African refugee c amps. For this res earch thesis, the focus will consist of characterization of risk factors, morbidity, and mortality associated with diarrheal disease in CU5 across East African refugee c amps, from 1996 2016. Research Questions In order for policy and other decision maker s t o effectively address morbidity and mortality associated with diarrheal disease among refugee children, it is essential that improve the evidence base for understand ing the risk factors of diarrheal disease within this population. Doing so may enable No n Governmental Organization (NGO s ), UNHCR, and other agencies to better coordinate health interventions or programs or improve policies to facilitate health care access in these refugee camps. In the end, they may be able to mitigate the risk of childhood m orbidity and mortality from the diarrheal disease, especially during the complex emergencies that displace people, such as the ongoing situation in South Sudan, and in the refugee camps themselves. This research aims to characterize and investigates risk f actors, morbidity, and mortality associated wi th diarrheal disease among CU5 across East African refugee camps. The researcher first conducted a sy stematic review of the existing literature to identify risk factors, and then followed an empirical character ization of UNHCR data for diarrheal disease in the refugee camps. The dissertation is organized as follows:

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19 Chapter 2: A systematic re view of available literature to address questions about the existing risk factors for diarrheal disease among CU5 in the r efugee camps and how they vary across time and space. Chapter 3: A characterization morbidity and m ortality associated with diarrheal disease in CU5 across East African refugee camps, based on UNHCR HIS datasets. Chapter 4: A cross s e ctional analysis of r isk factors for incidence of watery diarrheal among CU5 in East African refugee camps in 2016. Chapter 5 : Implications of r esearch findings Research Design In Cha pter 2, the researcher conduct ed a systematic review of the existing risk factors for diarrhe al disease in in the refugee camps fro m 1996 to 2016. The researcher employed the guidelines for the Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) by Moher et al. ( 2009 ) to complete the systematic review [18] In Chapter 3, the researcher used descriptive statistics to analyze secondary data in the characterization of morbidity and mor tality associate with diarrheal disease. These data come from 11 years of data in the UNHCR HIS data set from 2006 to 2016. In the final content Chapter 4, the researcher built a, cross sectional data, based on publicly available 2016 UNHCR data, to examine risk factors for incidence of watery diarrhea among CU5 For Chapter 3 4, the researcher focused on four East African refugee hosting countries: Ethiopia, Kenya, South Sudan, and Uganda. The UNHCR HIS case definitions, standards, and indicators were utili zed in the analysis. Additional detailed information on research design is included in each chapter.

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20 Data Analysis Data analysis was conducted using Stata 11.1(StataCorp, College Station, Texas 77845) to compute summary m easures, including average mean a nd frequency of diarrhea morbidity by country and camps; and average means mortality by country. A regression analysis using the Generalized Linear Models (GLMs) was utilized to examine correlations between major risk factors (health service utilization, c amp characteristics, and WASH conditions) and the incidence of watery diarrhea in CU5 across East African refugee c amps in 2016. Additional detailed information on data analysis is included within each chapter.

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21 CHAPTER 2 A SYSTEMATIC REVIEW OF THE EXISTI NG RISK FACTORS FOR DIARRHEAL DISEASE IN REFUGEE CAMPS According to Moher et al. (2009), s ystematic ha s become increasingly (p.e1000097) [18] In the context of refugee health, one of the justifications for conducting a systematic of health literature includes the intent that organization such as UNHCR and their camp implementing agencies can use this information to improve policies, identification of vulnerable populations within the camp, and access to care in the refugee camps In addition in developed countries such as United States ( U.S ) little resear ch has been conducted a mong refugees. This is worrisome to the scientific community because ma ny refugees are seeking asylum in developed countries. Therefore, it is time for the de veloped countries to have a robust understanding of some of the health issues that people in refug ee camps face. Furthermore, the world is getting smaller, and in a matter of 24 hours, refugees in African c amps can find themselves resettled in other countries bringing with them a lifetime of experiences that determine their health status upon arrival. Such a changing world requires that we better understand refugee health. In doing so, not only do we improve UNHCR and other organizations ability to improve the situation within camps, but also so that clinicians in the developed world have a better und erstanding of which health problems refugees coming into the US may have both short and long term s Objectives of the Systematic Review In this chapter, the author con ducted a systematic review in an attempt to answer the following question: what are the e xisting risk factors for diarrheal disease among refugees and how do these vary across t ime and space? No protocol for this systematic review existed or was identified during a review of the literature ; this was

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22 confirmed through a review in PROSPERO Th is systematic review will add to the body of knowledge on diar rheal risk factors and will assist agencies such as UNH CR to strengthen and improve health services and outcomes for these vulnerable populations. In the results, we focus specifically on CU5 li v ing in the refugee camps due to their increased vulnerability compared to the general population. Methods for the Systematic Review T he author followed PRISMA guidelines created by Moher and colleagues to conduct the systematic review [18] knowledge, no protocol for this systematic review existed in the literature. The author reviewed literature a nd then searched an International prospective registr y of systematic reviews PROSPERO, and found no record of simi lar historical undertakings T he PRISMA checklist (in cluded in APPENDIX A) includes the list of items about the article that must be included when con ducting and reporting to a s ystematic r eview. These include title, abstract, introduction, methods, results, discussion, and disclosure of funding. Selection Criteria The following inclusion criteria for s election of articles were used; publicati on types (they must be sch olarly peer review ed journal articles), language (the articles have t o be full text in English only), and publication date (Initially the author intended to conduct a systematic review of literature on risk factors from diarrheal disease in the last 10 years (2006 to 2016). However, given the limited focus of this study and the lack of peer review publications on the topic, the range of publication date s included in the review was expanded to include those papers published over a 20 years period from 1996 to 2016. An additional inclusion criteria was the population studied ; for this review, the author included publications on populations of refugee living in refugee camps, with

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23 a special focus on CU5 Importantly, another inclusion criterion was risk factors For a study to be included in our review and analysis, the article ought to include analysis of risk factors for diarrheal disease related to refugee camp s. The final inclusion criterion was that the article must pertain to the human species. The outcome inclusion criterion was diarrheal diseases, with attention to populations under five years old where possible. The exclusion criteria consists of p ublications types language, and publication date. For this systematic review, the author exclude d articles that a re considered, review articles, personal communications, popular press articles, editorials, letters, comments working papers, or technical reports. All publications included must be in English; those articles that were not full text in English were not included in this study. Finally, any articles published before 1996 or after 2016 was excluded from this systematic review Table 2 1 shows inclusion and exclusion criteri a Summary of Systematic Review Search strategy an d Study Selection Subject headings and truncated, phrase searched keywords for risk factors for diarrheal diseases and refugee places were search ed in 3 major databases widely used in the scientific community: PubMed, Web of Science (WOS), and CABI on May 24, 2016. Results were combined and limited to English language full text, humans, and publications within the last 20 years (1996 to 2016). Full details of the search strategies are given in Appendix B. Study selection was performed by an independent rev iewer. Titles and abstracts of the studies identified in PubMed, WOS, and CABI were reviewed. After the abstract s and titles were reviewed, dupli cates were removed. W hen a study relevant to the review was found, the full text article was retrieved for anal ysis. Studies that did not meet the inclusion criteria were excluded (Appendix B).

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24 Furthermore, any discrepancies were resolved by the dissertation committee members to double check the methods Data Collection/Extraction Once re levant articles were ident ified for the study, data extractions were conducted and an excel table was created containing the following categories of information for each article : author, year, and title of the article. Also, reference type (i.e., the name of the journal), whether the full article t ext was online, and what country ( s ) or region(s) the article studied Additional information extracted included target population (i.e., universal child, travelers, target adult, high r isk children), study size (total number of people in the study), and actual people that were interviewed out of the total number of people in the study or cases/controls. Moreover, positive cases/negatives, the definition of diarrhea cases (defined or undefined) and the case definition of dysentery cases ( defined or not) were extracted from the articles. In addition, the author gathered data on whether the arti cles contained control groups (yes or no), analysis of the pathogen Shigella (yes or no) and pathogen Enterotoxigenic Escherichia Coli (ETEC) (yes o r no).If the article discussed other pathogens than Shigella and ETEC the author listed the pa thogens Most importantly, once all articles identified for inclusion were determined, the author extracted information about statistically not significant risk factors, statistically significa nt risk factors, and protective risk factors identified in the articles. When possible, the author extracted information about the reason for displacement such as war or conflict that forces someone to take refuge in the ne ighboring country The author also extracted information about the refugee's country of origin (i.e., South Sudanese and Somali who reside in refugee camps in Kenya ) and when possible, the

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25 name of the camp of residence (i.e., Kakuma refugee camp). When ava ilable in the articles, the author reported the p value of the associated risk factor and extracted information about the proportion, prevalence, attack rates, and CFR of diarrheal dis ease in the article. Finally, the author extracted information about la boratory methods used in the article and the conclusion the author(s) provided in the article. Quality of the Evidence Using Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) For this research study, Grades of Recommendation, Assess ment, Development, and Evaluation (GRADE) was used to evaluate the overall quality of evidence included in this systematic review [19] and communication of such judgment can support better informed choices in (p.1490 4) [19] Results A flowchart showing a study selection process is provided in Fig ure 2 1 including: records identified through database searching, number removed as exact duplicates, records after duplicates removed, total number of abstracts reviewed, number of articles excluded for other reasons and the total number of articles inc luded in this systematic review One hundred and twenty four citations, including 40 duplicates, were found in the PubMed, WOS and CABI databases on May 24, 2016. Evaluation of exa ct number duplicates removed, records after duplicates removed and a total number of a bstracts reviewed resulted in 84 remaining references; 71 studies did not answer our research question and were excluded for other reasons (i.e., review articles, full t ext not available or non English) from our systematic review. In Appendix B the full details of the search strat egies for our systematic review are included to explain

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26 why certain studies were excluded. Only 13 studies met all the inclusion criteria and we re available for the system atic review analysis of risk factors for diarrheal disease in refugee camps (Table 2 1). Study Characteristics Of the 13 studies, most were observational studies including 3 case control studies (Table 2 1) [16, 17, 20] 2 prospective cohort studies [21, 22] 3 cross sectional studies [23 25] 2 descriptive studies [26 28] a nd 1 retrospective cohort study [29] and only 2 s tudies were experimental studies [30, 31] The thirteen articles range in publication date from 1997 to 2015. Table 2 2 describes the characteristic s of the thirteen articles included in the systematic review w ith the following subheadings: a uthor, year, study design, camp, the host country, study population, target population, risk factors, lab methods and diarrheal disease outcome. In a 1997 case control study on epidemic cholera in Nyam ithuth Refugees Camp in Malawi, m ost of the refugees residing in this camp originated from Mozambique [20] 1931 persons were admitted to the treatment tent; there were 50 case patients and 50 matched c ontrols A In a Case Control B, the authors collected important data from 47 patients in the treatment tent. Out of the 245 households in Nyamithuthu North, 108 potential control households were then excluded (leaving 137) because one family member had been sick wi th diarrhea since arriving at the camp. The authors defined Nyamithuthu Camp between 23 August and 15 December (p.207) [20] The team interviewed and examined all patients in two IV treatment tents at the cholera cam p on December 12, 1990 [20] The r isk factors they looked at were as follows: water container, used separate container to drink or wash, shared water container with

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27 neighbors, went to river, drank any river water, left peas out overnight, ran out of firewood in previo us week ate dried fish, owned soap, o wned a cooking pot and reheated leftover peas [20] Peterson et al .,(1998) conducted a prospective cohort study on the effect o f soap distribution on diarrhea in Nyamithuthu refugee c amp [21] The authors sample 402 households and survey 356 in mid March; 322 households were available at the end of the study period The authors interviewed the subjects twice a week or 4 months about new diarrheal episodes and the presence of soap in the household [21] Peterson and colleagues defined a New Diarrheal e pisod e as the onset of diarrhoea (>3 watery stools in 24 h) reported by the female head of the household, in a household that had no diarrheal reported for any household member on the previous two interview days (i.e. (p.520 524) [21] The researchers identified the following risk factors in the study: household soap presence, households on days when soap was present, days when soap was not present in the same household, households who had soap in the household on the previous interview day (4 days earlier), number of children age 5, water quantity, maternal education [21] This study did not use laboratory methods because it was a survey study [21] Roberts et al., ( 2001 ) conducte d a randomized intervention tria l about keeping water clean in a Malawi refugee camp [30] They conducted an inter view with the household ( n= 401) with a female head or whomever else may have been available [30] The researchers visited households twice per week, and they asked if anyone experienced diarrhea [30] Robert and colle a gues (2001) more loose stools in a 24 hour period 287) and assessed whether the

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28 househo ld had any soap [30] The followi ng risk factors were identified by the authors in their study: number of huts making up the household, buckets in the household presence of latrine, animals in the household visible feces on latrine floor, improve bucket, children had a change of clothes [30] Regarding laborator y metho ds used by Roberts et al (2001) filled at the wells, the bucket number, the time of filling, the type of bucket, and the sex (p. 280 287) [30] samples were collect ed in sterilized 125 plastic Nalgene bottles which were placed on (p.280 287) [30] Mourad ( 2004 ) conducted a cross sectional survey of 1 655 households; most of those interviewed were women between the age of 18 49 years [23] This study categorized risk factors by intestinal parasites and diarrhea according to demographic conditions (crowdi ng index, female work, income, a ge group year), intestinal parasites and diarrhea according to environmental health c onditions (sewage disposal, barrel, flush toilet, direct from the tape, indirect from storage tank, full day water supply, storage tank was cleaned periodically, storage tank was not cleaned, and storage tank was not existing), and intestinal parasites and diarrhea according to hygienic conditions (cleanliness of the house, cleanliness of adults, cleanliness of children, presence of mosquitoes, flies inside the house, house ventilation, garbage inside the house, garbage around the house and status of the ki tchen) [23] I t is worth noting that the author did not clearly define diarrhea in his study. This study did not include lab methods.

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29 Doocy and Burnham, ( 2006 ) conducted a quasi experiment al study about the point of use water treatment and diarrhea reduction in the emergency context in Monrovia, Liberia [31] They conducted, a three month study in that include d 2215 participants in 400 househ olds [31] Risk factors that were ide ntified were household size, household head e ducation years, fe male (gender) literacy, hand pump, well narrow opening storage container, covered storage container, removal by dipping, chlorination ever, and shared or public l atrine Regarding laboratory methods used, the team conducted chlorine col iform, and testing to ass ess both free and total coliform levels [31] Abu Alrub et al ., (2008) conducted a prospective co hort study on the prevalence of Cryptosporidium ssp in children with diarrhea in West Bank, Palestine [22] The researchers examined biological samples from 76 0 children, sick with diarrhea. Individuals range from 1 month to 15 years of age and stratified by origin urban, rural, or refugee camp. Within the samp le, 123 children were from re fugee camps [22] In this stu dy, the definition o f the diarrhea was not provided, because the focus was the epidemiology of Cryptosporidium ssp Some of the risk factors that were identifi ed included wastewater disposal, rural areas and refugee camps without proper sewage disposal, po or living conditions and lack of self awareness, personal hygiene, and cleanliness [22] Regarding the laboratory analysis concentrated using the ethyl acetate sedimentation method and stained by the modified acid fast (p.059 062) [22] Abu Elmareen et al., (2008) conducted a descriptive study of isolation and antibiotic susce ptibility of Salmonella and Shigella strains from children in Gaza,

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30 Palestine [32] They a total of 3570 children ( and stool samples) age 1 month to 12 years (p.e330 e333) [32] .T he aut hors did not directly define case s of diarrhea, but defined it indirectly were diarrhea on ly; diarrhea with vomiting; diarrhea and fever; diarrhea together with (p. e 330 e333) [32] st any risk factors; however, the author extracted the following assuming they are risk factors: m ales, females, delay in ordering stool cultures and patients hospitalization of >3 days [32] Pertaining to the laboratory met hods used by the authors, they [and] identified biochemical reaction profile using Hy.enterotest and the API 20E test kit and Antibiotic susceptibility of Salmonella and Shigella (p. e 330 e333) [32] Kerneise et al., ( 2009 ) conducted a descriptive study on Shigella dysenteriae Type 1 epidemics in refugee settings in Central Africa [27] They examined an estimated 181,921 cases of Shigella dysenteriae type 1 among CU5 or old in the refugee camps in Central Africa [27] The authors defined "dysentery case as any person with diarrhea (passage of 3 or more watery or loose stools in the past 24 hours) and visible blood in the stool" (p.e4494) [27] Some of the key risk factors identified by the authors were: camp size children under 5 years old, arrival of refugees, liters of water per person per day, number of residents per latrine, food supply (kcal/person/day), context o f settlement, availability of resources and response speed, and seasons (dry and rainy) [27] Regarding l aboratory methods used, the authors

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31 stated that "bacteriological examinations were not routinely available for individual diagnosis and dysentery was diagnosed clinically" (p.e4494) [27] Shultz et al., (2009) conducted a retrospective matched case control study on Cholera outbreak among children in four age categories: <2, 2 4, 5 14 and >14 in a Kenyan refugee camp [16] watery diarrhea (at least three stools in a 24 h our period) who was admitted to the [International Rescue Committee] ( IRC ) cholera ward from April 1 through June 30, (p.640 645) [16] The researchers identified the following statistically not significant risk factors: drinking river water, s toring water in a jerry can, usually keeps water stored in house keeps water stored in h ouse covered, reheat food cooked the previous day, washes hands after eating, washes hands after visiting toilet, washes hands with soap, uses latrine, fifteen or more people sharing the same latrine, and three or more households sharing the same latrine [16] For laboratory methods used, Shultz et al., (2009) reactions, and the Vibrio c holerae positive iso lates were serogrouped and serotyped (p.640 645) [16] Hersey et al., ( 2011 ) conducted a retrospective cohort study on the inc idence and risk factors for malaria, pneumonia, and diarrhea in CU5 in UNHCR refugee camps [11] The authors including morbidity, mortality, health services and refugee health status, were obtained from the UNHCR (p.24) [11] The researchers used the following case definitions fo r watery a nd bloody diarrhea: 1 ) watery diarrhea was

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32 (p.24) [11] and 2 ) bloody watery or loose stoo (p.24) [11] Risk fa ctors for diarrhea in Hersey et al., (2011) were identified as follows: camp location & size (small <10,000, medium 10,000 19,999 and Large >20,000), water and sanitation (water quantity, water access, water proximity, latrine access, latr ine coverage, soap access), nutrition standards (Global Acute M alnutrition (GAM) and rational adequacy) and health service utilization (new visits and growth monitoring) [11] In this study, authors provided no laboratory methods. Mahamud et al. ( 2011 ) conducted a case control study on the epidemic cholera in Kakuma refugee c amp [17] The authors identified 224 cases (163 refugees and 61 non refugees) [17] The researchers diarrhea (>three watery stools in 24 hours) in any resident of Kakuma refugee camp >two years old, who was admitted to the IRC hospital cholera treatment center with the onset of illness after 1 (p. 234 241) [17] Some of the r isk f actors for cholera identified were : male, Somali, new arrivals after 6/1/09, soap present in the home, used soap to wash hands, latrine in compound, communal latrine, observed feces on ground, neighbor/family member had diarrhea u se water from sources other than tap, dirty water storage containers, treated water before drinking, eat or drink anything outside the home, ate cooked vegetables at home and drank milk at home [17] In term of labora tory methods diarrhea (p.234 241) [17]

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33 Mohamed et al. (2014) conducted a cross sectional survey on health care utilization for acute illness among the refugee population in Nairobi, Kenya [24] The researchers an individual was considered a member of a selected household if he/she slept within a compoun d, apartment, or room within the study area for at least 3 of any of the preceding 12 (p.200) [24] The authors had several sta ndard case def initions at the household level: 1 ) Fever defined as an illness associated with the feeling hot or feverish during the 2 weeks before the interview" (p.200) [24] and 2 ) Diarrhea was three or more loose stools over a 24 hour period during the before the survey" (p.200) [24] The following risk factors were identified in this study: language predominantly spoken in household (Somali and Oromo), country origin (Somalia and Ethiopia), gender of household member (male and female), age of househol d member (<5 years and >5 years), religious education, only primary school or less and secondary school or higher), household size (1 <3, 3 <5, 5 <8, and >8 ), who cared for the person during the ill ness (no one/cared for self and an other family member ), social economic statu s (higher, middle and lower), and severity (severe and mild) [24] The laboratory methods used were not described by the authors. Issa et al (2015) conducted a cross sectional stud y on access to safe water and personal hygiene practices in Kulandia refugee c amp in Jerusalem [25] In this study, 96 individuals were enrolled (62 females and 34 males) [25 ] The authors defined diarrhea [25] assesse d and identified the following risk factors for emesis and

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34 diarrhea: sex (female and male), education level (<8 th grade, some or high school graduate, and some or college graduate), annual income USD ( <2000, 2000 3000 and >3000), household water source (pi ped into dwelling, piped into yard/plot and tanker truck), drinking water source (piped into dwelling, piped into yard/plot, tanker truck), parents provided hygiene education re ceived formal hygiene education, and teaching children hygienic practices [25] In this st udy, the authors did not describe the laboratory methods they used [25] In the remaining of this ch apter, the author will discuss the non significant risk factors, statistically risk factors, and protective risk factors for diarrheal disease in studies in the refugee camps. Synthesi s of Systematic Review for Diarrheal Disease Studies in r efugee c amps An overview of the Systematic Review synthesis of all the 13 st udies can be found in Table 2 3 M ajor author, year, number of participants, and select statistically significant risk fact or, and disease outcome were categorize d as headings A case contr ol study by Swerdlow et al., ( 1997 ) compared exposures with cholera 50 cases patients with cholera 50 matched controls patients in Case Controls A [20] In Cases Control B, the authors compared 47 case patients in the IV treatment from hou by going door to door in Nyamithuth North ( Table 2 3 ) [20] For Case Control A, the researchers found these risk factors : placing hands into the water in the storage container, holding household drinking water during washing or drinking in the previous week, out of firewood during the previous week, and eating cooked pigeon peas t hat had been left out overnight to be statistically significant(Matched Odds Ratio) (MOR]

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35 =6.0, 95% Confidence Intervals [CI]=1.3 26.8 and [mOR] =8.0, [ CI]=1.0 64.0 respectively) [20] Swerdlow et al. (1997) found these risk factors (drank any river water [mOR]=2.2, [CI]= 0.8 6.3 and placed hands in the water container [mOR]=1.8, CI=0.6 5.5) were not statistically significant risk factors respectively for Case Control A and Case Control B [20] They reported heating leftovers (OR=0.15, CI=0.02 1.0, P< 0.05) as a significant protective risk factor [20] A prospective cohort study by Peterson et al. (1998) compared d iarrhea in households on days when soap was present to days when soap was not present in the same household [21] and found a k (RR =0.73, 95% Cl: 0.54 0.98) (p.520 524). In addition, they found 25% reduction of risk of diarrhea among households (HH) who had soap on the previou s interview day (RR = 0.75, 95% CI: 0.51 1.1) (p. 520 524) [21] In this study, there was no mention of r isk factors that were not statis tically significant for diarrheal disease. A study by Roberts et al., (2001) compared households which received improv ed buckets to households that did not (control houses). Robert et al. found the "presence of animals in th e household was significantly associated with increased diarrheal incidence (RR=1.1, P value=0.003), having animals in the household (RR=1.16, P value= 0.004) and visible feces value =0.001) were significa nt risk factors for diarrhea (p.280 287) [30] Also, Robert s et al. found that households which consumed more water experienced less diarrhea (P <0.01 and they mong children up to 5 years of age, having an improved bucket (RR=0.57, P value=0.040), a latrine (RR=0.86, P valu e=0.188), a change of clothing (RR=0.67 P

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36 value=0.078) and more buckets in household (RR=0.86, P value=0.22) were protective (p.280 287) [30] A cross se ctional survey by Mourad et al., ( 2004 ) demographic, environmental health and hygiene conditio ns associated with intestinal parasites and diarrhea (p.131 142) [23] Mourad et al. ,( 2004 ) found children aged younger than one year to be statistically significant risk factors for diarrheal disease [23] T he author s did not mention non statistically significant risk factors for diarrheal d isease, or any protective risk factors for diarrheal disease. A quasi experiment al study by Doocy and Burnham ( 2 006 ) diarrhea rates among households with flocculants disinfectant water treatment and improved water storage (intervention group) to households with only improved storage (control (p.1542 1552) [31] Doocy and Burnham ( 2006 ) found and incidence were significantly greater in Last Displaced Camp than in Morris Farm (P < 0.001 for (p.1542 1552) [31] In addition, rate of cont amination between the two sites was observed with Last Displaced Camp and Morris Farm reporting contamination in 88% and 86% of water source tests, respectively (P = 0.959) and no significant levels of free or total chlorine were observed in any water sour (p.1542 1552) [31] Finally, this article did not identify the protectiv e factors for the presence of diarrhea in each household member. A prospective cohort study by Abu Alrub et al., ( 2008 ) compared children with diarrhea to children without diarrhea (matched control) among Palestinian children living in the West Bank [22] The researchers found that children younger than 5 years of age

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37 (14.4%), children 5 to 10 years old (7.7%) and children of 11 to 15 years of age (5.9%) to be statistically signific ant risk factors (P<0.05) for c ryptosporidium spp. infection among Palestinian children with diarrhea living in West Bank [22] In this study there were no protective risk factors that were identified by the authors. A descripti ve study by Abu Elamreen et al., ( 2008 ) compared children with diarrhea only to diarrhea with vomiting to diarrhea and fever to diarrhea with vomiting and fever [32] They not identify or analyse risk or protective factors for the presence of Salmonella and Shig ella A descriptive study by Kerneis et al. (2009) "compared some cases of bloody diarrhea and deaths in refugee's camp to persons five years or older" (two age groups: children under five years' vs. persons five years or older) (p.e4494) [27] The authors did not report their su mmary measures in statistical comparisons but repo rted CFR were higher in children under 5 with the highest CFR seen in Inera (18.3%) and lowest (p.e4494) [27] A retrospective Matched Case Control Study by Shultz et al. ,( 2009 ) compared cases of cholera with matched controls during an outbreak [16] Two of the r isk factors for cholera identified by Shultz et al. were hou seholds ( Matched Odd Ratio MOR = 2.17 [1.01, 4.68]), and having recently arrived to the camp (MOR = 4.66 [1.35, 16.05]) [16] The study identified water sources being used including communal taps, wells, water from vendors, rainwater and bottled water, but none of these was found to be statistica lly signif icantly associated with having been ill with cholera [16] Key protect ive factors

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38 home in sealed or covered containers tended to be protective (MOR = 0.55 [0.29, 1.03]) 645) [16] Hersey et al ., ( 2011) compared risk factors for malaria, pneumonia and diarrhea in children 5 years old in UNHCR R efugees Camps [11] The authors found that: camps in Asia we re more likely to have cases of diarrheal disease than those in Africa ( Incidence Rate Ration ( IRR ) = 1.93, 95% CI 1.52 2.45), camps with large ( 20,000 refuges) and medium (10,000 19,999 refugees) size populations were associated with increased patient vis its for diarrhea (IRR= 2.16, 95% CI 1.04 4.49 and IRR = 1.80, 95% CI 1.07 3.03, respectively) compared to small (< 10,000 persons) camps and increased new patient visits was associated with an increase in all patient visits for diarrhea (IRR= 1.90, 95% CI 1.38 2.62) [11] No protective factors for m alaria p neumoni a, and d iarrhea were identified in the study. A case control by Mahamud et a l., (2011) compared cases during c holera outbreak to Mat ched Control of in Kakuma r efugee c amp [17] They found dirty water storage containers to be a statistically significan t risk factor, non significant risk factors were not found, and protective factors found were: those who ate cooked vegetab les drank milk at home, and ith chlorine (p.24) [ 17] A cross sec tional study by Mohamed et al., (2014) compared Febr ile illness Acute Respiratory Infection (ARI), and diarrhea in an urban refugee camp [24] .T he also Kenyans in the middle SES group were significantly more likely to seek health care services (OR 3.04; 95% CI 1.39 (p.200) [24] T he authors

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39 care seeking behavior: recommendation by a third party to seek health care services, (p.200) [24] The researchers did not describe any prote ctive risk factors for ARI and d iarrheal illness. A cross sec tional study compared women education to men water source piped in dwelling to water tanker truck for individual and household G astro intestinal (GI) burden (emesis and diarrhea ) [25] The study found that compared to men, women had statistically significantly better hygiene practices and lower GI burden and diarrhea [25] T he authors found an statistically significant association between formal, higher education and emesis (P<0.05), and diarrheal (P<0.05), piped drinking and household water and less diarrhe a (P<0.05), soap availability (P<0.05), hand wash post restroom use han d wash before meal preparations, and vender cleanness consideration, and lower GI burden [25] Quality of the GRADE This s ystematic review includes GRADE of the risk factors for diarrheal disease in refugee camps illustrating the overall quality of the evidence (Table 2 4 ). The quality of evidence in this analysis are categorize d as being either very low, low or high. Very 4) [20]. Low is defined as "Further research is very likely to have an important impact on our confidence in the estimate of effect and is like (p.1490 4) [19] High is defined as "further research is unlikely to change our confidence in the estimate of effect" (p.1490 4) [19] Most studies included were observational studies (i.e., cohort, cross sectional and case control ), which resulted in ver y low, and low levels according to GRADE [19]

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40 In Table 2 4 54% of articles (7/13) were low level evidence, 38% of the articles (5/13) were and 7.69 % of the articles (1/13) were high level evidence In the thirteen articles studied, a risk of bias was found due to the li mitation of the study designs. The case control study by Swerdlow et al. (1997) has a major problem with confounding variables and bias (i.e., sampling bias, observation bias and recall bias) [33] For example, 50 patients with cholera in Nyamthu thu camp, Mali, may be a biased sample (for example c holera patients being referred from outside of Nyamithuthu camp) or the 50 matched cholera patients may be biased due to whether these cont rols were volunteers, different ages, sex and socioeconomic group in the Nyamithuthu Camp [33] A potential issue in the cross sectional survey by Mourad et al. (2004) is that it cannot differentiate cause and effect from simple association [33] For example, it is difficult t o establish cause and effects of socioeconomic demographic, environmental health and hygiene conditions associated with intestinal para sites and diarrhea. [33] Summary of Findings In summary, the most risk facto rs for diarrheal diseases in refugee camps involved WASH conditions. The statistically significant risk factors identified in the systematic review associated with an increase of diarrheal disease in the refugee camps were: Placing hands into of a household water storage container; Holding household drinking water during washing; Household not having firewood during the previous week ; Eating leftover that had been left out overnight; Presence of animals within the household;

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41 Visible feces Children age younger than one year; Sharing a latrine with three or more households; Being a recent arrival in refugee camp; The presence of dirty storage containers for water ; P rotective risk factors identified in this systematic review against diarrheal disease in the refugee camps were: Heating leftovers; The presence of soap in a household; Having an imp roved bucket; Presence of an i mprove d l atrine; Having a c hange of clothing; Having m ore buckets in household; Storing water in the home in sealed or covered container; Consuming cooked vegetables; Drinking milk at home; and Treating water by either boilin g it or with chlorine before drinking. Key finding of this systematic review is that most of the diarrhea diseases in refugee camps that are reported within the literature are in the form of the outbreaks. The diarrheal pathogens reported in this systemati c review are, Cholera Enterobius vermicular Giardia lamblia Entamoeba Histolytica, Cryptosporidium Salmonella Shigella and Emesis For this review risk fact ors for diarrheal disease in refugee camp s were searched as key subject headings. T he 3 m ajor databases searched were PubMed,

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42 WOS and CABI. The results were combined and then limited to English language full text, humans subjects and publications within the last 20 years (1996 to 2016). Full details of the search strategies are given in the appendix (Appendix A). Study selection was performed by an independent reviewer. Titles and abstracts were reviewed and duplicates removed. The full text of relevant studies was then retrieved for analysis and studies that did not fully meet the inclusion and exclusion criteria were excluded. This study aimed to conduct a systematic review of existing risk factors of diarrheal dise ase in the refugee camps. C onducting a systematic review, the author followed (PRISMA ) guidelines, and used GRADE to assess the quality of evidence by [19] In th is review most of the studies (7 /13) were observational, and the rest of ( 6 /13) were experimental (1), quasiexperimental (1) and descriptive (4) Limitations of the systematic review. There are several limitations in this systematic review. By focusing on the scholarly literature, this search does not include the grey literature which is a very common outlet for humanitarian and development work In addition, the population we are focusing on is refugees. Most of them reside in sub Sahara n Africa, and this population is not well studied due to the harsh environmen tal conditions they live in, and the magnitude of severity of the situation many of them find themselves in. Research in the context of humanitarian disaster or complex emer gencies is logistically complicated thus there is very limited data. This is underscored by the scarcity of evidence on the subject of diarrheal disease among refugees : from one hundred twenty four potenti ally relevant studies, only 13 studies met the rev iew selection criteria. Furthermore, these studies show large scale heterogeneity in all risk factors across the refugee camps, populations, and d iarrheal disease in these

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43 settings. The final limitation is that the quali ty of the evidence available from th e 13 studies in this review was very low.

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44 Table 2 1 Inclusion and Exclusion Criteria Inclusion Criteria Exclusion Criteria Publication type Publication type Language Language Publication date Publication date Population st udied Risk Factors Human subject focus

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45 Figure 2 1. Flowchart of identification and selection of studies for systematic review of risk factors for diarrhea l disease in the refugee camps: 1996 2016

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46 Table 2 2 Characteristics of the 13 articles inc luded in the Systematic Review for existing risk factors for Diarrheal Disease in the refugee camps from 1996 2016. Author, Year Study Design Camp, Host Country Country of Origin Study Population Target population Selected Risk Factors Lab Methods Outcome Swerdl ow et al. 1997 Case Control Nyamithuthu, Malawi Mozambican 1931 of the 6114 persons admitted to the IV treatment tent Age group: 0 4 years, 5 14 years and >15 years old. Drinking river water, place hands into stored household drinking water and eati ng leftover cooked peas. swabs of and Use standard DPD reagent and cultured with the Spira jar technique Cholera Peters on et al. 1998 Prospective Cohort Nyamithuthu, Malawi Mozambican 402 households surveyed and then interviewed Age g roup:<5 years, 5 14 years and 15+ years. Presence of soap in the household (protective factor). N/A: No Lab methods provided, it was Survey New diarrhea episode Robert s et al. 2001 Experiment al Nyamithuthu Malawi Mozambican 401 Mozambica n refugee househo lds followed over a 4 month Children <5 years of age Visible feces in the family latrine and the presence of animals. Water Samples Diarrhoe a

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47 Table 2 2 Continued Author, Year Study Design Camp, Host Country Country of Origin Study Population Target p opulation Selected Risk Factors Lab Methods Outcome T.A. Abu Mourad. 2004 cross sectional Nuseirat, Gaza Strip Palestinian 1625 households Survey. Age groups: <1 <1 4 9 18 33 years 34 49 years >50 years Crowding, the source of drin king, water and the cleaning of water tanks. N/A: No Lab methods provided, it was Survey. Enterobius vermicularis, Giardia lamblia, Entamoeba histolytica, Ascaris lumbricoides, Giardia lamblia and Enterobius vermicularis, Entamoeba histolytica and Gi ardia lamblia Shan non Doocy and Gilbert Burnham. 2006 Quasi experiment IDPs, Liberia Liberians A total of 2215 participants. Children less than 5 years of age Flocculant disinfectant Chlorine and coliform testing Diarrhea

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48 Table 2 2 Continued Autho r, Year Study Design Camp, Host Country Country of Origin Study Population Target population Selected Risk Factors Lab Methods Outcome Sameer M. Abu Alrub et al. 2008 Prospective Cohort West Bank (Urban centers, rural villages, refugee camps), Palestine Palestine Fecal samples were taken from 760 with diarrhea Age group: 1 month to 13 years old. Age group <5 years samples were concentrated using the ethyl acetate sedimentation method and stained by the modified acid fast stain Crypt osporidiu m spp Abu Elamreen et a l. 2008 Descriptive EINasser pediatric hospital, Gaza Palestine Palestine Evaluated 3570 stool specimen: All stool samples were examined for the presence of Salmonella and Shigella Patients ranged in age from 1 month to 12 years N/A: this article does not mention or list any significant risk factors. bacteria were identified by their biochemical reaction profile using Hy.enterotest and the API 20E Salmonella and Shigella

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49 Table 2 2 Continued Author Year Study Design Camp, Host Country Country of Origin Study Population Target population Selected Risk Factors Lab Methods Outcome K erneis et al. 2009 Descriptive 11 refugee c amps: Rwandans 181,921 cases of bloody diarrhea w as reported Children Under Five years old Children Under Five, small and medium and large camps. was diagnosed Shigella d ysenteriae Type 1 Shultz et al. 2009 Retrospective Matched Case control Kakuma, Kenya South Sudanese and Somalia. 418 people treated Fou r age categories: < 2, 2 4, 5 14 and >14). Sharing a latrine with at least three households and arriving at Kakuma camp on or after November 2004. V.cholerae serogroup 01 isolated from stool Cholera outbreak Hersey et al. 2011 A retrospective Cohort 90 U NHCR Camps, 16 countries 16 countries Under five (U5) population mean =3812 (Africa) 1761 (Asia). Children Under Five Years Old (CU5) Years. Camp characteristic s in Africa and Asia, Health facility visits and growth monitoring. N/A Diarrhea

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50 Table 2 2 Continued Author, Year Study Design Camp, Host Country Country of Origin Study Population Target population Selected Risk Factors Lab Methods Outcome Mahamud et al. 2012 Case Control Kakuma, Kenya Somali, South Sudanese and Ethiopians. Total 224 cas es were identified and hospitalized at IRC Hospital. Age groups: <5, 5 14 15 24 and >25 Presence of dirty water storage containers. V. Cholerae 01, serotype Inaba isolated in the stool specimens. Cholera outbreak. Mohamed et al. 2014 Cross sectional Eas tleigh, Kenya Somalia, Ethiopia and Eritrea. Collected 673 households with 3, 005 individuals. Age groups: <20 years old, 20 35 years old. Care seeking behavior, reasons for not seeking care. N/A Healthcare Utilization of illness (i.e diarrhea). Issa e t al. 2015 Cross sectional Kulandia refugee c amp, Jerusalem, Israel. Palestine 96 individuals enrolled in the study; 62 females and 34 males. Sex: Male and Female Sex, parents provide hygiene education, receive formal hygiene. N/A Diarrhea and Emesis

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51 Tab le 2 3 Synthesis of the findings of the Systematic Review of risks facto r s of the diarrheal in r efugees c amps from 1996 2016. Author, Year #Participants Statistically significant risk factor Protective factor Selected Comparison Outcome (Diarrheal Diseas e) Swerdlow et al. 1997 50 case patients and 50 matched controls. The p revious week, eating cooked pigeon peas that had been left out overnight (mOR=8.0, CI=1.0 64.0). protective: OR=0.15 (CI=0.02 1.0). Exposures case patient s Versus Matched Controls Patients. Cholera. Peterson et al. 1998 168 households with children under 5 of mothers reported washing their children's hands. 27% reduced risk (RR =0.73 Cl 0.54 0.98) of diarrhea in households on days when soap present vs day s when soap was not. 27% fewer episodes of diarrhea in households when soap was present Diarrhoea in households on days when soap was present versus Days when soap was not present. New Diarrho ea Episode: Roberts et al. 2001 received improved individuals in control households remained household (RR=1.16, P value= 0.004) and visible feces on the floor of a ho 36, P value =0.001) were significant risk factors for age, having an improved bucket (RR=0.57, P value=0.040) a latrine (RR=0.86, P value=0.188), a change of clothing (RR=0.67 P value=0 .078) and more buckets in household (RR=0.86, P value=0.22) were Households identified to receive the improved buckets versus controls houses. Diarrhoea :

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52 Table 2 3 Continued Author, Year #Participants Statistically s ignificant risk factor Protective factor Selected Comparison Outcome (Diarrheal Disease) T.A. Mourad, 20 04 A total of 485/1625 of the investigated households reported parasitic cases. diarrhea was found to be statistically signifi cantly higher among children aged younger than one year (X 2 Not available (N/A) Yes/No question versus multiple choice Enterobius vermicularis, Giardia lamblia, Entamoeba histolytica and Ascaris lumbricoides. Doocy and Burnham, 2006 otal of 200 households in each intervention group with 1138 and 1053 Vs. Intervention households for diarrhea incidence and prevalence were 3.0(CI 2.7 3.3 ) and 4.4 (CI 4.0 4.8). Not available (N/A) iarrhoea rates households vs. improved water storage Presence of Diarrhea. Abu Alrub et al. 2008 were taken from 760 children with cryptosporidiosis was found in children younger t as compared to that in children 5 to 10 years old (7.7%) and in children 11 to 15 years of age (5. Not available (N/A) month to 15 years old) Versus Matched Controls and treated exactly in the sa me manner as Cryptosporidium spp.

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53 Table 2 3 Continued Author, Year #Participants Statistically significant risk factor Protective factor Selected Comparison Outcome (Diarrheal Disease) Abu Elamreen et al. ,2008 Evaluated 3570 (children) stool specimens of patients ranged in age from 1 month to 12 years. Not available (N/A) Not available (N/A) Compare children enrolled in this study based on: Diarrhea only versus diarrhea with vomiting versus diarrhea and fever and diarrhea with vomiting and fever! Salmonella and Shigella Kerneis et al. 2009 Small camp ranged from 8,588 to 215,889 in the largest camp. CU5 has highest CFR in Inera (18.3%) and lowest (1.6%) in Rkondo Not available (N/A) Children under five years vs persons fiv e years or older. Shigella d ysenteriae Type 1 : Shultz et al. 2009 348 cases in camp residents were enrolled along with 170 matched controls. three or more households (MOR = 2.17 [1.01, 4.68]) and being a recent arrival in the camp (MOR = 4.66 [1.35, 16.05]) were associated with increased stored in home sealed/ covered was protective (MOR = 0.49 Cases with Cholera Outbreak Versus Matched Control of Cholera outbreak. Cholera Outbreak Hersey et al. 2011 camps in Africa than Asia, 117 camp years were analyzed for Africa and Camps in Asia were more likely to have cases of diarrheal disease than those in Africa (IRR= 1.93, CI 1.52 Not availab le (N/A) Comparison of risk factors for malaria, pneumonia and diarrhea in children 5 years old in UNHCR Refugee Camps. Malaria, Pneumonia and diarrhea.

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54 Table 2 3 Continued Author, Year #Participants Statistically significant risk factor Protective f actor Selected Comparison Outcome (Diarrheal Disease) Mahamud et al. 2012 matched controls were storage containers, which was a risk factor (AOR 4.39, CI 1.12 17.14, p = 0.03 hands with soap, which was protective against cholera (Adjusted OR [AOR] 0.25, CI 0.09 0.71, p = 0.010) Cases with Cholera Outbreak Versus Matched Control of Cholera outbreak in Kakuma r efugee c amp. Cholera Mohamed et al. 2014 3,005 partici pants. Reported at least one of the illness of interest (ARI and Diarrhea). Kenyans (seek health care services: OR 3.04; CI 1.39 6.63; p = Not available (N/A) Acute ill nesses: ARI and Diarrhea.

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55 Table 2 3 Continued Author, Year #Participants Statistically significant risk factor Protective factor Selected Comparison Outcome (Diarrheal Disease) Issa et al. 2015 were enrolled in the study ; each sink is associated with fewer diarrhea episodes (P<0.05; 31.6% for yes, 55.6% for sometimes, 83.3% for no associated with 2 or more higher education appeared to be pro tective against emesis (P<0.05) and diarrheal symptoms Women educate compared with men. Women more likely to have better hygiene practices with lower GI burden emesis and diarrhea Versus relative to men. Water source piped in dwelling versus for tanker truck Emesis and diarrhea.

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56 Table 2 4 Grades of Recommendation Assessment, Development, and Evaluation (GRADE) for Systematic Review of the risk factors for diarrh eal disease in refugee camps from 1996 2016. Author, Year Study Design Assignin g GRADE of Evidence Definitions of GRADE of Evidence by [19] Swerdlow et al. 1997 Case Control Study Low impact on our confidence in the estimate of effect and is [19] Peterson et al. 1998 Pr ospective Cohort Study Low See definition [19] Roberts et al. 2001 Experimental Study (Randomized trial Intervention Trial) High [19] Mourad, 2004 A cross sectional Survey Very low [19] Doocy and Burnham, 2006 Quasi experiment study Very low See above definition Abu Alrub et al. 2008 Prospective Cohort Study Low See definition above Abu Elamreen et al. ,2008 Descriptive Study Very low See definition a bove Kerneis et al., 2009 Descriptive Study Very low See definition above Shultz et al. 2009 Retrospective Matched Case control study Low See definition above Hersey et al. 2011 A R etrospective Cohort Study Low See definition above Mahamud et al. 201 2 Case Control Study Low See definition above

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57 Table 2 4 Continued Author, Year Study Design Assigning GRADE of Evidence Definitions of GRADE of Evidence by[25] Mohamed et al. 2014 Descriptive Study Very low See definition above Issa et al. 2015 Cro ss sectional Study Low See definition above

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58 CHAPTER 3 CHARACTERIZATION OF DIARRHEA MORBIDITY AND MORTALITY AMONG CHILDREN UNDER FIVE (CU5) ACROSS EAST AFRICAN REFUGEE CAMPS Background Global Burden of Diarrheal Disease Worldwide, diarrheal dis ease is the third leading cause of morbidity and mortality in CU5: 7.6 million children are estimated to die every year from diarrheal diseases [8] Globally, the majority of children who die from diarrheal disease s reside in developing countries in sub Saharan Africa and South Asia [8] A study by Kosek et al,.( 2003 ) found diarrheal morbidity incidence for CU5 is 3.2 episodes per child per yea r, and that 21% of deaths amon g CU5 were attributable to diarrhea [34] Black et al,.( 2003 ) pointed out that "ingestion of unsafe water, inadequate availability of water for hygiene, and lack of access to sanitation contribute to about 1.5 million child deaths and 88% of deaths from diarrhea 2234) [35] A study examining incidence and risks factors for diarrhea in CU5 in UNHCR camps found that 7% of mortality and 10% of morbidity among CU5 were attributable to diarrheal diseases [11] A study by Cronin et al (2009) quantifying the burden of disease associated with inadequate provision of water and sanitation in selected sub Saharan refugee camps found that in Ethiopia, the average per capita Disability Adjusted Life Years (DALY) due to diarrhea [was] higher than the national averages, and yet the number of deaths due to diarrhea in the camps was much lower than the national average [36] Cronin et al., (2008) have documented that GA M rates among CU5 ranged between 18 and 23%, and those with the highest risk for GAM were those children with dysentery in the camps [37] A study in Western Kenya found that the 2 week period prevalence of diarrhea among all children was 26% [38]

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59 Registered Refugees Asylum Seekers in East Africa in 2017 It has been documented that there is a lack of adequate water and sanitation in the following refugee hosting countries: Uganda, Chad, Kenya and DRC [37] Because diarrheal disease is ubiquitous among refuge es these vulnerable population s mainly rely on : adequate q uantities of disi nfected water, elementary sanitation, community outreach, and managing cases of the patients when they are sick [37] Table 3 1. shows registered refugees and asylum seekers across East African refugee camps. The total registered refugees asylum seekers in Ethio pia in 2017 was 829,925, the p roportion of CU5 was 14% (Fe male 7.0% and Male 7.1%), and C ountry of O rigin of refugees included : South Sudan, Somali, Eritrea, Sudan, Yemen and other nation s (Table 3 1) [39] In 2017, the total registered refugee popul ation in Kenya was 488,045, 15.3% CU5 refugee came from Somalia, Sou th Sudan, DRC, Ethiopia, and Sudan [40] For South Sudan i n 2017, the total number of registered refugees was 268,286, 20% CU5, and the cou ntry of origin for refugees were Sudan, DRC, Ethiopia, and CAR [41] For Uganda in 2017, the total number of refuge es and asylum seekers was 1,252,47 0, and the country of origin of refugees were primarily South Sudan, DRC, Burundi, Somali a, Rwanda and others (Table 3 1) [42] V ulnerability of Refugee Populations Refugee populations constitute vulnerable groups of people globally, for various and complex reasons. In Africa, refugee camps are lo cated mostly in rural areas and service populations affected by long running conflicts or aftermath of emergencies. UNHCR routinely monitor s many of the variables widely accepted as risk factors for diarrheal disease, including access to health care services, nutritional status of children,

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60 access to water, and WASH conditions [11] However, the difficult, yet typical co nditions of refugee camps addi tionally exacerbate condition s, e.g., overcrowding, a lack of access to clean water and sanitation, and inadequate shelter [11] All of these factors may increase the risk of diarrheal infections among refugees, particularly among th e most vulnerable population, CU5. UNHCR and HIS In 1950, the office of the UNHCR w as established, and today, it is the lead agency "protecting and assisting refugees around the world" [43] Currently, there are 65.6 million forcibly displaced people worldwide, and 22.5 million are refugees [44] The proportion of displaced people hosted by continent from highest to l owest is as follows: Africa (30%), Middle East and North Africa (26%), Europe (17%), the Americas (16%) and Asia and Pacific (11%) [44] It is documented that 55% of refugees globally came from the following three countries: Syria (5.5 million), Afghanistan (2.5 million) and South Sudan (1.4 million) [44] In 2006, the UNHCR launched HIS and currently, HIS is operational in Ethiopia, health status of the refugee population and to increase the early detect ion of an [45] HIS data are collected weekly and entered monthly in to the HIS reporting system These data provide important insights into the health of refugee populations globally. The HIS data provide a unique opportunity to characterize diarrheal morbidity mortality Understanding these data may assist implementing agencies to better plan how to prevent diarrheal disease morbidity and mortality among CU5 within a context of limited resources. Thus, the overall goal of this research is to character ize diarrheal

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61 morbidity and mortality among CU5 in East African refugee c amps, using the UNHCR HIS data from 2006 2016. This study will help us to have a better understanding of the burden of diarrheal disease in CU5 which may be applicable in refugee cam ps across other parts of the world. Aims of the Research For this chapter 3, specific research aims include: Aim 1: To de scribe the geographic distribution of camp level data included in UNHCR Diarrhea Morbidity, Mortality, and WASH Nutrition datasets for m 2006 2016. Aim 2: To characterize diarrheal morbidity and mortality among CU5 across East African refugee camps. The remaining sections of this paper are laid out as follows: First, a description of the three HIS datasets utilized in this research and me thods used to generate results are described. Next, results including a section on morbidity and one on mortality are examined. Finally, implications of these findings are discussed. Methods UNHCR provided HIS data access to researchers at the University of Florida to answer questions surrounding Health Facility Utilization (HFU) rate (consultation/person/month), the incidence of watery (cases/1000/population/month) and incidence rate of bloody (cases/1000/population/month) with diarrheal disease among CU5 in refugee camps in East Africa. Three separate datasets entitled Diarrhea Data Pop Mort dat a and WASH Nutrition Data were provided in the form of excel spreadsheets. The 3 datasets were cleaned and imported into Stata 11.1 ( StataCorp LP, College Statio n Texas, USA) for analysis.

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62 Data HIS Diarrhea Dataset Like all HIS data, diarrhea data are collected on a monthly basis at refugee camps across East Africa, including those in Ethiopia, Kenya, South Sudan, and Uganda. The key variables existing within th e HIS, dataset and of interest to this project were the HFU rate, the incidence of watery diarrhea and incidence of bloody diarrhea among CU5 The researcher collapsed (pooled mean) of HFU rate, incidence of watery diarrhea, and incidence of bloody diarr heal by country and month. Also for camp level analysis the researcher collapsed the same variables mentioned above by year, country and camp. These da ta were included in analyses comprised data from 39 camps between 2006 and 2016. HIS Population Mortali ty Dataset Within the second data set, which contained important diarrhea related mortality data, information was included for 59 refugee camps across the four study countries. This included mortality data in cases of watery and cases of bloody diarrhea, a s well as cases of acute malnutrition among CU5 between 2006 and 2016. Simila r to the diarrheal data in the first dataset, the data reported in the mortality dataset is collected monthly at camps across East Africa before being sent to UNHCR headquarters. Specifically, the HIS mortality dataset provided the following variables included in the analysis : sex disaggregated mortality cases of watery diarrhea in CU5 sex disaggregated mortality cases of bloody diarrhea in CU5 and sex disaggregated mortality c ases of acute malnutrition in CU5

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63 Water and Sanitation & Hygiene (WASH) Nutrition Dataset The third and final dataset, which included water, sanitation, and hygiene nutrition data, differed markedly from the Diarrhea and Mortality datasets. These data ar e collected through an annual survey conducted by UNHCR across th e East Africans refugee camps. The following variables were of interest for this analysis: average number of liters of potable water available per person per day, percent of families with lat rines, percent of families receiving >250g soap, percent of households collecting at least 15 liters of water per day, percent of water quality tests meeting necessary standards, and prevalence of GAM Case Definitions and Standards UNHCR HIS case definiti ons and UNHCR standards and indicators were used for much of this ana lysis. Throughout this chapter the following definition s have been used: 1 ) HFU rate is defined as number of new out patient consultations per person per month [46] ; 2 ) incidence r ate is defined as the new cases due to diarrheal disease per 1000 persons per month [46] ; 3 .) w atery diarrhea is defined as persons with diarrhea (passage of 3 or more watery or loose stools in the past 24 hours) with or without dehydrati on [47] 4 .) bloody d iarrhea is defined as person with diarrhoea (passage of 3 or more watery or loose stools in the past 24 hours) and visible blood in the stool [48] ; 5 ) n umber of children under five years of age is defined as the number at mid month of all CU5 from a defined geographic location (can be disaggregated by sex for male/female) [46] ; 6 .) Under 5 mortality rate (UMR) is defined as the numbe r of deaths during the month among children <5 years of age per 1,000 population per month [46] ; 7) a cute moderate malnutrition is defined as children with a weight for heigh t index of < 2 and > 3 z scores [48]

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64 Data Management and Analysis Data were examined for duplication and the dup licates were dropped. C amp s data were stratified into four geographic areas of i nterest for the remainder of the analysis: Ethiopia, Kenya, South Sudan, and Uganda. Characteristics of East African refugee camps were compared across countries. Categorical variables are sho wn in percentage and continuous variables are shown as mean s W ater, sanitation, and nutrition variables were converted into dichotomous variables based on the performance of meeting or failing to meet UNHCR standards [11] Data analysis was conducted in Stata 11.1 and included summary measures of the diarrhea morbidity variables, diarrhea population mortality data variables, a nd WASH nutrition variables. Among camps included in the Diarrhea dataset (n=39; Ethiopia n=15, Kenya n=7, So uth Sudan n=6, and Uganda n=11), t he following variables were examined: incidence rates of watery diarrheal in CU5, the incidence rate of bloody d iarrhea cases in CU5 and HFU rate. Among camps included in the Mortality dataset (n=59; Ethiopia n=28, Kenya n=7, South Sudan n=12, and Uganda n=12) variables examined included a count of mortality cases of watery diarrhea in C U5 count of mortality case s of bloody diarrhea CU5 and total mortality cases of acute malnutrition CU5 Among camps included in the WASH Nutrition dataset, there were twenty four (24) camps in Ethiopia, seven (7) in Kenya, twelve (12) in South Sudan, and fifteen (15) in Uganda.

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65 Re sults C haracteristics of East African refugee c amps Number of Camps Studied for Diarrhea Morbidity, Population Mortality, and WASH Nutrition Datasets The distribution of camp level data from East African refugee camps by country from 2006 2016, including Ethiopia, Kenya, South Sudan, and Uganda is shown in Table 3 2 The total camps include fifty nine (59) camps for Mor tality data, fifty eight (58) for WASH Nutrition, and thirty nine (39) for Diarrheal morbidity dataset. The total camps studied in all thre e (3) datasets represent sixty seven (67) for Ethiopia, thirt y eight (38) for Uganda, thirty (30) for South Sudan, and twenty one (21) for Kenya Over the 11 years (2006 2016), the total camps studied for these three (3) databases numbered one hundred fift y six (156) for Ethiopia, Kenya, South Sudan, and Uganda combined (Table 3 2). Summary data for diarrheal morbidity data Table 3 3 s hows summary data for diarrheal morbidity in UNHCR East African refugee camps by country from 2006 2016. Country level gran d me an was collapsed for HFU rate, the incidence of watery and incidence bloody diarrhea in C U5 by year and coun try. The mean incidence of watery diarrhea among CU5 was highest in Ethiopia (61 cases/1000 C U5/month), Kenya (56 cases/1000 C U5/month), South Sudan (51 cases/1000 C U5/month), and lowest in Uganda (35 cases/1000/ C U5/month) (Table 3 3). In comparison to the incidence of watery diarrhea, the mean incidence of bloody diarrhea among CU5 years old was lower, but countries ranked differently: the hi ghest rate was in South Sudan (7.3 cases/1000 C U5/month), followed by Ethiopia (6.0

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66 cases/1000 C U5/month), Uganda (2.5 cases/1000 C U5/month), and Kenya (0.7 cases/1000 C U5/month). For HFU rate C U5 in Uganda utilize health services more often on average (2 .5 consultation/person/month) than South Sudan (2.3 consultation/person/month), Ethiopia (1.8 consultation/person/month), and Kenya (1.7 consultation/person/month) (Table 3 3). Summary data for WASH nutrition data S ummary data for camp lev el WASH Nutrition standards among UNHCR East African refugee camps by country from 2006 2016 is given in Table 3 4 As indicated, UNHCR standards were used to measure some WASH and Nutrition indicators. These indicators are thus presented as dichotomous variables, where ca mps have either met the UNHCR standard or not. For example, camps may have an average of 22 liters of potable water per person, which is above the threshold of 20 liters of water recommended by UNHCR standard. Thus it meets the standard. Data for each of t hese indicators are presented in Table 3 4. The average mean number of total population of C U5 children across East African refugee camps ranges from 83,679.12 (highest) in Kenya, to 53,065 in South Sudan, 51,392 Ethiopia, and 41,385 in Uganda (lowest) ( T able 3 4). For WASH indicators, variables exam ined (UNHCR standards) include the n umber of liters of potable water per person per day (>20 L), p roportion of families with access to latrine (100%), p ercentage of families receiving at least 250 g (90%) of s oap, p ercentage of HH) collecting at least 1 5 liters of water per day (80%); and p roportion of water quality tests at chlorinated water collection locations compliant with standards (100%).

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67 Based on the 2006 2016 HIS data for East Africa, the proportion of camps meeting the standard of >20 liters of potabl e water per person per day in South Sudan is 20%, in Ethiopia is 37.5%, in Kenya is 62.5%, and in Uganda is 62.5%. The proportion of camps reporting 100% of famil ies with access to latrines was 80% for S outh Sudan, 50% for Ethiopia, 50% for Kenya, and 50% for Uganda. The proportion of camps reporting more than 90% of families receiving >250g soap in Ethiopia was 87.5%, 87.5 % in Kenya 80% in South Sudan, and 37.50% in Uganda The proportion of camps repor ting at least 80% of HH collecting at least 15 liters of water per day was 100% in Kenya, 62.50% in Uganda, 60% in South Sudan and 50% in Ethiopia Finally, the proportion of camps meeting water quality standards ( reporting 100% of water quality tests at chlorinated water collection locations compliant with standards ) was 50% in Ethiopia, 50% in Kenya, 50% in Uganda, and 20% in South Sudan (Table 3 7). The prevalenc e of GAM is set by UNHCR standard to be <10% in refugee camps. From 2006 2016, the proportio n of camps where this standard was met was quite low, ranging from the highest in South Sudan at 40.48%, followed by Ethiopia at 29.57%, Kenya at 23.53% and lowest in Uganda at 17.0% (Table 3 7). HFU Rate, and Incidences of Watery and Bloody Diarrhea in CU 5 across East African refugee c amps: 2006 2016 C haracteristics of Ethiopian refugee camps indicated by HFU rate, the incidence of watery and incidence of blood diarrheal among C U5 is shown in Table 3 5 The year each camp opened ranged from 1986 2014. The total number of observations by camp, which are monthly reports from 2006 to 2016, ranges from 51 in Shimelba to 1 in Leitchuro. The mean of HFU rate (consultation per person per months) ranges from 2.5 in Bonga to 0.1 in T ierkid in 2006 2016. The mean in cidence of watery diarrheal among

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68 CU5 (cases per 1000 population per month) ranges from 127 i n Adi Harush to 0.1 in Sheder. The mean incidence of bloody diarrhea in CU5 across Ethiopia refugee camps ranges from 17.3 in Shimelba to 0.1 in Sheder from 2006 2 016(Table 3 5).Fig ure 3 1 s hows the mean incidence of watery and bloody diarrhea among CU5 across Ethiopian refugee c amps. When comparing the mean incidence of watery and bloody diarrhea among CU5 in Ethiopia c amps, the 3 camps that show a major difference in each camp were: Adi Harush, Bambasi and Sheder (Fig ure 3 1). Table 3 6 s hows characteristics of Kenyan refuge e camps indicated by the mean of HFU rate, the mean incidences of watery diarrhea, and mean bloody diarrhea among CU5 By camp, the total numbe r of observations from 2006 2016, ranges from a high 101 months of reported data in Kakuma to only 4 months of reported data in Kalobeyei. Compared to Ethiopian refugee camps, generally speaking, camps in Kenya a little later, ranging from 1991 (Kakuma) t o 2015 (Kalobeyei). The mean HFU rate among reporting camps ranges from a high of 4.0 visits per person per month in Kalobeyei to only 1.2 visits per person pe r month in Hagadera. The mean incidence of watery diarrhea among CU5 per 1000 population per month in Kenya refugee camps ranges from 142.6 in Kalobeye i to 43.1 in Kakuma. The mean incidence bloody diarrhea among C U5 children per 1000 population per month in Kenya refugee camps ranges from 40 in Kalobeyei to 0.3 in Ifo and Hagadera respectively (Table 3 6). Fig ure 3 2 s hows the mean incidence of watery and bloody diarrhea among CU5 across Kenyan refugee c amps. When comparing the mean incidence of watery and bloody diarrhea in CU5 in Kenyan camps, the top three camps that had a highest incidence rate we re: Kalobeyei, Kambioos, and Ifo2 (Fig ure 3 2).

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69 Table 3 7 s hows characteris tics of South Sudan refugee c amps ind icated by mean of HFU rate, the me an incidence of watery diarrhea, and mean incidence of bloody diarrhea among CU5 By camp, the total number of observations from 2006 2016, ranges from a high 17 months of report ed data in Lasu to only 1 month of reported data in Gorom. Compared to Ethiopian and Kenyan refugee camps, camps in South Sudan opened later, ranging from 2008 (Makpandu) to 2012 (Gendrass a, Ezo, and Kaya) (Table 3 7). The mean HFU rate among reporting camps ranges from a high of 3.5 visits per person per month in Gendrassa to 1.3 visits per person per mo nth in Lasu and Ezo The mean incidence of watery diarrhea among CU5 per 1000 populatio n per month in South Sudanese refu gee camps ranges from 107.1 in Gendrassa to 2.7 in Ezo. The mean incidence bloody diarrhea among CU5 per 1000 population per month in South Sudanese refugee camps ranges from 15.1 in Gorom to 1.0 in Lasu (Table 3 7). Fig ur e 3 3 s hows the mean incidence of watery and bloody diarrhea among CU5 across South Sudanese refugee ca mps. When comparing the mean incidence of watery and bloody diarrhea in South Sudanese Camps, the top three (3) camps that has the highest rate of watery and bloody diarrhea were Gendrassa, Gorom, and Kaya (Fig ure 3 3). Table 3 8 s hows char acteristics of UNHCR in Uganda refugee c amps indicated by the mean HFU rate, mean incidences of watery and bloody among CU5 2006 2016. Compared to Ethiopian, Kenyan a nd South Sudanese refugee camps, camps in Uganda are much older established from 1959 (Oruchinga and Nakivale) to 2016 (Ikafe). The total number of observations by camp, which are monthly reports from 2006 to 2016; ranges from 70 in Kiryand ongo to 13 in Ik afe. The mean HFU rate among

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70 reporting camps ranges from a high of (6.0) visits per month in Nyakabanda to 0.9 visit per persons per month in Adjumani. The mean incidence of w atery diarrhea among CU5 per 1000 population per month in Uganda refugee camps ra nges from 142.4 in Nyakaban da to 6.8 in Imvepi. The mean incidence of bloody diarrhea in CU5 across Uganda refugee camps ranges from 7.1 in Nyakabanda to 0.2 in Imv epi from 2006 2016 (Table 3 8). Fig ure 3 4 s hows the mean incidence of watery and bloody di arrhea among CU5 across Ugandans refugee camps, 2006 2 016. When comparing the mean incidence of watery and bloody diarrhea in Ugandans Camps, the top three with highest rate were Nyakabanda, Kyaka II and Imvepi (Fig ure 3 4). Results of Diarrheal Mortalit y among CU5 across East African refugee c amps: 2006 to 2016 Having provided an overview of the data sets by characterizing three main morbidity indicators by country; the mean HFU rate, the average mean incidence of watery diarr heal, among CU5, and the mea n incidence of bloody diarrhea among CU5 the remainder of this chapter will focus on diarrheal mortality data. These data, presented for all UNHCR reporting East African refugee camps combined, include total counts of cause specific mortality among CU5 by Sex and mean mortality cases of watery, bloody, and acute malnutrition among CU5 Total counts of cause specific mortality among CU5 by sex across all UNHCR reporting East African refugee camps Table 3 9 s hows the total counts of cause specific, sex disa ggregated mortality among CU5 in East African UNHCR reporting refuge e's camp between 2006 and 2016. Consistent with findings a greater number of male children reportedly died from watery diarrhea (507) compared to female (440) (Table 3 9). There were also more mortality cases from bloody diarrhea among m ales (40) than females (32) (Table 3 9). In

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71 contrast, the number of female children who reportedly died from acute ma lnutrition (807) was higher than m ales (796) (Table 3 9). Though the difference in these number s is small it is not anticipated, given that boys suffer ed from higher rates of malnutrition than girls do Over the course of 11 years (2006 2016), the total number of reported deaths due to watery or bloody diarrhea and acute malnutrition wa s 2 62 2 across refugee camps in four East African countries (Table 3 9). Average mean mortality cases of watery, bloody and acute malnutrition among CU5 in East African refugee camps. Table 3 10 s how s the characteristics of mean mortality c ases of watery, bloody diarrhea, and acute malnutrition in CU5 East African refugee camps by c ountry from 2006 2016. The number of possible observations for the country of Ethiopia was 1 396 camps (including the multiple camps counted in the course of 11 year). For Ethiopia ref ugee c amps, the mean of mortality total cases of watery, bloody and all diarrhea (watery plus bloody) among CU5 was 0.12 /1 000 (0.012%), 0.009/1000 (0.009%), and 0.13/1000 (0.013%) respectively. The mean mortality cases of acute malnutrition in Ethiopia r efugee camps in C U5 children is 0.14/1000 (0.014%) (Table 3 10). For Kenyan refugee c amps, there were 265 total number of observations (multiple camps counts from 2 006 to 2016). For Kenya refugee c amps, the mean of mortality total cases of watery, bloody and all diarrhea (Watery Plus Bloody) among CU5 was 0.38 /1000(0.038%), 0.011/1000 (0.0011%) and 0.39/1000(0.039%) respectively. The mean of mortality total cases o f acute malnutrition in Kenyan refugee c amps among CU5 is 1.2/ 1000 (0.12%). For the country of South Sudan, the number of observations was 383 (number of camps data collected including a camp being counted multiple times throughout the

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72 years). For the hosting refugee country, South Sudan, the mean of mortality cases of watery, bloody and all dia rrhea (watery plus bloody) among CU5 was 0.44 /1000 (0.044%), 0.039/1000 (0.0039%) and 0.48/1000 (0.048%) respectively. The mean mortality cases of acute malnutrition in South Sudanese refugee c amps among CU5 is 0.14/ 1000 (0.014%) (Table 3 10). Lastly, for Uganda, there was observations for nearly 11 years (2006 2016). For the Ugandan refugee camps, the mean of mortality cases of watery, bloody and all diarrhea (watery plus b loody) among CU5 was 0.07 /1000 (0.007%), 0.013/1000 (0.0013%) and 0.09/1000 (0.009% ) respectively. The mean mortality total cases of ac ute malnutrition in Ugandan refugee c amps among CU5 is 0.08/1000 (0.008%) (Table 3 10). Conclusion Remarks This chapter has characterize d morbidity and mortality associated with diarrheal disease among CU 5 across East Africans refugee c amps f rom 2006 to 2016. T he researcher examined the total camps studied which ranges from 39 for Morbidity Diarrhea data, 58 for WASH Nutrition Data and 59 for Mortality Diarrheal data from 200 6 2016 (Table 3 2). The mean in cidence of watery diarrhea among CU5 across East African refugee c amps from 2006 2016 was highest (61/1000/month) in Ethiopia. In 2011, UNHCR documented that Acute Water y Diarrhoea (AWD) or c holera was endemic in five countries, Somalia, Djibouti, Uganda, and Ethiopia [49] In Ethiopia, diarrhea ple hence at risk of communicable [49] Some of the factors that may explain the higher incidence of watery in CU5 in Ethiopia include more refugee camps (38.5%) compared

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73 to (28.2%) in Uganda, (18%) in Kenya and (15.4%) in South Sudan (See Table 3 2). Also due to unforeseen civil war conflicts in neighboring countries such as South Sudan, Somalia, and Sudan, there has been a huge influx of re fugees into Ethiopia. Recently, it become hosting [50] South Sudan camps have the highest me an incidence of bloody diarrhea, 7.3/1000/mont h from 2006 2016. In 2012, UNHCR documented that there was a "sharp increase of bloody diarrhea cases "in Yida refugee camp in South Sudan, which experienced "newly arrivals [that has] doubled the refugee population" [51] Furthe rmore, the average mean incidence of bloody diarrhea was lowest in Kenyan Refugee Camps (0.7/1000/months) from 2006 2016. The relatively low b loody diarrhea in Kenyan water [11] from 2006 to 2016. Only 20% of South Sudanese refugee camps met the UNHCR Sta ndard of camps reporting an appropriate number of liters of potable water available per person per day (>20L). UNHCR has documented that to address clean and sufficient drinking water, they are drilling more wells, additional amounts of chlorine are being use d at water points, and they are working to increase awareness of WASH and nutrition strategies, specifically targeting the youth within the population of refugees [51] d buckets to all families with CU5 [51] to address this problem.

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74 About 100% of Kenyan r efugee camps met the UNHCR Standard of camps report ing more than 80% of HH collecting at least 15 liters of water per day. This finding may re flect improve access to water in the Kenyan refugee c amps from 2006 2016. When looking at the camp characteristics of reporting ref ugee camps across East African refugee c amps, the higher mean incidence of watery diarrhea in CU5 are predominantly from new ly established camps, ranges: 107/1,000/month in Gendrassa (2012) in South Sudan, 127/1,000/month in Adi Harush (2010) in Ethiopia, 142.4/1,000/month in Nyakabanda (2012) in Uganda and 142.6/1000/month in Kalobeyei (2016) in Kenya. In the HIS Data, it was clear that incidence of watery diarrhea among CU5 was more prevalent than the incidence of bloody diarrh ea throughout the East African r efugee camps from 2006 2016. In fact, the implementing agencies working along UNHCR should be aware of the high incidenc e of watery diarrhea when they are working in these camp settings. From 2006 to 2016, the total count of cause specific death among CU5 across East African refugee camps was 2622 (Table 3 9). Hershey et al. 2011 supported these findings he relatively low proportion of deaths due to diarrhea may (p.24) [11] in [East African refugee c amps] from 2006 2016. Finally, camps in South Sudan have the highest child mortality due to watery diarrhea ( 44%) and bloody diarrhea (3.9%), as compared to camps in Ethio pia, Kenya, and Uganda (Table 3.10). UNHCR has documented the worsening scenario in refugee camps in the South Sudan, as they continue to receive large inflows of new refugees with heightened concern about implications for disease [51]

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75 Table 3 1 Total registered refugees and asylum s eekers across East African refugee c amps in 2017 [39 42] Country, Year Total population of refugees/ asylum seekers Na tionality of refugees/ asylum seekers (number or proportion) Proportion of CU5 among refugees/ asylum seekers Sex composition of children under five among refugees/ asylum seekers Ethiopia 829,925 South Sudanese:366,198 Somalis: 246,742 Eritreans: 168,44 7 Sudanese: 41,031 Yemenis: 1,643 Other Nationalities: 5,864 14.1% Female:7.0% Male: 7.1% Kenya 488,045 Somalia: 288,296 South Sudan: 107,806 DR. Congo: 13,450 Ethiopia: 17,891 Sudan: 2,952 Other: 3,915 15.3% Female:7.5% Male: 7.8% South Sudan 268,286 Sudan: 247,111 DRC: 14,548 Ethiopia: 4,738 CAR: 1,853 20% Female: 9% Male:11% Uganda 1,252,470 South Sudan: 898,864 DRC: 227,413 Burundi:45,993 Somalia:42,826 Rwanda:17,147 Others:20,227 Not provided Not provided

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76 Table 3 2 Geographic breakdown of cam p level data included in UNHCR Diarrhea, Mortality, and WASH Nutrition datasets from 2006 2016 Variable Ethiop i a Kenya South Sudan Uganda Total Camps Studied # Camps Studied for Diarrhea Data 15 7 6 11 39 # Camps Studied for Mortality Data 28 7 12 12 59 # Camps Studied for WASH Nutrition Data Data 24 7 12 15 58 Total # Camps Studied for all of the 3 datasets 67 21 30 38 156 Table 3 3 Summary data for diarrheal morbidity in UNHCR East African refugee camps by country level grand mean from 2006 2016 V ariable Ethiopia Kenya South Sudan Uganda M ean incidence of watery diarrheal in C U5 61 56 51.0 35 M ean incidence of bloody diarrhea in C U5 6.0 0.7 7.3 2.5 M ean of HFU rate 1.8 1.7 2.3 2.5

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77 Table 3 4 Summary data of camp level WASH Nutrition standa rds met among UNHCR East African refugee camps by country from 2006 2016 Variable Ethiopia Kenya South Sudan Uganda Country level grand mean Total Population of C U5 51,392 83,679 53,065 41,385 Percent of camps reporting appropriate number of liters of po table water available per person per day (>20L) 37.50% 62.50% 20.00% 62.50% Proportion of camps reporting 100% of families with access to latrine 50.0% 50.0% 80.0% 50.0 % Proportion of camps reporting >90% families receiving >250g soap 87.50% 87.50% 80 .0% 37.50% Proportion of camps reporting more than 80% of H ousehold collecting at least 15 liters of water per day 50.0% 100 % 60.0 % 62.50 % Proportion of camps reporting 100% of water quality tests at chlorinated water collection locations compliant with standards 50.0% 50.0% 20.00% 50% Proportion of camp/months reporting GAM Prevalence of less than 10% 29.57% 23.53% 40.48% 17.02%

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78 Table 3 5. Camps characteristics of UNHCR reporting refugee camps in Ethiopia: 2006 2016 Country Year Camp opened Camp #m onth Observed Pooled m ean of HFU rate consultation/person/ month Pooled m ean i ncidence watery diarrhea in U5 cases/1000 population/month Pooled m ean i ncidence bloody diarrhea in U5 cases/1000 population/month Ethiopia 1986 Dimma 18 1.8 41 2.8 1990 Bonga 19 2.5 48 5.4 1991 Kebribeyah 22 1.2 20.3 0.3 1993 Fugnido 22 0.9 18 3.2 1997 Sherkole 29 1.4 25.1 4.4 2004 Shimelba 51 2.1 75 17.3 2007 Awbarre 12 0.9 34.5 6.6 2010 Sheder 18 1.8 80 0.1 2010 Bokolmanyo 2 0.74 11.2 1.5 2011 Tongo 6 1.6 70 2.4 2010 Adi Harush 2 0.5 127 30 2008 Aysaita 2 1.2 45.5 0.5 2012 Bambasi 1 1.8 89.1 10.4 2014 Tierkidi 2 0.1 21 6 2014 Leitchuor 1 1.7 39 11 Total number of months observed from 2006 2016 N/A N/A 207 N/A N/A N/A

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79 Figure 3 1. M ean inc idence of watery and bloody in CU5 across Ethiopian refugee c amps: 2006 2016 0 20 40 60 80 100 120 140 Dimma Bonga Kebribeyah Fugnido Sherkole Shimelba Awbarre Sheder Bokolmanyo Tongo Adi-Harush Aysaita Bambasi Tierkidi Leitchuor Ethiopia Mean incidence of watery and blood in CU5 across Ethiopian refugee camps:2006 2016 Average mean incidence of watery diarrhea CU5(cases per 1000/month) 2006-2016 Average mean incidence of bloody diarrhea CU5(cases per 1000/month) 2006-2016

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80 Table 3 6 Camp charact eristics of UNHCR reporting refugee camps in Kenya: 2006 2016 Country Year Camp opened Camp #month Observed Pooled mean (HFU) rate consultation/person/ mo nth Pooled mean in cidence watery diarrhea in CU5 cases/1000 population/month Pooled mean i ncidence bloody diarrhea in CU5 cases/1000 population/month Kenya 1992 Kakuma 101 1.8 43.1 0.5 1992 Ifo 101 1.7 61.3 0.3 1992 Dagahaley 101 1.6 59.1 0.7 1 992 Hagadera 101 1.2 43.3 0.3 2011 Kambioos 62 2.0 64.0 0.8 2011 Ifo 2 55 2.0 62.1 0.4 2016 Kalobeyei 4 4.0 142.6 4.0 Total number of months observed from 2006 2016 N/A D N/A 525 months observed N/A N/A N/A

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81 Figure 3 2. M ean incidence of w atery and bloody diarrhea in CU5 in Kenyan refugee camps : 2006 2016 0 20 40 60 80 100 120 140 160 Kakuma Ifo Dagahaley Hagadera Kambioos Ifor 2 Kalobeyei Kenya Mean incidence of watery diarrhea in CU5 in Kenyan refugee camps:2006 2016 Average mean incidence of watery diarrhea CU5(cases per 1000/month) 2006-2016 Average mean incidence of bloody diarrhea CU5(cases per 1000/month) 2006-2016

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82 Table 3 7 Camp Characteristics of UNHCR reporting refugee camps in South Sudan: 2006 2016 Country Year Camp opened Camp #month Observed Pooled m ean HFU rate A consultation/ person/mont h Pooled mean incidence of watery diarrhea in CU5 cases/1000 population/month Pooled mean incidence of bloody diarrhea in CU5 cases/1000 population/month South Sudan 2008 Makpandu 12 2.1 54.2 7.6 2009 Lasu 17 1.3 13.1 1.0 2012 Gendrassa 14 3.5 107.1 7.3 2012 Ezo 4 1.3 2.7 6.0 2012 Kaya 11 3.3 80.0 C 8.8 2010 Gorom 1 2.4 93.0 15.1 Total month observed N/A D N/A 59 months observed N/A N/A N/A

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83 Figure 3 3 M ean incidence of watery and bloody diarrhea in CU5 in South Sudan refugee camps : 2006 2016 0 20 40 60 80 100 120 Makpandu Lasu Gendrassa Ezo Kaya Gorom South Sudan Mean incidence of watery and bloody diarrhea in CU5 in South Sudan refugee camps: 2006 2016 Average mean incidence of watery diarrhea CU5(cases per 1000/month) 2006-2016 Average mean incidence of bloody diarrhea CU5(cases per 1000/month) 2006-2016

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84 Table 3 8 Camp Characteristics of UNHCR reporting refugee camps in Uganda: 2006 2016 Country Year Camp opened Camp #month Observed Pooled mean of (HFU) rate Pooled m ean of Incidence rate of watery diarrhea in CU5 cases/1000 Pooled m ean o f Incidence rate of bloody diarrhea in CU5 cases/1000 Uganda 1995 Kiryandongo 70 2.0 13.0 0.61 1968 Kyangwali 64 1.5 21.0 3.4 1989 Adjumani 54 0.9 15.2 2.5 1995 Rhino Camp 48 1.8 20.0 6.9 1959 Oruchinga 46 3.4 22.0 1.5 1959 Nakiva le 39 1.7 17.0 2.0 R eopened in 2016 Palorinya 36 1.3 15.2 4.0 1983 Kyaka II 32 1.3 24.0 2.5 2012 Nyakabanda 28 6.0 142.4 7.1 2016 Imvepi 23 1.5 6.8 0.2 N/A Ikafe 13 1.2 23.9 4.5 Total months observed N/A N/A 453 months observed N/A N/A N/ A

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85 Figure 3 4 M ean incidence of watery and bloo dy diarrhea in CU5 in Ugandans refugee c amps: 2006 2016 0 20 40 60 80 100 120 140 160 Kiryandongo Kyangwali Adjumani Rhino Camp Oruchinga Nakivale Palorinya Kyaka II Nyakabanda Imvepi Ikafe Uganda Mean incidence of watery and bloody diarrhea in CU5 in Ugandan refugee camps: 2006 2016 Average mean incidence of watery diarrhea CU5(cases per 1000/month) 2006-2016 Average mean incidence of bloody diarrhea CU5(cases per 1000/month) 2006-2016

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86 Table 3 9. Total counts of Cause specific Mortality among CU5 by sex across al l UNHCR reporting East African refugee c amps 2006 2016. Variable Total Counts/Sum Mortality cases from watery diarrhea (male) 507 Mortality cases from watery diarrhea(female) 440 Morta lity cases from bloody(male) 40 Mortality cases from bloody (female) 32 Mortality cases from acute malnutrition(male) 796 Mortality cases from acute malnutrition (female) 807 Total Counts/sum 2622

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87 Table 3 10 Child mortality due to watery, bloody diarrhea and acute malnutrition across East African refugee camp s by Country level grand mean : 2006 2016 Country Number of Observations (n) Mean mortality cases of watery diarrhea <5 per 1000 Mean mortality cases of bloody diarrhea <5 per 1000 All mean mortality diarrhea (watery+b loody) <5 per 1000 Mean mortality c ases of Acute malnutrition <5 per 1000 Ethiopia 1396 0.12 0.009 0.13 0.14 Kenya 265 0.38 0.011 0.39 1.2 South Sudan 383 0.44 0.039 0.48 0.14 Uganda 993 0.07 0.013 0.09 0.08

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88 CHAPTER 4 A CROSS SECTIONAL ANALYSIS OF RISK FACTORS FOR INCIDE NCE OF WATERY DIAR RHEA AMONG CHILDREN UNDER FIVE (CU5) IN EAST AFRICAN REFUGEE CAMPS IN 2016 Introduction Global Burden of Diarrhea Disease in CU5 Diarrheal diseases are the leading causes of morbidity and mortality in CU5 in developing countries [34] Another study conducted by Black and colleagues (2003) underscores that the three quarters of death of CU5 gl obally occur in sub Saharan Africa and in South Asia (34% and 41%, respectively) [35] Mor eover, this study highlights that half of all mortality among CU5 occurs in only six countries: India, Nigeria, Chi na, Pakistan, DRC, and Ethiopia [35] A study in 90 UNHCR refugee camps found diarrheal disease as one of the major causes of morbidity (7%) and mortality (7%) among CU5 [11] T his research focus on the diarrheal di sease among CU5 in East African r efugee c amps in Et hiopia, Kenya, South Sudan and Uganda in 2016. Africans refugee camps. To reduce morbidity and mortality in refugee camps, there has to be a good healthcare system, clean wate r, and sufficient food rations [52 54] Hershey et al. ( 2011 ) emphasized that a lack of sanitation and contaminati on of drinking water contribute to increased risk of diarrhea in 90 UNHCR refugee camps [11] UNHCR is mandated by the UN to provide clean water to refugees a s a basic human right [55] but there is still a lack of adequate access to water and sanitation in many refugee hosti ng countries, including; Uganda, Chad, Kenya, and DRC [55] An illustration of the impact of a l ack of clean water was seen in 1994 when Rwandans fled genoci de as refugees to DRC, and around 60,000 people died due to

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89 "water shortage and consequent cholera" (p.12 14) [55] .These findings are reinforced by additional empirical evidence showing that unsafe water sources are associated with diar rheal disease among refugees [56] In the refugee camp settings, w omen perform a majority of domestic labor incl uding water and fuel collection outside of the refugee camps. In Uganda it has been reported that when women collect water outside of the camps, the y often became victims of violence and rape, begin attacked by the rebel group the Army (LRA) [55] It is thus understable, in such circumstances where women fear for their lives, that they may resort to collecting water that is known to be or coming from unhygienic (p.12 14) [55] These cost benefit analyses are a dai ly Finally, the other important risk factors for diarrheal disease in the refugee camps that have been documented are overcrowding, inadequate shelter, poor access to water and sanitation and sharing a latrine [11, 16] Rationale for Conducting a Study on Risk Factors for Inci dence of Watery Diarrheal among CU5 in East Africans refugee c amps in 2016. In 2015, the United Nations (UN ) launched the Sustainable Development Goals (SDG) in an effort to garner global support and coordinate efforts among the agencies that provide healt h servi ces, clean water and sanitation. SDG 3 is to reduce child mortality [57] and SDG 6 is to secure water and sanitation by 2050 [58] Meeting SDG 3 Goo d Health, and SDG 6 Clean Water and Sanitation will require a better understanding and interventions t o improve the status of refugee camps across the world [59]

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90 One of the SDG Goal 3 targets is to end preventable deaths of newborns and [ CU5 ] with a ll countries aiming to reduce neonatal mortality to at least 12 per 1, 000 live births and [CU5 ] mortality to at least 25 per 1,000 live births" by 2030 [60] For SDG 6, the target according to the United Nations Developme nt Programme (UNDP) to achieve universal and equitable access to safe and affordable drinking water, achieve access to adequate and equitable sanitation and hygiene, and end open defecation by 2030 [61] To fulfill and implement SDGs 3 and 6, there is a need to conduct a systematic review of the existing risk factors, morbidity, and mortality associated with diarrheal disease among C U5 There is also a need to understand how the risk factors of refugees may differ from those of other populations, and t here is a need to quantify risk factors that are statistically assoc iated with diarrheal disease in CU5 such that agencies wo rking in these refugee camps can develop data driven strategic plans to improve children lives and meet the SDGs. These gaps were highlighted in a 2008 study in which the authors pointed out esearch on water, sanitation and hygiene promotion issues among refugee populations has remained a challenge" (p.1 13) [37] Authors explained that the death of data available on refugees is at least in part due to the difficulty of collecting data in the refugee camps because of "security restrictions, complex operational conditions, scarce resources, understaffing or high staff turnover, and the fact that refugee camps are forcibly located on marginal lands" (p.1 13) [37] All these factors combine to limit our knowledge and understanding thus ability to intervene of the impact of diarrheal disease on refugee children.

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91 East Africans Refugee Hosting Countries in 2016 UNHCR routinely monitors selected demographic, public health, and WASH indicators across East African refugee camps UNHCR produced a 2016 report on the East African refugee h osting countries that is available on the UNHCR website titled UNHCR Public Health 2016 Annual Global Overview [62] UNHCR produces yearly site reports for each camp, providing information on key health indic ators and services that fall below or meet the UNHCR standards [11] For example, UNHCR has standard indicators such as Health Utilization (HU) rate (1.4 new visits/person/year), the average liters p er person per day (>20), and the average / communal toilets (<20). Table 4 1 s hows East African refugee hostin g countries in 2016. The total number of registered refugees in Ethiopia was 742,725, 15% of whom are CU5. The origin s of the refugees registered were: South Sudan Somali, Eritrea, and various other countries [63] Additionally, the HU rate ranged from 0.3 2.9 new visits/person/year, the average number of liters water/ p erson/ day was 13 26, and the number of /communal toilets was between 5 56 ( Table 4 1). In 2016, the total registered refugee population in Kenya was 523,498, the proportion of CU5 was 16%, and home countries of the refugee were Somalia, South Sudan, Ethiopi a and DRC [64] In Kenyan refugee camps, the HU rate was 1.5 2.9, the average l iters of water/ person / day was 13 36, and the number of persons / communal toilets was 3.4 to 10.8 in 2016 [64] (Table 4 1). The total population of registered refugees for South Sudan in 2016 was 763,752, the proportion of CU5 was 22%, and the origin of refugees included Sudan, DRC, Central African Republic (CAR) and Ethiopia [65] Among refugees in South

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92 Sudan in 2016, the HU rate was 0.8 3.5, the averag e liters of water/person/day ranged from 15 21, and the number of persons/communal toile t in South Sudan refugee camps was 7.6 43.1 in 2016 (Table 4 1) [65] In 2016, The total registered refugees in Uganda camps was 828,862, the proportion of CU5 was 20%, and most refugees in Uganda were from South Sudan, DRC, Somali a, and Burun di [66] Among registered ref ugees in Uganda, the HU rate ranged from 0.4 5.6, the average liters of water /person/day was 13 32, and the person per communal toilets/latrines was 3.7 44.0 (Table 4 1) [66] In 2016, camps in Uganda had the largest total population of refugees (828,862 individuals) compared to other East Africans countries and these refugees utilize health services more frequently compared to ref ugees in camps in Ethiopia, Kenya, and South Sudan (Table 4 1). In 2013, civil war broke out in the newest nation of South Sud an, and many South Sudanese fled the conflict into Uganda, where they remain today as refugees. Also, plenty of refugees are fleei ng DRC due to the ongoing civil war there, again, arriving as refugees in Ugandan camps. The neighboring countries into Uganda refugee camps has a tremendous impact on livelihood of the vulnerable populati ons who resided i n these refugee camps. Moreover, the more refugee utilizes health services in Ugandans camps, the more they will increase the high risk of incidence of watery diarrheal in these refugee camps. Research Question The documented burden of diarrheal disease in the refugee camps, especially among the vulnerable population such as children and commitment to contribute to the UN efforts to fulfill the SDGs contributed to the development of the following

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93 research question, "What are the primary risk factors fo r watery diarrheal among CU5 in East African refugee camps in 2016?. Methods Study setting D iarrheal disease is one of the major causes of morbidity and mortality among C U5 in the refugee camps. This study is a cross sectional analys is of risk factors fo r watery diarrhea among CU5 in East Africans refugee camps in 2016 with a specific focus on Ethiopia, Kenya, South Sudan and Uganda. Through the UNHCR Public Health 2016 Annual Global Review, the research is based on reports for 23 camps in Ethiopia, 7 re fugee camps in Kenya, 8 refugee camps in South Sudan, a nd 9 refugee camps in Uganda [64]. Data For this research, the dependent variable (DV) was the incidence of watery diarrhea in CU5 in East African refugee camps, and the independent v ariables (IV) we re categorized into key health indicators including information on demographics public health ser vice usage, water availability, and sanitation and hygiene (WASH) (Table 4 2). The researcher created an excel table and extracted the DV and IVs based on th e 2016 c amp level reports. The incidence of watery diarrhea among CU5 at each camp level was imported to the excel table. The demogr aphic indicators extracted included the origins of refugees, the age of the camp and proportion of CU5 across East African refugee camps. The public health variables imported into the excel chart were the HU rate and the proportion of host population consultations for 2016 (Table 4 2). Th e WASH Variables included were the number of concerned persons per water tap, proportion o f households collecting drinking water from protected water sources only,

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94 proportion of households with sufficient daily water storage capacity, refugees per latrine/toilet, proportion of households with drop hole latrine, and proportion of households repo rting defecating in a toilet (Table 4 2). The se data were extracted saved as a new dataset that was then exported from excel as a CSV file and imported into Stata 11.1 (StataCorp, Col lege Station, Texas 77845 USA) for Data analysis. For measurement of the DV, the incidence of watery diarrhea was defined as passage of 3 or more wat ery or loose stools in 24 hours with or without dehydration" (p.1 43) [48] Th e UNHCR report contained the incidence of watery diarrheal among CU5 in East Africans Refugee camps for 2016, thus this data was extracted and added to the dataset. T he as a binary variable ( 0 = fixed, and 1=mixed) ( Table 4 2), where f ixed represents one single country of origin (i.e., South Sudanese), and m ixed represents multiple countries of origin ( i.e., South Sudan and Somalia or more). Another variable that was created was the age of the camp. To create this va riable, the researcher subtracted the year camp opened from the year of the study (i.e., 2016 minus 2006 = 10 years the camp has been opened). Also for this study, the researcher used the UNHCR defin ition of standard s and indicator s. A s tandard is defined (indicator) that has to be reached or maintained to avoid the occurrence of unacceptable conditions for refugees and persons of concern or unacceptable levels of performance. The indicator is define d as "a variable scale on which it is possible to measure different points objectively, and that corresponds to or correlates closely with variations in the conditions of the refugee and persons of concern" [67] (Table 4.2).

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95 The IVs were examined for their association with incidence of watery diarrhea in CU5 across East African refugee camps in 2016. Data Analyses Data analysis was conducted in R 3.4. 2 software, and included summary measures incidence of w atery diarrhea in East African refugee c amps in 2016. The researcher conducted a univariate and multivariate Gamma Distribution regression analysis to identify risk factors associated with the inciden ce of watery diarrhea disease. The researcher used the Gamma D istribution because most of the variables were continuous wit h a skewed distribution, and the DV is "real valued" in a range from zero to thousands (0 1000) [68] For the univariate regression, the researcher was able to model the DV dependent (incidence of watery dia rrhea) with Gamma Distribution by each IV shown in Table 4 4. This Tabl e 4 4 also displays the coefficient and p value as summary measures of the regression results The researcher first created the univariate models for each of the risk factors and IVs that, might affect the yearly incidence of watery diarrhea in each camp. If the researcher found that the risk factor (covariates or IVs) were even mar ginally significant (using p<.2 ) the researcher considered those variables for inclusion in the final m ultivariate model for predicting the incidence of watery diarrhea, considering these risk factors as potential predictors for the incidence of watery diarrhea. After fitting the final multivariate model, the researcher excluded the variables gradually acc ording to the highest p value retaining only those variables in the model significant at the .05 level or below (Table 4 5). The researcher mapped the location of camps in ArcMap 10.5.1 and then mapped attributed data on the incidence of watery diarrheal among by the refugee

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96 hosting countries for 2016 The researcher then mapped the country aggregated average mean and Standard Error (SE) of the mean for the significant variables by host country (Table 4 5). Results Camp Characteristics of the IVs in East African Refugees Camps in 2016 Table 4 3 shows camp characterist ics of the IVs in East African refugee c amps in 2016. Over a third refugees came fro m mixed or multiple countries of origin (36%). The mean average camp age for East African refugee camps was 13 years in 2016. The proportion of CU5 across the East Afr ican refugee Camps in 2016 was 21% Across East African refugee c amps in 2016, the average mean HU rate was 1.64 new visits/ refugee/year, which met UNHCR standard for HU rate of 1 4. The proportio n of host population consultations (surroundings communities around the refugee camp) was (16%) in 2016. The average mean number of liters of potable water available per person per day was 20.4, which did not meet UNHCR Standard of >20 liters of potable wa ter need for person per day The average mean number of persons of concern per water tap in East African r efugee camps in 2016 was 191.5, which did not meet UNHCR Standard of <80 number of person of concern per water tap. The proportion of households coll ecting drinking water from protected water sources only in East African refugees c amps in 2016 was (99%) which did m e et UNHCR Standard of >95% ( See Table 4 2 and Table 4 3). The proportion of households with sufficient daily water st orage capacity in East Afri can R efugee camps, 2016 was 62% which did not meet UNHCR standard of >80% (Table 4 3). The average mean number of refugees per toilet in East African refugee c amps in 2016 was 17.0 which met the UNHCR standard of <20 (Table 4 2). The

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97 proportion of ho useholds with drop hole latrines was 54% across the regions. No UNHCR Standard was provided for this indicator ). The proportion of households reporting defecating in a toilet was (92%), which exceeded the UNHCR Standard of >85% (Table 4 2). Table 4 4 shows un ivariate analysis for selected demographics, access and utilization, water, sanitation and hygiene (WASH) indicators for the incidence of watery d iarrhea among CU5 in 2016. For camps under consideration, the camps with the mixed country of origin had a lower risk of incidence of watery diarrhea (coefficient 0.61, p value 0.65 ) compared to the single country of origin camps (coefficient 0.48, P value 0.6). An increase in the age of the camp incre ase the in cidence of watery diarrhea by 4 per thousand ( co efficient 0.004, p value, 0.1 ). One unit increase in the proportion of CU5 in the refu gee camps significantly increase the incidence of watery diarrhea by 0.0735 units (coefficient 0.0735 p value, 0.01). Each one unit increase in the HU rate significantly reduces the risk of incidence of watery diar rhea by 49 % ( 0.0049, p value 0.00 ) (Table 4 4). A one unit increase in the proportion of host population consultations increase the inci dence of watery diarrhea by 0.0373 units (coefficient, 0.0373 p value 0. 1 ,) among CU5 across East Africa Refugee c amps in 2016. A one unit increase in the mean number of liters of potable water a vailable per person per day reduces the inci dence of watery diarrhea by 0.0007 times (coefficient 0.0007, p value 0.1 ) (Table 4 4). A one unit increase in the number of persons of conc ern per water tap significantly reduces the in cidence of watery diarrhea by 0.004 units (Coefficient 0.0044, p value 0.03 ).

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98 A one unit increase in the proportion of households with sufficient daily water storage capacity significantly reduces the inc idence of watery diarrhea by 00.019 times (coefficient 00.019, p value 0.03 ). A one unit increase in refugees per latrine/ toilet reduces the incid ence of watery diarrhea by 0.0122 times (coefficient 0.0122 p value 0.2 ). A one unit increase in the proportion of househol ds with drop hole latrines reduces the inc idence of watery diarrhea by 0.013 times (coefficient 0.013 p value 0.1 ). A one unit increase in the proportion of households re porting defecating in a toilet reduces the inc idence of watery diarrhea by 0.044 times /units (coefficient 2.0, p value 0.1) among CU5 across East Africa Refugee c amps in 2016 (Table 4 4). Table 4 5 shows, Multivariate Analysis of Incidence of Watery Diarrheal among CU5 acr oss East African Refugee c amps in 2016 including d emographics, a ccess and utilization, water, sanitation and h ygiene (W ASH) indicators. The multivariate model showed the following: One year increase in the age of the camp, increase the incidence of water y diarrheal by 0.03 unit s (Coefficient 0.03, p value, 0.2). A one unit increase in the proportion of CU5 in the refugee camps si gnificantly increase the incidence of watery diarrhea by 0.8 (coefficient 0.8, p value, 0.002 ). A one unit increase in HU rate s ignificantly reduces the reporting of the incidence of watery diarrhea by 0.6 units ( 0.6 p value 0.03 ) (Table 4 5). A one unit increase in proportion of host population consultations increase the incidence of watery diarrhea by 0.03 units (coefficient 0 .005, p value 0. 9 ) A one unite increase in average number of litres of potable water available per person per day; increase the incidence of watery diarrhea by 0.005 units (coefficient 0.005, p value 0.9).

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99 A one unit increase in the number of persons of concern per water tap increase the incidence of watery diarrhea by 0. 002 (0.00 2 p value 0.2 ) A one unit increase in proportion of households with sufficient daily water storage capacity increase incidence of watery diarrhea by 0.04 units ( co efficient 0.0 4, p value, 0.9). A one unit increase in proportion of households with drop hole latrine increase incidence of watery of diarrhea by 0.05 units (coefficient 0.05, p value 0.9). A one unit increase in the proportion of households report ing defecating in a t oilet reduces the inc idence of watery diarrhea by 0.1 times (coefficient 0.1, p value 0.6 ) among CU5 in East Africa r efugee c amps in 2016 (Table 4 5). Sample Sizes of the Multivariate Si gnificant Variables by Hosting r efugee Countries in 2016 Table 4 6 shows sample size of the significant multivariate variables by hosting refugee countries in 2016. For the average mean incidence among C U5 the sample size range from 7 camps in Kenya, 8 camps in South Sudan, 9 camps in Uganda and 23 camps in Ethiopia. For the average mean proportion of CU5 and average mean HU rate, the sample size was similar to the incidence sample size mentioned above (Table 4 6). For the average mean number of persons of concern per water tap, the sample size range from 5 camps in Sou th Sudan, 7 camps in Kenya, 8 ca mps in Uganda, and 23 camps in Ethiopia. The average mean refugees per latrine sample size range from 7 camps in Kenya, 8 camps in South Sudan, 10 camps in Uganda and twenty three camps in Ethiopia. Finally, the average mean proportion of households reporting defecating in a toilet sample size range from 5 camps in South Sudan, 7 camps in Kenya, 8 camps in Uganda and twenty three camps in Ethiopia (Table 4 6).

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100 Mapping the Incidence of Watery Diarrheal among CU5 in East Afric an r efugee c amps by Country in 2016. Figure 4 1 shows a map of the locations of camps with the incidence of watery diarrhea in CU5 in East African Refugee c amps in 2016. The incidence of watery diarrhea diseases (cases per 1,000/ CU5 /month) is shown over t he camps of each hosting countries in 2016 The map of the locations of camps were divided into 5 quintiles as indicated by the size and color of the circles and the incidence of watery diarrheal (Figure 4 1). Figure 4 1 highlights the heterogeneity at the refugee host country level in watery diarrheal disease incidences across region Five panels map of the average mean and the Standard Error (SE) of the mean for the significant multivariate variables. Figure 4 2 s hows the average mean and the Standard Erro r (SE) for the multivariate model of variables that were significantly associated with the incidence of watery diarrhea Figure 4 2, shows the average mean and the SE of the mean for each variable by the hosting refugee countries In East African Refugee camps in 2016, the average mean HU rate s are 1.12 in Ethiopia 2.03 in Kenya, 2.13 in Uganda, and 2.29 in South Sudan, a nd the SE of the mean range are 0.14 in Ethiopia, 0.29 in Kenya, 0.4 in South Sudan, and 0.49 in Uganda (Figure 4 2). The average mea n pro portion of CU5 in the East African Refugee camps are 18% in Kenya, 21% in Uganda, and 22% for both Ethiopia and South Sudan The SE s of the mean range from 1% for bot h Kenya and South Sudan camps, 2% in Uganda, and 4% for Ethiopia (Figure 4 2). The average mean number of Persons of Concern per Water Tap (PCWT) vary throughout the region: 84.29 in Kenya, 99.04 in Ethiopia, 104.6 in South Sudan and

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101 605.25 in Uganda. The SE of the mean s range from 8.23 in Ethiopia to 170.09 in Uganda (Figure 4 2). Th e average mean Refugees per Latrine (RPL) in East Afri can refugee camps in 2016 are 5.71 in Kenya, 13.4 in Uganda, 15.25 in South Sudan, and 22.57 in Ethiopia The SE s of the mean range from 0.97 in Kenya to 4.5 in Ethiopia (Figure 4 2). The average mean of proportion of Households reporting Defecating in a Toilet (HDT) are all above 85% in Uganda to 100% in Kenya. The SE of the mean are 0% in Kenya, 1% in South Sudan, 2% in Ethiopia, and 3% in Uganda (Figure 4 2). Discussion Analysis of UNHCR Public Hea lth 2016 Annual Global Overview data from 47 East African r efugee c amps in 4 Countries: Ethiopia, Kenya, South Sudan, and Uganda. The study has selected ke y health indicators from UNHCR Public H ealth 2016 Annual G lobal Overview dat a from 47 East African R efugee c amps in 4 countries: Ethiopia, Kenya, South Sudan and Uganda. Most o f the refugees in East Africa co me from multiple countries of origi n (36%) (Table 4 3). In fact, the author included the mixed origin of refugees in the study as a potential risk factor because, in the refugee settings, most refugees do not have a choice on which camp they should live. As a result, the refugees are gathered together into whatever camp they are deem ed to fit according to UNHCR regulations and accessibility or conven ience of the refugees travelin g into the camp. For example, Kakuma Refugee c amp in Northern Kenya consists of refugees from South Sudan, Somalia, and Ethiopia. Imagine these refugees being congregated into this overcrowded camp, and the differences in cult ural background and health beliefs that make them prone to diarrheal, particularly with CU5 Surprisingly, the mixed

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102 origin of refugees was not significantly associated with the incidence of watery diarrhea in the univariate analyses (Table 4 4). Neither the average number of liters of potable water a vailable per person per day, nor households with drop hole latrine were found to be statistically significantly associated with the incidence of watery diarrhea (Table 4 4). In addition, camp age, proportion o f host population consultations, number of refugees per latrine, and proportion of households reporting defecating in a toilet were found to be not statistically significantly associated with the incidence of watery diarrhea (Table 4 4). Finally, in the uni variate analysis, proportion of CU5, Health Utilization (HU) rate, average number of persons of concern per water tap, and proportion of households with sufficient daily water storage capacity were significantly associated with incidence of watery diarrhea (Table 4 4). In the multivariate model, the proportion of CU5, and HU rate was significantly associated with the incidence of watery diarrhea among CU5 in East African r efug ee c amps in 2016 (Table 4 5). In the multivariate model, it was found: camp age, proportion of CU5, proportion of host population consultations, a verage number of liters of potable water available per person per day a number of p ersons of concern per water tap, proportion of h ouseholds with sufficient daily water storage capacity pro portion of h ouseholds with drop hole latrine and proportion of h ouseholds reporting defecating in a toilet not significantly associated with incidence of watery diarrheal among CU5 in East African refugee camp. I n 2016, Ugandans refugee camps had the hi ghest incidence of watery diarrhea (214 per 1,000 per month) among CU5. This is, indicated by the size and color of the

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103 circles (Figure 4 2) compared to Ethiopians, Kenyans and South Sudanese refugee camps in 20 16. In 2016, refugees in South Sudanese camps utilize d health services more (2.29) (Figure 4 2) compared to other refugee camps in East Africa. This finding might be because South Sudanese camps have the highest proportion of CU5 (22% ) compared to the proportion of CU5 in Ethiopian, Kenyan and Ugand ans camps in 2016 (Table 4 1). Also, i n 2016, all of the East African refugee camps met the UNHCR standard for the of HU rate (1 4 new visits/refugee/year) (Figure 4 2). On the other hand, when it comes to the average mean number of persons of concern per water tap in 2016, none of East African Refugee c amps met the UNHCR standard of <80 ( Figure 4 4). The average mean for some persons of concern per water tap in Ugandans refugee camps was 8 times (605.25) higher compared to the UNHCR standard of <80; thi s should raise concerns for the implementing agencies working in these refugee camps. Also in 2016, there is documentation of an influx of refugees from South Sudan and the DRC into Uganda which may have affected the services being given to the refugees a cross the camps. Regarding the average mean refugees per latrine, the refugee camps in Kenya, Uganda, and South Sudan met the UNHCR standard of <20; but refugee camps in Ethiopia fell below this standard in 2016. In addition, all of the East Africans Ref ugee camps met the UNHCR standard of >85% average mean for the proportion of households reporting defecating in a toilet in 2016.

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104 One of the limitations of conducting the cross sectional study on risk factors for incidence of diarrheal disease among refug ee CU5 is that there were not enough data points to have a robust statistical analysis. The study is based on only studied 47 East Africans Refugees camps for whom 2016 data were available. For future studies, data from 2011 2016 can be used to provide a more robust underpinning to the statistical findings here.

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105 Table 4 1 East African Refugee c amps hosting Countries reports for 2016 Country, Year Total population of refugee Proportion of children under five Country Origin of refugees Camps refugees resi ded Health Utilization Rate new/person/ year Proportion of Primary Healthcare consultations for watery diarrhea Average lit er s /person/ day Persons per communal toilets/latrin es Ethiopia, 2016 742,725 15% S. Sudanes e, Somali, Eritrean Various Tsore Kule To ngo Fugnido Kebriebeya h Sheder Bokolmany o Barahle Bambasi Sherkole Okugo Leitchuor Melkadida Awbarre Shimelba Buramino Aysaita Fugnido 2 Hitstats Adi Harush Hilaweyn Mai Aini Tierkidi Kobe 0.3 2.9 8.6% 13 26 5 56

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106 Table 4 1 Continued Country, Year Total population of refugee Proportion of children under five Country Origin of refugees Camps refugees resided Health Utilization Rate new/person/ year Proportion of Primary Healthcare consultations for watery diarrhea Average lit er s /person/ day Persons per comm unal toilets/latrines Kenya, 2016 523,498 16% Somalia S. Sudan, Ethiopia DRC Kalobeyei Hagadera Nairobi Kakuma Dagahaley Kambioos IFo Ifo2 1.5 2.9 Not Available 13 36 3.4 10.8 S.Sudan 2016 263,752 22% Sudan DRC CAR Ethiopia Parmir Ajuong Thok Kaya G orom Panrieng Bunj Hospital Gendrassa Doro Makpandu Yida Yusuf Batil Lasu Ezo 0.8 3.5 8.4% 15 21 7.6 43.1

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107 Table 4 1. Continued Country, Year Total population of refugee Proportion of children under five Country Origin of refugees Camps refugees resided Health Utilization Rate new/person/ year Proportion of Primary Healthcare consultations for watery diarrhea Average lit er s /person/ day Persons per communal toilets/latrines Uganda, 2016 828,862 20% S.Sudan DRC Somali Burundi Bidibid Adjumani Rwamwanj a Kyan gwali Kyaka II Nyakaband e Ikafe, Lobule Lawmwo Nakivale Oruchinga Kiryandong o Rhino Camp, Polorinya Kampala 0.4 5.6 5.3% 13 32 3.7 44.0

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10 8 Table 4 2. Summary of the Exposure variables extracted from East African hosting Countries reports in 2016 Name of va riable Variable type (e.g. categorical or continuous and binary Indicator at the Camp level, 2016 UNHCR Standard/definition at the camp level, 2016 Origin of Refugees Binary Created variable : 0=fixed country of origin ( i.e, South Sudan), 1= mixed country of origin (i.e., South Sudanese and Somali). Not available (N/A) Camp Age Continuous created this variable by subtracting the month and year the camp is open by 2016(i.e., January 1958 2016 = Not Available (N/A) Health Utilization rate Continuous X Nu mber given at the camp level 1 4 new visits/refugee/year Proportion of Host Population Consultations Continuous X Proportion g ave at the camp level Not Available (N/A) Average number of lit er s of potable water available per person per day Continuous X N umber is given at the camp level >20 Litres Number of persons of concern per water tap Continuous X Number is given at the camp level <80 Proportion of households collecting drinking water from protected water sources only Continuous X Proportion g ave at the camp level >95% Proportion of households with sufficient daily water storage capacity Continuous X Proportion g ave at the camp level >80% Refugees per latrine/toilet Continuous X Number given at the camp level <20

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109 Table 4 2. Continued. Name of variable Variable type (e.g. categorical or continuous and binary Indicator at the Camp level, 2016 UNHCR Standard/definition at the camp level, 2016 Proportion of households with drop hole latrine Continuous X Proportion gave at the camp level No Sta ndard provided Proportion of households reporting defecating in a toilet Continuous X Proportion gave at the camp level >85%

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110 Table 4 3 Camp c haracteristics of the Exposure v ariables in East African r efugee c amps in 2016 Independent Variables Number of observatio ns (n) mean/proportion 95% Conf. Intervals (CI) Mixed origin of Refugees 50 0.36 0.23 0.51 Camp Age 49 13.1 9.1 17.0 CU5 in the camp 47 0.21 0.17 0.26 Health Utilization rate (HU)(New Visits/refugee/year) 47 1.64 1.33 1.96 Host Population C onsultations 47 0.16 0.11 0.20 Average number of liters of potable water available per person per day 49 20.4 18.9 21.9 A n umber of persons of concern per water tap. 43 191.5 104.3 279.0 Households collecting drinking water from protected water sources only 43 0.99 0.97 0.999 Households with sufficient daily water storage capacity 43 0.62 0.53 0.70 Refugees per Latrine 48 17.0 11.9 22.1 Households with drop hole latrine 42 0.54 0.44 0.65 Households reporting defecating in a toilet 43 0.92 0.90 0.95

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111 Table 4 4 Univariate analysis for selected Demographics, Access and Utilization, Water, S anitation and Hygiene (WASH) indicators for Inci dence of watery Diarrhea among CU5 across East African r efugee c amps in 2016 Exposure v ariables Coefficient P Valu e Mixed origin of Refugees 0.0061 0.65 Camp Age. 0.0004 0.1 CU5 in the camp. 0.0735 0.01* Health Utilization(HU) rate (New Visits/refugee/year) 0.0049 0.00* Host Population Consultations. 0.0373 0.1 Average number of liters of potable water availa ble per person per day. 0.0007 0.1 A number of persons of concern per water tap. 0.0044 0.03* Households with sufficient daily water storage capacity. 00.019 0.03* Refugees per Latrine. 0.0122 0.2 Households with drop hole latrine. 0.0135 0.07 Hou seholds reporting defecating in a toilet. 0.044 0.1 Note: *p<0.05 Values shown in each cell are unstandardized coefficients

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112 Table 4 5 Multivariate Analysis of Incidence of Watery Diarrheal among CU5 across East African r efugee c amps in 2016 with respec t to Demographics, Access and Utilization, Water, Sa nitation and Hygiene (WASH) indicators Exposure v ariables Coefficient P Value Camp Age. 0.03 0.2 CU5 in the camp. 0.8 0.002* Health Utilization(HU) rate (New Visits/refugee/year) 0.6 0.03* Host Po pulation Consultations. 0.03 0.9 Average number of liters of potable water available per person per day. 0.005 0.9 A number of persons of concern per water tap. 0.002 0.2 Households with sufficient daily water storage capacity. 0.04 0.9 Households with drop hole latrine. 0.05 0.9 Households reporting defecating in a toilet. 0.1 0.6 Note: *p<0.05 Values shown in each cell are unstandardized coefficients

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113 Table 4 6 Sample size of the multivariate significant variables by hosting refugee countries Exposure v ariable Ethiopia Kenya South Sudan Uganda Mean incidence among CU5 s ample size (n) 23 7 8 9 Mean p roportion for CU5 sample size (n) 23 7 8 9 Mean HU rate sample size (n) 23 7 8 9 M ean number of persons of concern per water tap sample size (n) 23 7 5 8 Mean refugees per l atrine sample size (n) 23 7 8 10 Mean of the proportion of h ouseholds reporting defecating in a toilet sample size (n) 23 7 5 8

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114 Figure 4 1 L ocations of camps with data on the incidence of watery diarrhea (cases per 1,000/ C U5/month ) in C U5 in East African r efugee c amps in 2016

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115 Figure 4 2 The mean and the Standard Error (SE) for the multivariate model significant variables that were associated with incidence of watery diarrheal among CU5 in East African Refug ee c amps by hosting refugee countries in 2016. A is the average mean of Health Utilization (HU) rate, B is Standard Error (SE) of (HU) of the mean, C. is the average mean of proportion of Children under Five (CU5), D. is Standard Error (SE) of proportio n of CU5 of the mean, E is average mean of Person of Concerns per Water Tap (PCWT), F is Standard Error (SE) of PCWT of the mean, G is average mean of Refugees per Latrine (RPL), H is Standard Error (SE) of RPL of the mean, I is average mean of Households reporting Defecating in the Toilet (HDT, and J is Standard Error (SE) of HDT of the mean

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116 CHAPTER 5 DISCUSSION AND IMPLICATIONS OF RESEARCH FINDINGS Discussion The aims of this study have been to increase understanding, specifically risk factors, for dia rrheal disease in an understudied population: refugee children under the age of 5 In Chapter 2, systematic review of the literature found that lack of clean water; inadequate sanitation and lack of cleanness at the camp's level were the main drivers of a diarrheal disease among CU5 in the refugee camps. Furthermore, it found that much of this diarrheal disease came from outbreaks. Refugee camps are run by UNHCR, and UNHCR often relies on the prominent supporters such as actress es (i.e., Angelina Jolie), g oodwill ambassadors (i.e., Modeler Alex Wek from South Sudan), and high profile supporters (i.e., actor Ben Stiller). When resources are limited (dry up), and UNHCR is unable to provide clean water, adequate sanitation, and hygiene, the incidences of diarr heal disease increase among CU5. As a result, CU5 is most like ly to die from the diarrheal disease, despite being a relatively easy disease to cure with modern technology. Since resources are constrained at the camp level, implementing agencies such as IRC Doctors Without B orders, and Care International who work at the camp level should focus on the provision of sufficient clean water This may include the need to collaborate and /or share resources including information about WASH conditions Having identi fied the seemingly self evident risk factors for diar rheal disease in refugee camps, those being risk factors relate d hygiene and sanitation conditions, the outcome of the systematic review of literature in Chapter 2 was

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117 used to examine the primary risk fa ctors for diarrheal disease among CU5 in East African refugee camps in subsequent analysis T he analysis of the UNHCR HIS morbidity and mortality data, this research found a much higher incidence of watery diarrhea among CU5 compared to incidence of bloody diarrheal from 2006 2016 This finding is not unexpected, given that watery diar rhea is much more prevalent than bloody diarrhea in the general population, however, the findings underscore a need for decision makers and program implementing partners withi n refugee camps to put additional effort into prevention and management of watery diarrhea If these agencies were able to invest additional resources into molecular testing to further define the cases of watery diarrhea and bloody provided additional reco mme ndations might be evident. For example it has been documented in literature that CU5 are susceptible to diarrheal pathogens such as: viral agents ( Rotavirus, Adenovirus, Norovirus ), protozoa agents ( Giardia lamblia, Entamoeba Histolytica, Cryptosporidiu m parvum ), bacterial agents ( Enteroaggregative Escherichia coli, Shiga toxigenic Escherichia coli, Enteropathogenic Escherichia coli,Enterotoxigenic Escherichia coli, Shigella, Salmonella ), and soil transmitted helminthes ( Ascaris lumbricoides, trichuris t richiura, ancylostoma duodenale, necator Americans ). In refugee camps, robust data about incidence and prevalence of pathogen specific among CU5 are lacking. Establishing laboratory to examine the etiology of diarrheal pathogen spec ific among CU5 in refug ee camps would dramatically increase our understanding of the current situation In addition, given that the incidence of watery of diarrheal was found to be prevalent among newly established camps

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118 from 2006 2016, a pilot study on diarrheal disease among C U5 in East African refugee camps that are established from 2017 on forward would contribute additional understanding to the vulnerability certain populations. Final elements of increased understanding came from the multivariate analysis conducted in Chapte r 4. That analysis indicated that camps with a greater proportion of CU5 are positively associated with increased incidence of diarrheal disease. Given that, according to UNHCR 51% of refugees worldwide are children under the age of 18 years old, it is imp ortant to recognize that camps with high rates of young children are increasing at risk for diarrheal disease among those children. Importantly, however, this multivariate regression also indicates that the more CU5 utilize health services at the camp leve l, the lower the incidence of watery diarrhea. These findings serve to reinforce the message that although increased proportions of children within camps may increase the monthly incidence rate, this risk may be offset by utilization of health facilities b y CU5, Thus agencies may be interested in investigating factors that facilitate or inhibit health seeking behaviors within the camps. Outside Information about the author lived experienced ay offer additional insight in to interpretation of findings. At the age of six, the authored travelled over 2,000 miles to escape a brutal civil war in South Sudan that claimed his family, the journey ending in an overcrowded Kenyan refugee camp. From the disease among CU5 is the conflict that displaces these children into neighboring countries. Once the conflict or war breaks out in the country of origin, these

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119 children are forced to flee either with parents or with a caregiver, in the case of children being separated from their families, which is common within war zones Among the numerous difficulties that children living in refugee camps must face, many of these children arrive in poor h ealth condition malnourished and psychologically traumatized making them increasingly vulnerable to diarrheal disease and continued nutritional complexities once, they are in the camp. In the refugee camps, there is minimal variety in the diet due to the food ration constraints. In the normal camp, the food is distributed according to the number of the pe ople at the household at level. For example, if a household has five children, these children are given a ration of lentil, wheat flower, potatoes etc In UNHCR food ration, meat is not distributed, leaving CU5 with insufficient daily dietary intake In developed countries, diarrheal disease is not an enormous problem compared to refugee camps, and CU5 should not be dying of communicable disease such as diarrheal when we know there are protective factors we can deploy against this disease. It is time for the developed and developing nations to work together to mitigate the risk of diarrheal disease among CU5 in the refugee camps. What is missing in HIS datasets There were definitely constraints to this research given the nature of the UNHCR HIS data set. UNHCR and its partners have been collecting the HIS data since 2006, but data are collec ted at the camp level by month. The ability to understand the he alth situation of children within the camps would be dramatically improved if the data were collected at the individual level. Collecting diarrheal morbidity and mortality data among CU5 in the refugee camps at the

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120 household level would significantly incre ase the ability for researchers to engage the data in scholarly publications, thus increasing research and understanding of the understudied subject of refugee health. Individual level data though costly will provide essential information to form a robust data set, providing meaningful information to improve child hea lth outcomes through the camps. Recommendations for Future Research The H IS data has some limitations as described in Chapter 3. For the future studies, the author recommends seeking the quali tative approach to address the gaps in HIS Data. Also, this qualitative approach should be conducted among camps with a higher prevalence of incidence watery diarrheal in CU5. This research should examine the etiology of diarrheal pathogen specific among C U5 in East African refugee camps, as justified by the gap in knowledge identified in the HI S Data. This research will be significant because no such epidemiological study, to the knowledge of the researcher has been conducted among CU5 in East African refu gee camps. The following research aims should be explored for further studies: Describe the etiology of enteric infections associated with diarrheal disease in CU5 in East African refugee camps. Test the relationship between risk factors operating at mult iple levels (e.g., individual, household, and community levels) and enteric infections in CU5 in East African refugee camps. Compare etiologies of enteric infections among groups, particularly by country of origin (nationality), among CU5 in East African r efugee camps. Determine the cost of treating diarrhea, and how this may impact the financial and social well being of the household among CU5 in East African refugee camps.

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121 Determine whether the cost of treating previous diarrheal episodes affect future h ealthcare treatment for subsequent diarrheal episodes or other illnesses among CU5 in East African refugee camps. Determine the spatiotemporal dynamics of diarrheal occurrence, severity (blood in stool), mortality and morbidity, and determine what ecologi cal (climate, temperature), demographic (influx of new refugees), or social (cultural practices, WASH behavior) risk factors are associated with these patterns among CU5 in East African refugee camps. Having reviewed the findings of each chapter and recom mendations for future research the researcher now turned to those broader implications of the research. Who can benefits from this research findings Characterization of risk factors, morbidity, and mortality associated with CU5 across East African refuge e camps should be of interests research to the UNHCR and its implementing agencies with potential for drawing operational conclusions and formulating programmatic recommendations. There are numerous potential stakeholders and decision makers who may utiliz e findings from this study. A description of stakeholders is provided below at various levels: 1. Individual and Community level a characterization of risk factors, morbidity, and mortality associated with diarrheal disease will provide physicians or health care providers at health facilities in refugee camps the information necessary to effectively manage cases. This will improve the health outcome of individuals (both the CU5 and others) protect communities from potential diarrheal outbreaks by targeting ef fective treatments of case and prevention strategies throughout refugee camps in East African refugee host countries. 2. Health partner and UN agency levels improved information regarding risk factors, morbidity, and mortality associated with CU5 in the East Africans Refugee camps will help planners and managers more effectively allocate limit resources toward effective prevention and treatment efforts. 3. UNHCR (Headquarters) level an improved understanding of the risk factors, morbidity, and mortality associa ted with CU5 in East African Refugee camps will allow donors and the Ministries of Health (MOH) to

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122 develop more effective strategic policy, advocacy, and resource mobilization efforts for improved health outcomes. Our findings of diarrheal disease among C U5 living in refugee camps may provide insights into risk factors for diarrheal disease among the entire East African r efugee camps or community. This study helps us to have a better understanding about the burden of diarrheal disease in CU5 years old, whi ch may be applicable in refugee camps across other parts of the world.

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123 APPENDIX A CHECKLIST OF ITEMS TO INCLUDE WHEN REPORTING A SYSTEMATIC REVIE W

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124 Table A 1 Checklist of items to include when reporting a systematic review Section/topic # Checkl ist Item Reported on page # TITLE Title 1 Identify the report as a systematic review, meta analysis, or both. ABSTRACT Structured summary 2 Provide a structured summary including, as applicable: background; objectives; data sources; study eligib ility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number. INTRODUCTION Rationale 3 Describe the rationale for the review in the context of what is already known. Objectives 4 Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS). METHODS Protocol and registra tion 5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number. Eligibility criteria 6 Specify study characteristics (e.g., PICOS, length of follow up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale. Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact w ith study authors to identify additional studies) in the search and date last searched. Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated Study selection 9 State the pr ocess for selecting studies (i.e., screening, eligibility, included in the systematic review, and, if applicable, included in the meta analysis). Data collection process 10 Describe the method of data extraction from reports (e.g., piloted forms, indepe ndently, in duplicate) and any processes for obtaining and confirming data from investigators.

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125 Table A 1. Continued Section/topic # Checklist Item Reported on page # Data items 11 List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made. Risk of bias in individual studies 12 Describe methods used for assessing the risk of bias of individual studies (including specification of whether this was done at the study or outcome leve l), and how this information is to be used in any data synthesis. Summary measures 13 State the principal summary measures (e.g., risk ratio, the difference in means). Synthesis of results 14 Describe the methods of handling data and combining result s of studies, if done, including measures of consistency (e.g., I 2 ) for each meta analysis. Risk of bias across studies 15 Specify any assessment of the risk of bias that may affect the cumulative evidence (e.g., publication bias, selective reporting wit hin studies). Additional analyses 16 Describe methods of additional analyses (e.g., sensitivity or subgroup analyses, meta regression), if done, indicating which were pre specified. RESULTS Study selection 17 Give numbers of studies screened, asses sed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally with a flow diagram. Study characteristics 18 For each study, present characteristics for which data were extracted (e.g., study size, PICOS, follow up p eriod) and provide the citations. Risk of bias within studies 19 Present data on the risk of bias of each study and, if available, any outcome level assessment (see item 12). Results of individual studies 20 For all outcomes considered (benefits or har ms), present, for each study: (a) simple summary data for each intervention group (b) effect estimates and confidence intervals, ideally with a forest plot. Synthesis of results 21 Present results of each meta analysis done, including confidence interval s and measures of consistency. Risk of bias across studies 22 Present results of any assessment of the risk of bias across studies (see Item 15). Additional analysis 23 Give results of additional analyses, if done (e.g., sensitivity or subgroup analy ses, meta regression [see Item 16]).

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126 Table A 1. Continued Section/topic # Checklist Item Reported on page # DISCUSSION Summary of evidence 24 Summarize the main findings including the strength of evidence for each main outcome; consider their relev ance to key groups (e.g., healthcare providers, users, and policymakers ). Limitations 25 Discuss limitations at study and outcome level (e.g., the risk of bias), and at review level (e.g., incomplete retrieval of identified research, reporting bias). C onclusions 26 Provide a general interpretation of the results in the context of other evidence and implications for future research. FUNDING Funding 27 Describe sources of funding for the systematic review and other support (e.g., the supply of data) ; the role of funders for the systematic review.

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127 APPENDIX B FULL DETAILS OF THE SEARCH STRATEGIES FOR SYSTEMATIC REVIEW Research Question What are the existing risk factors and etiology of diarrheal disease in the refugee camps or Internally Displa ced Camps? Inclusion Criteria Publication types : scholarly peer reviewed (where possible) journal articles Article types: (clinical trials, meta analyses, systematic reviews, observational studies??? OR all types, since this is such a narrowly focused stud y (yay!) but that may not have a lot published on it) Language : full text in English language only. Publication date : Past 20 years 1996 to 2016. The p opulation studied : Residents that live in the Refugee or Internal Displaced Camps. Has to be humans spec ies (EXAMPLE: Journals, conference proceedings, workshops, dissertations/thesis, reports, commentaries, and case studies English language only Past 10 years (2004 2014) Populations studied Must be (age, gender, race, ethnic background socioeconomic st atus, __________ name of health phenomenon) must occur in or around___(geographic area) Exclusion Criteria: Publication types : personal communications, popular press articles, editorials, letters, comments. Languages : Full text in language ot her than English Publication dates : Before 1996 and 2016 Populations studied: nonresident that does not live in the Refugee or Internal Displaced Camps.

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128 Languages other than English Before 2004 or after 2014 Populations studied are from North America, Eur ope, Japan, Australia, or New Zealand Research on ___________________________________ _________________ from outside factors not related to (location in last item of Inclusion criteria this from an infectious disease search, so may not apply to your search ) Term Harvesting PubMed database 1 Concept Risk factors Etiology Diarrheal diseases Refugee place MeSH Subject Terms (non major) "Risk Factors"[MeSH] OR "Sanitation"[Mes h] OR "Maternal Child Health Services"[Mesh] OR "Child Health Services"[Mesh] OR "Co mmunity Health Services"[Mesh] OR "Health Services Accessibility"[Me sh] OR "Breast Feeding"[Mesh] OR "Malnutrition"[Me sh] OR "Toilet Facilities"[Mesh] OR "Nutritional Status"[Mesh] "Etiology"[Subheadi ng] OR "Causality"[MeSH Terms] OR "Cholera"[Mesh] OR Shigella"[Mesh] OR "Rotavirus"[Mesh] OR "Norwalk virus"[Mesh] OR "Salmonella"[Mesh] OR "Enterotoxigenic Escherichia coli"[Mesh] OR "Gastroenteritis"[Me sh] "diarrhea"[MeS H Terms] OR "dysentery"[Me SH Terms] OR "Cholera"[Mesh ] ("Refugees"[Me SH Terms] AND cam p*) Keywor ds OR malnutrition OR sanitation OR latrine* OR etiology OR etiologic OR etiolog OR aetiolog OR cause OR causes OR causality OR d iarrhea* OR diarrhea* OR dysentery OR cholera "refugee camp" OR "refugee camps" OR "displaced persons camp" OR "displaced

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129 Concept Risk factors Etiology Diarrheal diseases Refugee place c breast feeding shigella OR OR rotavirus OR rotavituses OR salmonella OR Escherichia coli" OR OR gastroenteritis OR cholera persons camps" OR ((refugee* "displaced people" OR "displaced population" OR "displaced populations" OR d AND (camp OR Concept 1: risk factor or risk factors, causality, Causalities Concept 2: etiology, aetiology Concept 3: diarrhea, diarrhoea dysentery,

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130 Concept 4: Refugee, Re fugees, asylum seeker, asylum seekers, displaced person displaced persona, displaced people and stateless person, stateless persons Pull all my search terms for e ach concept together Concept 1: ((("risk factor"[MeSH Terms] OR "Risk Factors"[MeSH Terms OR "causality"[MeSH Terms] OR Risk factor OR Risk factor* OR causality OR Causalit*) Concept 2 ("diarrh Concept 3 : And ("refugees"[MeSH Terms] OR "emigrants and immigrants"[MeSH Concept 4 Term Harvesting Database 2 (heading applies to Web of Science aka WOS) Concept Concept 1 Concept 2 Concept 3 Concept 4 Keywords WOS Categories (disciplines) used to limit/refin e search Term Harvesting Database CABI 3 Concept Concept 1 Concept 2 Concept 3 Concept 4 CABICODEs Key Words Database Name: PubMed PubMed (44 articles) Medici ne, nursing, dentistry, veterinary medicine, the preclinical sciences, nutrition, delivery of health care, pharmacology, environmental health, pathology, toxicology, biochemistry, genetics, molecular biology, and psychiatry. Date search conducted: May 24, 2016 Search string We conducted several searches but here is the final search string for PubMed (44 articles) that we settle with: (("Risk Factors"[MeSH] OR "Sanitation"[Mesh] OR "Maternal Child Health Services"[Mesh] OR "Child Health Services"[Mesh] OR "Community Health Services"[Mesh] OR "Health Services Accessibility"[Mesh] OR

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131 "Breast Feeding"[Mesh] OR "Malnutrition"[Mesh] OR "Toilet Facilities"[Mesh] OR "Nutritional Status"[Mesh] OR "risk factor" OR "risk factors" OR "nutrition status" OR "nutritional status" OR "malnutrition" OR "sanitation" OR "latrine*" OR "community toilet" OR "community toilets" OR toilet* OR "food insecurity" OR "access to health service" OR "access to health services" OR "access to a health clinic" OR "access to health clinics" OR "health service utilization" OR "health services utilization" OR "utilization of health services" OR "use of a health service" OR "use of health services" OR "health service use" OR "health service uses" OR "health services use" OR "health services uses OR "oral hydration" OR "breast feeding" OR "Etiology"[Subheading] OR "Causality"[MeSH Terms] OR "Cholera"[Mesh] OR "Shigella"[Mesh] OR "Rotavirus"[Mesh] OR "Norwalk virus"[Mesh] OR "Salmonella"[Mesh] OR "Enterotoxigenic Escherichia coli"[Mesh] OR "Gastro enteritis"[Mesh] OR "etiology" OR "etiologic" OR "aetiology" OR "aetiologic" OR "cause" OR "causes" OR "causality" OR "shigella" OR "Norwalk virus*" OR "rotavirus" OR "rotaviruses" OR "salmonella" OR "Enterotoxigenic Escherichia coli" OR "Enterotoxigenic E coli" OR "E. coli" OR "ETEC" OR "gastroenteritis" OR "cholera")) AND ((("diarrhea"[MeSH Terms] OR "dysentery"[MeSH Terms] OR "diarrhea" OR "diarrhoea" OR "diarrheal" OR "diarrhoeal" OR "dysentery" OR "bloody stool" OR "bloody stools" OR "watery stool" OR "watery stools" OR "loose stool" OR "loose stools")) AND ("refugee camp" OR "refugee camps" OR "displaced persons camp" OR "displaced persons camps" OR "internally displaced people camp" OR "internally displaced people camps" OR "IDP camp" OR "IDP camps" OR "Refugees"[MeSH Terms] OR "refugee*" OR "asylum seeker" OR "asylum seekers" OR "displaced person" OR "displaced persons" OR "displaced people" OR "displaced population" OR "displaced populations" OR "stateless person" OR "stateless persons" OR "stateles s people" OR "internally displaced" OR "conflict displaced" OR "forcibly displaced" OR "internally displaced")) AND (camp[tiab] OR camps[tiab]) AND (("1996/01/01"[PDat] : "2016/12/31"[PDat]) AND Humans[Mesh]). Filters activated We searched article publish ed in the last 20 years from 1996 to 2016, humans, English. Results (#) 44 articles were found Database name: Web of Science (WOS) (50 articles) Web of Science consists of 3 databases (in sciences, social sci ences, and arts & humanities) that cover journals or primary literature. They are: the sciences, social sciences, and arts & humanities. Date search conducted May 24, 2016 Search string:

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132 TOPIC: ("maternal child health service*" OR "child health service* OR "community health service*" OR "health services accessibilit *" OR "etiology" OR "etiologic" OR "aetiology" OR "aetiologic" OR "cause*" OR "causality" OR "shigella" OR "Norwalk virus" OR "Norwalk viruses" OR "rotavirus" OR "rotaviruses" OR "salmonella" OR "Enterotoxigenic Escherichia coli" OR "Enterotoxigenic E. coli" OR "ETEC" OR "gastroenteritis" OR "cholera" OR "health services utilization" OR "health service utilization" OR "utilization of health services" OR "use of health service" OR use of heal th services" OR "health service uses" OR "health services use" OR "health services uses" OR "oral hydration" OR breast feeding OR "risk factor*" OR "malnutrition*" OR "latrine*" OR "community toilet*" OR "toilet*" OR "sanitation" OR "shared toilet*" OR n utritional status OR "nutrition status*" OR "toilet facilit *" OR "stunting" OR "wasting" OR "food insecurity" OR "access to health service" OR "access to health services" OR "access to a health clinic" OR "access to health clinics") AND TOPIC: ("diarrhea" OR "diarrhoea" OR "diarrheal" OR "diarrhoeal" OR "dysentery" OR "bloody stool*" OR "watery stool*" OR "loose stool*" OR "gastroenteritis") AND TOPIC: ("refugee camp" OR "refugee camps" OR "displaced persons camp" OR "displaced persons camps" OR "internally displaced people camp" OR "internally displaced people camps" OR "IDP camp" OR "IDP camps" OR "asylum seeker" OR "asylum seekers" OR "displaced person" OR "displaced persons" OR "displaced people" OR "displaced population" OR "displaced populations" OR "s tateless person" OR "stateless persons" OR "stateless people" OR "internally displaced" OR "conflict displaced" OR "forcibly displaced" OR "internally displaced"). Filters activated: We searched article published in the last 20 years from 1996 to 2016, hu mans, English. Results (#) 50 articles were found Database name: CABI (31 articles) CAB : Keep track of every area of agricultural science, veterinary medicine, nutrition and natural resources. Date search co nducted: March 17, 2016. Search string: ("maternal child health service*" OR "child health service*" OR "community health service*" OR "health services accessibilit *" OR "etiology" OR "etiologic" OR "aetiology" OR "aetiologic" OR "cause*" OR "causality" OR "shigella" OR "Norwalk virus" OR "Norwalk viruses" OR "rotavirus" OR "rotaviruses" OR "salmonella" OR "Enterotoxigenic Escherichia coli" OR "Enterotoxigenic E. coli" OR "ETEC" OR

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133 "gastroenteritis" OR "cholera" OR "health services utilization" OR "healt h service utilization" OR "utilization of health services" OR "use of health service" OR use of health services" OR "health service uses" OR "health services use" OR "health services uses" OR "oral hydration" OR breast feeding OR "risk factor*" OR "mal nutrition*" OR "latrine*" OR "community toilet*" OR "toilet*" OR "sanitation" OR "shared toilet*" OR nutritional status OR "nutrition status*" OR "toilet facilit *" OR "stunting" OR "wasting" OR "food insecurity" OR "access to health service" OR "access to health services" OR "access to a health clinic" OR "access to health clinics") AND ("diarrhea" OR "diarrhoea" OR "diarrheal" OR "diarrhoeal" OR "dysentery" OR "bloody stool*" OR "watery stool*" OR "loose stool*" OR "gastroenteritis") AND ("refugee camp" OR "refugee camps" OR "displaced persons camp" OR "displaced persons camps" OR "internally displaced people camp" OR "internally displaced people camps" OR "IDP camp" OR "IDP camps" OR "asylum seeker" OR "asylum seekers" OR "displaced person" OR "displaced persons" OR "displaced people" OR "displaced population" OR "displaced populations" OR "stateless person" OR "stateless persons" OR "stateless people" OR "internally displaced" OR "conflict displaced" OR "forcibly displaced" OR "internally displaced"). Ti mespan : 1996 2016. Indexes : CAB Abstracts. Filters activated: 20 years from 1996 to 2016, humans, English Results #: 31 articles Summarize of my detailed search strategy into 1 2 sentences for the Methods section within the paper, see below: Subject he adings and truncated, phrase searched keywords for risk factors, etiology, diarrheal diseases and refugee place were searched in 3 major and widely used databases, PubMed, Web of Science (WOS) and CABI. Results were combined and limited to English language full text, humans and publications within the last 20 years (1996 to 2016). Total # of results (all databases): 125 articles # Removed a s exact duplicates: 124 Minus 85= 39 articles

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134 Total # abstracts reviewed: 85 articles # Excluded for other reasons: 71 articles see below: 1. Language that is not English: article by Heraut, L. A: [Miranda de Ebro: Medical condition of the concentration camp in the autumn of 1943], it was in French. 2. Language that is not English: article by Ivanoff and Chaignat (2002) title 3. Book section by WHO title: Communicable disease epidemiological profile: Cote d'Ivoire 2010. 4. Systematic Review: Heijnen, M et al, article title: Shared Sanitation Versus Individual Household Latrines: A systematic Review of Health Outcomes 5. A systematic Review article by De Buck, E. et al (2015) title: A Systematic Review of the Amount of Water per Person per Day Needed to Prevent Morbidity and Mortality in (Post 6. This article only talks about Mnigococcal meningitis and not mentioning anything about risk factors or the etiology of diarrheal disease at all. So we excluded this article by Heyman et al (1998) title Meningococcal meningitis among Rwandan refugees: diagnosis, manage 7. Review Article: title Infectious diseases of severe weather related and flood related natural Ivers et al, 2006. 8. Language that is not English: article by with was in dutch. 9. Systematic review article by Effectiveness of Water, Sanitation, and Hygiene (WASH) Interventions on Health Outc 10. Full text not only, the Prehospital and Disaster Medicine want me to buy the al, 1998. 11. Language that is not English: article by Berner, W, 2008, title History of the control of acute infectious diseases in Poland after the World War I until the year 12. This article by does not talk about the risk factors or the etiology of diarrheal disease in children in the refugee settings, so we excluded.

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135 13. Article by Chiabi, A et gn for children in catastrophic situations: the case of a Central African refugee camp at Gado Badzere 14. Article by Cronin, A. A et al (2008), title provision in refugee camps in association with selected health and nutrition indicators -is a review, so we will the article excluded from the study. 15. Full text not online for this article Emergence of vector borne disease s during 16. Excluded because it is a review article tittle Verocytotoxic diarrhogenic bacteria and food and water contamination in developing countries: a challenge to the et al, 2010. 17. Full text not online for this article Fox and Kumchum 1996. 18 Kavitha et al was excluded because it is irreleva nt to our research questions and it is a short report. 19. This article Infectious disease outbreaks in centralized homes for asylum seekers in Germany from 2004 it was not in English language, it is in G erman. 20. This article 2009 was excluded because it is a review. 21. This book section by Lionetti et al, title Coeliac disease in Saharawi children in because no f ull text online and it is a book section. 22. This article Disaggregation of health and nutrition indicators by age and gender why it is excluded. 23 This article R otavirus associated diarrhoea in children in a refugee camp in the article. 24. This article Morbidity and mortality amongst southern Sudanese in Koboko refugee camps, Aru 1999 does not have a full text online.

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136 25. This article Control of infectious diseases in refugee and displaced populations 1998 is a review and this is why it is excluded. 26. T his article A single dose of live oral cholera vaccine CVD 103 HgR is safe and immunogenic in HIV infected and HIV 1998 is irrelevant to our research question of Risk Factors and etiology of diarrhea disease in the refugee camp. 27. This article Sanitation and physical disability: challenges to latrine access in was excluded. Article to keep are in green background: Red=articles th at might be excluded and see below because, about risk factors or the etiology of diarrheal disease: 28. Malnutrition and micronutrient deficiencies among Bhutanese refugee children -Nepal, 2007 29. Ali, S. et al, 2015: Effectivene ss of emergency water treatment practices in refugee camps in South Sudan. 30. Biran et al, 2012: Hygiene and sanitation practices amongst residents of three long term refugee camps in Thailand, Ethiopia and Kenya. 31. Butler et al, 2013: Point of use wat er treatment with forward osmosis for emergency relief. 32. Chen et al: Hypovolemic shock and metabolic acidosis in a refugee secondary to O1 serotype Vibrio cholerae enteritis. 33. Connolly M.A et al: Communicable diseases in complex emergencies: impact and challenges, excluded because it is a review. 34.Cronin, A.A.: Quantifying the burden of disease associated with inadequate provision of water and sanitation in selected sub Saharan refugee camps, it is a review, good for introduction 35. Crooks A.t. and Hailegiorgis, A.B, 2014: An agent based modeling approach applied to the spread of cholera 36. Farmer et al: Meeting Cholera's Challenge to Haiti and the World: A Joint Statement on Cholera Prevention and Care. 37. Hassan et al 1997: Factors associate d with anemia in refugee children because, it only talks about anemia

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137 38. Husain et al 2015: A pilot study of a portable hand washing station for recently displaced refugees during an acute emergency in Benishangul Gumuz Regional State, Ethiopia, this arti cle only talks about soap but no mentioned of known risk factors or etiology of Diarrheal disease in the refugee camps. 39. Jee Hyun et al 2012: Program experience with micronutrient powders and current evidence, this was excluded because it does not addr ess the research question. 40. Kalluri, P et al 2006: Evaluation of three rapid diagnostic tests for cholera: does contain the research question being ask 41. Kiulia N. M et al 2014: Norovirus GII.17 Predominates in Selected Surface Water Sources in Kenya. This article is excluded because it does not answer the research question. 42. Lim, J. H et al 2005: Medical needs of tsunami disaster refugee camps, this article was excluded because it only talks about medical needs assessment but does not address the research question. 43. Magloire, R et al 2010: Rapid establishment of an internally displaced persons disease surveillance system after an earthquake Haiti, 2010 it is just about surveillance and does not mentioned risk factors or etiology of diarrheal disease. 44. Moss, W. J et al 2006: Child health in complex emergencies, this article was 45. Noji, E. K 2006 ABC of conflict and disaster Public health in the aftermath of disasters, this article was excluded because it does not answer the research question; risk factors and etiology of diarrheal disease in the refugee camps. 46. Palacio, H et al: Norovirus outbreak among evacuees from Hurricane Katrina fit into IDPs or Refugee camps but, it is good for discussions section. 47. Qayum, M et al 2011: Bathing and cleaning practices in the camp of Jalozai Pakistan, for internally displaced people, based on Sphere Standards and Indicators, this article was excluded because it does not answer the research question. 48. Rosewell, A et al 2013: Concurrent Outbreak s of Cholera and Peripheral Neuropathy Associated with High Mortality among Persons Internally Displaced by a Volcanic Eruption, this article is excluded because it does not answer the research question.

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138 49. Saeed, I. E and Ahmed, E. S 2003: Determinants of malaria mortality among displaced people in Khartoum state, Sudan, this article is excluded because it does not address the research question. 50. Salama, P et al 2004: Lessons learned from complex emergencies over past decade, this article was exclude d because it is a literature review. 51. Sami, L 2011: Starvation, Disease and Death: Explaining Famine Mortality in Madras 1876 1878, this article was excluded because it does not answer the research question. 52. Sugunan, A. P et al Outbreak of rotavir al diarrhoea in a relief camp for tsunami victims at Car Nicobar Island, India, this article is excluded because it was a short 53.Todd et al 2007: Outbreaks where food workers have been implicated in th e spread of foodborne disease. Part 2. Description of outbreaks by size, severity, and settings, this article was excluded because it is a literature review. 54. Toole, M. J and Waldman, R. J 1997: The public health aspects of complex emergencies and ref ugee situations, this article is excluded because it does not answer the research question. 55. Walden, V. M et al 2005 Container contamination as a possible source of a diarrhoea outbreak in Abou Shouk camp, Darfur province, Sudan, this article is exclud 56. An article published by WHO: Epidemic prone disease surveillance and response after the tsunami in Aceh Province, Indonesia in 2005 was excluded from esearch question (risk factors and etiology). 57.An article by Chaicumpa, W. et al 1998: Rapid diagnosis of cholera caused by Vibrio cholerae O139 was excluded because it does not address the research question. 58. An article by Dalahmeh, S. and Assayed A 2008: : Health risk assessment of children exposed to greywater in Jerash refugee camp in Jordan) was excluded because it does not address the research question. 59. An article by Davis, A. P: Targeting the vulnerable in emergency situations: who is vulnerable? 1996 was excluded because it does not answer the research question.

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139 60. An article Degomme, O. and Guha Sapir, D: Patterns of mortality rates in Darfur conflict 2010 was excluded because it does not answer the research questions. 61. Article by Elsanousi, S et al A study of the use and impacts of LifeStraw in a settlement camp in southern Gezira, Sudan was excluded because it does not address the research question. 62. Article by Fredrick, T et al 2015: Cholera Outbreak Linked with Lack of S afe Water Supply Following a Tropical Cyclone in Pondicherry, India, 2012 was excluded because it does not address the research question, hint (Tropical Cyclone). 63. Article by Grandesso, F et al 2005: Mortality and malnutrition among populations living i n South Darfur, Sudan: results of 3 surveys, September 2004 was excluded because does not address the research question, hint mortality and malnutrition. 64. Article by Grandesso, F et al 2014: Risk factors for cholera transmission in Haiti during inter peak periods: insights to improve current control strategies from two case control studies was excluded because it does not address the research question, hint (Earthquake in Haiti). 65. Article by Grein, T et al 2003: Mortality among displaced former UNIT A members and their families in Angola: a retrospective cluster survey was excluded because it does not address the research question, hint (this article talk about mortality). 66.Article by 2009: Malnutrition and Mortality Patterns among Internally Displ aced and Non Displaced Population Living in a Camp, a Village or a Town in Eastern Chad was excluded because it does not address the research questions, hint ( Malnutrtional and Mortality). 67. Article by Gupta, S. K et al 2007: Factors associated with E c oli contamination of household drinking water among tsunami and earthquake survivors, Indonesia was excluded because it does not address the research question, hint (tsunami and earthquake). 68. Article by Jayatissa, R et al 2006 Assessment of nutritional status of children under five years of age, pregnant women, and lactating women living in relief camps after the tsunami in Sri Lanka was excluded because it does not address the research question, hint (tsunami). 69 Article by Pinto, A et al 2005: Setti ng up an early warning system for epidemic prone diseases in Darfur: a participative approach was excluded because it does not address the research question, hint (i.e early warning system). 70 Article Polonsky, J. A et al 2013: High levels of mortality, malnutrition, and measles, among recently displaced Somali refugees in Dagahaley camp, Dadaab

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140 refugee camp complex, Kenya, 2011 was excluded because it does not answer the research question, hint (mortality, malnutrition and Measles). 71. Article by Spieg el, P et al et al 2002: Health programmes and policies associated with decreased mortality in displaced people in postemergency phase camps: a retrospective study was excluded because it does not address the research question, hint(i.e., programmes policie s and mortality). 72. Benny, E. et al 2014: A large outbreak of shigellosis commencing in an internally displaced population, Papua New Guinea, 2013. This article is duplicate this wa s discover during the screening and identification process. Article to keep are: 1. Abu Elamreen et al, 2008: Isolation and antibiotic susceptibility of Salmonella and Shigella strains isolated from children in Gaza, Palestine from 1999 to 2006. 2. Abu Mo urad, T. A, 2004: Palestinian refugee conditions associated with intestinal parasites and diarrhoea: Nuseirat refugee camp as a case study. 3. Abu Alrub, S. M. et al, 2014: A large outbreak of shigellosis commencing in an internally displaced population, P apua New Guinea, 2013. 4 Doocy, S and Burnham, 2006: Point of use water treatment and diarrhoea reduction in the emergency context: an effectiveness trial in Liberia. 5 Hershey et al 2011: Incidence and risk factors for malaria, pneumonia and diarrhea in children under 5 in UNHCR refugee camps: a retrospective study. 6 Issa et et al:2015: Access to safe water and personal hygiene practices in the Kulandia Refugee Camp (Jerusalem). 7 Kerneis, S et al 2009: A Look Back at an Ongoing Problem: Shigella dys enteriae Type 1 Epidemics in Refugee Settings in Central Africa (1993 1995). 8 Mahamud, A. S et al 2012: Epidemic cholera in Kakuma Refugee Camp, Kenya, 2009: the importance of sanitation and soap. 9 .Mohamed, A. H et al 2014: Health care utilization for a cute illnesses in an urban setting with a refugee population in Nairobi, Kenya: a cross sectional survey. 10 Peterson et al 1998 The effect of soap distribution on diarrhoea: Nyamithuthu Refugee Camp.

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141 11 .Roberts et al 2001: Keeping clean water clean in a Malawi refugee camp: a randomized intervention trial. 12 Shultz A. et al:2009: Cholera Outbreak in Kenyan Refugee Camp: Risk Factors for Illness and Importance of Sanitation 13 Swerdlow D. L et a : Epidemic cholera among refugees in Malawi, Africa: treat ment and transmission

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146 53. Salama, P., et al., Lessons learned from complex emergencies over past decade. The Lancet, 2004. 364 (9447): p. 1801 1813. 54. Spiegel, P., et al., Health programmes and policies associat ed with decreased mortality in displaced people in postemergency phase camps: a retrospective study. The Lancet, 2002. 360 (9349): p. 1927 1934. 55. Shrestha, D. and A. Cronin, The right to water and protecting refugees. waterlines, 2006. 24 (3): p. 12 14. 5 6. Tomczyk, B., et al., Emergency nutrition and mortality surveys conducted among Sudanese refugees and Chadian villagers, northeast Chad, June 2004. Atlanta: US Centers for Disease Control. http://www cdc. gov/globalhealth/gdde r/ierh/ResearchandSurvey/Chad_report04. pdf (accessed 25 July 2012), 2004. 57. Goals, S.D. Goal 3: Good Health and Well Being 2017 [cited 2017 9 28 2017]; Available from: http://www.undp.org/content/undp/en/home/sustainable development goals/goal 3 good health and well being.html 58. Programme, U.N.D. Goal 6: Clean Water and Sanitation 2017 [cited 2017 9 28 2017]; Available from: http://www.undp.org/content/undp/en/home/sustainable development goals/goal 6 clean water and sanitation.html 59. Program, U.N.D. Sustainable Development Goals 2017 [cited 2017 9 28 2017]; Available from: http://www.undp.org/content/undp/en/home/sustainable development goals.html 60. Progr amme, U.N.D. Goal 3 Targets 2017 [cited 2017; Available from: http://www.undp.org/content/undp/en/home/sustainable developmen t goals/goal 3 good health and well being/targets/ 61. Programme, U.N.D. Goal 6 Targets 2017 [cited 2017; Available from: h ttp://www.undp.org/content/undp/en/home/sustainable development goals/goal 6 clean water and sanitation/targets/ 62. UNHCR. UNHCR Public Health 2016 Annual Global Overview 2016 [cited 2017 6/9/2017]; Available from: http://twine.unhcr.org/ar2016/ 63. . 64. . 65. . 66. .

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147 67. UNHCR. Practical Guide to the Sytematic Use of Standards & Indicators in UNHCR Operations 2006 [cited 2017 9 2 2017]; Available from: http://www.unhcr. org/en us/statistics/unhcrstats/40eaa9804/practical guide systematic use standards indicators unhcr operations.html 68. Johnson, P.E. GLM with a Gamma distributed Dependent Variable 2014; Available from: http://pj.freefaculty.org/guides/stat/Regression GLM/Gamma/GammaGLM 01.pdf 69. SSHCO. Jacob's Story: A Tale of Personal Tradedy and Trial 2017 [cited 2017 10 10 2017]; Available from: http://www.sshco.org/about founders.html

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148 BIOGRAPHICAL SKETCH Jacob Atem received a Bachelor of Arts degree in Pre Medicine/Biology from Spring Arbor University in 2008 and a Master of Public Health from Michigan State Unive rsity in 2010. He received his Ph.D from the University of Florida in the fall of 2017. He spent most of his life as one of the original Lost Boys of South Sudan. He is the President and Chief Executive Officer (CEO) of Southern Sudan Healthcare Organiza tion (SSHCO) from 2008 A Tale of Personal Tragedy and Trial http://www.sshco.org/about founders.html [69]