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Informing Surveillance for the Lowland Plague Focus in Azerbaijan

Permanent Link: http://ufdc.ufl.edu/UFE0045491/00001

Material Information

Title: Informing Surveillance for the Lowland Plague Focus in Azerbaijan
Physical Description: 1 online resource (101 p.)
Language: english
Creator: Morris, Lillian
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2013

Subjects

Subjects / Keywords: azerbaijan -- plague
Geography -- Dissertations, Academic -- UF
Genre: Geography thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Yersinia pestis is a gram-negative,zoonotic pathogen that causes plague. Plague is maintained in nature through a transmission cycle between partially resistant rodent hosts and fleas. There are natural reservoirs on almost every continent, and the number of human plague cases has increased in recent years.  Azerbaijan is a country at the crossroads of Eastern Europe and western Asia that has a history of environmental plague foci.  Informing plague surveillance in this region is imperative due to the deteriorating public health system that resulted from the collapse of the Soviet Union. This study aims to prioritize regions for plague surveillance in Azerbaijan.  A 14 year historic data set was employed to analyze the spatio-temporal pattern of the primary plague host in the country, Meriones libycus,using the Space Time Analysis of Moving Polygons method (STAMP).  This method has the utility to identify areas that remained stable over time, which is meaningful when analyzing historic patterns. The relationship between stable M.libycus abundance and environmental variables including temperature,altitude, land cover type and annual precipitation was explored.  Changes in human population density over the historic period to modern times were also analyzed.  We were particularly interested in identifying increasing population trends in the area surrounding regions characterized by historically high M. libycus abundance,as the risk of human plague increases as humans come into close proximity with hosts and vectors.  We found that there was variation in M. libycus abundance over the historic period, but regions of stability were identified.  There are significantly different climatic and land cover conditions associated with different levels of abundance.  The population in Azerbaijan has steadily increased over the past 30 years, including regions bordering plague foci.  Surveillance should be prioritized for regions with historically stable high host abundance, regions with climaticconditions associated with high abundance, and regions with increasing populations surrounding plague foci.
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.
Statement of Responsibility: by Lillian Morris.
Thesis: Thesis (M.S.)--University of Florida, 2013.
Local: Adviser: Blackburn, Jason K.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2013
System ID: UFE0045491:00001

Permanent Link: http://ufdc.ufl.edu/UFE0045491/00001

Material Information

Title: Informing Surveillance for the Lowland Plague Focus in Azerbaijan
Physical Description: 1 online resource (101 p.)
Language: english
Creator: Morris, Lillian
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2013

Subjects

Subjects / Keywords: azerbaijan -- plague
Geography -- Dissertations, Academic -- UF
Genre: Geography thesis, M.S.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Yersinia pestis is a gram-negative,zoonotic pathogen that causes plague. Plague is maintained in nature through a transmission cycle between partially resistant rodent hosts and fleas. There are natural reservoirs on almost every continent, and the number of human plague cases has increased in recent years.  Azerbaijan is a country at the crossroads of Eastern Europe and western Asia that has a history of environmental plague foci.  Informing plague surveillance in this region is imperative due to the deteriorating public health system that resulted from the collapse of the Soviet Union. This study aims to prioritize regions for plague surveillance in Azerbaijan.  A 14 year historic data set was employed to analyze the spatio-temporal pattern of the primary plague host in the country, Meriones libycus,using the Space Time Analysis of Moving Polygons method (STAMP).  This method has the utility to identify areas that remained stable over time, which is meaningful when analyzing historic patterns. The relationship between stable M.libycus abundance and environmental variables including temperature,altitude, land cover type and annual precipitation was explored.  Changes in human population density over the historic period to modern times were also analyzed.  We were particularly interested in identifying increasing population trends in the area surrounding regions characterized by historically high M. libycus abundance,as the risk of human plague increases as humans come into close proximity with hosts and vectors.  We found that there was variation in M. libycus abundance over the historic period, but regions of stability were identified.  There are significantly different climatic and land cover conditions associated with different levels of abundance.  The population in Azerbaijan has steadily increased over the past 30 years, including regions bordering plague foci.  Surveillance should be prioritized for regions with historically stable high host abundance, regions with climaticconditions associated with high abundance, and regions with increasing populations surrounding plague foci.
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.
Statement of Responsibility: by Lillian Morris.
Thesis: Thesis (M.S.)--University of Florida, 2013.
Local: Adviser: Blackburn, Jason K.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2013
System ID: UFE0045491:00001


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1 INFORMING SURVEILLANCE FOR THE LOWLAND PLAGUE FOCUS IN AZERBAIJAN USING A HISTORIC DATASET By LILLIAN REBECCA MORRIS A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2013

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2 2013 Lillian Rebecca Morris

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3 To my mom and dad

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4 ACKNOWLEDGMENTS This project was funded by the United States Defense Threat Reduct ion Agency (DTRA) through the Cooperative Biological Engagement Program under the Cooperative Biological Research Project AJ 3. Funding was administered by the joint University Partnership managed by the University of New Mexico. I thank my family for the ir constant support guidance and motivation for all of my endeavors inside and outside of academia. I would also like to thank the members of the SEER lab for their help, encouragement and patience throughout this process I would like to thank my advisor, Jason Blackburn, for his dedication and enthusiasm. He has continuously challenged me to learn and grow as a scientist over the past two years. I would also like to thank the members of my committee, Liang Mao and Mike Binford, for their participation and guidance in writing this thesis. Finally, I would like to thank FUEL for providing a much needed and appreciated outlet throughout my graduate school career.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 7 LIST OF FIGURES .......................................................................................................... 8 LIST OF ABBREVIATIONS ............................................................................................. 9 ABSTRACT ................................................................................................................... 10 CHAPTER 1 INTRODUCTION .................................................................................................... 12 Plague Background ................................................................................................ 12 Primary Host and Focus ......................................................................................... 15 Plague in Azerbaijan ............................................................................................... 18 STAMP ................................................................................................................... 20 Plague and Climate ................................................................................................ 21 Human Plague Risk ................................................................................................ 23 Objectives ............................................................................................................... 25 2 METHODS .............................................................................................................. 27 Study Area .............................................................................................................. 27 Meriones libycus Data ............................................................................................. 28 Database Development .......................................................................................... 29 STAMP ................................................................................................................... 30 Stable Regions ....................................................................................................... 31 Environmental Data ................................................................................................ 32 Environmental Analysis ........................................................................................... 33 Human Population Analysis .................................................................................... 34 3 RESULTS ............................................................................................................... 44 STAMP ................................................................................................................... 44 Stable Regions ....................................................................................................... 44 Environmental Data ................................................................................................ 45 Environ mental Analysis ........................................................................................... 45 Human Population .................................................................................................. 46 4 DISCUSSION ......................................................................................................... 59

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6 Future Di rections .................................................................................................... 66 APPENDIX A STAMP OUTPUTS ................................................................................................. 67 B POPULATION DISTRIBUTION .............................................................................. 93 LIST OF REFERENCES ............................................................................................... 94 BIOGRAPHICAL SKETCH .......................................................................................... 101

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7 LIST OF TABLES Table page 2 1 L ist of host and vector species found in annual yearbooks ................................ 37 2 2 GlobCover classifications. .................................................................................. 38 3 1 Changes in the area from STAMP analysis ........................................................ 48 3 2 Mann Whitney U test, 5 categories .................................................................... 49 3 3 Descriptive statistics for environmental variables .............................................. 50 3 4 Mann Whitney U test, 3 categories ..................................................................... 51 3 5 The percentages of each land cover type ........................................................... 52

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8 LIST OF FIGURES Fig ure page 2 1 Azerbaijan with land cover ................................................................................. 39 2 2 Plague focus and protected areas in Azerbaijan ................................................ 40 2 3 Extracting data from annual yearbooks .............................................................. 41 2 4 Hand drawn maps .............................................................................................. 42 2 5 Event definitions for STAMP ............................................................................... 43 3 1 STAMP outputs from 1976 to 1977. ................................................................... 5 3 3 2 Stable regions for each abundance category ..................................................... 54 3 3 The distribution of environmental variables across Azerbaijan ........................... 55 3 4 Regions of stability for each abundance level .................................................... 56 3 5 The percentage of each land cover type ............................................................ 57 3 6 The percentage population change between 1970 and 2010. ............................ 58 A 1 STAMP outputs for very low Meriones libycus abundance ................................. 68 A 2 STAMP outputs for low Meriones libycus abundance ......................................... 71 A 3 STAMP outputs for average Meriones libycus abundance ................................. 77 A 4 STAMP outputs for high Meriones libycus abundance ....................................... 83 A 5 STAMP outputs for very high Meriones libycus abundance ............................... 89 B 1 HYDE population grids for 1970 and 2010. ........................................................ 93

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9 LIST OF ABBREVIATIONS APS Republican AntiPlague Station APD AntiPlague Division CDC Center for Disease Control CEPF Critical Ecosystems Partnership Fund GIS Geographic Information System GlobCover Global composites and land cover maps HYDE History Database of the Global Environment RMS root meansquare error STAMP Space Time Analysis of Moving Polygons WHO World Health Organization WorldClim Global Climate Data

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10 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science INFORMING SURVEILLANCE FOR THE LOWLAND PLAGUE FOCUS IN AZERBAIJAN USING A HISTORIC DATASET By Lillian Rebecca Morris May 2013 Chair: Jason B lackburn Major: Geography Yersinia pestis is a gram negative, zoonotic pathogen that causes plague. Plague is maintained in nature through a transmission cycle between partially resistant rodent hosts and fleas. There are natural reservoirs on almost ev ery continent, and the number of human plague cases has increased in recent years. Azerbaijan is a country at the crossroads of Eastern Europe and western Asia that has a history of environmental plague foci. Informing plague surveillance in this region is imperative due to the deteriorating public health system that resulted from the collapse of the Soviet Union. This study aims to prioritize regions for plague surveillance in Azerbaijan. A 14 year historic data set was employed to analyze the spatiot emporal pattern of the primary plague host in the country, Meriones libycus using the Space Time Analysis of Moving Polygons method (STAMP). This method has the utility to identify areas that remained stable over time, which is meaningful when analyzing historic patterns. The relationship between stable M. libycus abundance and environmental variables including temperature, altitude, land cover type and annual precipitation was explored. Changes in human population density over the historic period to m odern times were

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11 also analyzed. We were particularly interested in identifying increasing population trends in the area surrounding regions characterized by historically high M. libycus abundance, as the risk of human plague increases as humans come into close proximity with hosts and vectors. We found that there was variation in M. libycus abundance over the historic period, but regions of stability were identified. There are significantly different climatic and land cover conditions associated with dif ferent levels of abundance. The population in Azerbaijan has steadily increased over the past 30 years, including regions bordering plague foci. Surveillance should be prioritized for regions with historically stable high host abundance, regions with cli matic conditions associated with high abundance, and regions with increasing populations surrounding plague foci.

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12 CHAPTER 1 INTRODUCTION Plague Background Plague is a flea borne zoonosis caused by the gram negative bacterium Yersinia pestis ( Pollitzer 1954, Perry and Fetherston 1997, Gage and Kosoy 2005) Plague is a notorious dis ease that has been associated with three massive pandemics throughout history ( Gage and Kosoy 2005) The first plague pandemic spread across the Mediterranean in the 6th century and has be en linked to the weakening of the Byzantine empire ( Perry and Fetherston 1997) The Black Death, which killed almost one third of Europes population in the fourteenth centur y, has been attributed to plague. There is evidence that the black death originated from an environmental plague focus which is a region on the landscape that maintains the pathogen, in central Asia and spread to the south and east ( Pollitzer 1951) The third pandemic started in China in the 19th century ( Perry and Fetherston 1997, Stenseth et al. 2008) The spread of this pandemic was facilitated by rat infested steamships travelling to major ports ( Dennis 1998) An estimated 26 million plague cases resulted, with approximately 12 million fatalities ( Dennis 1998) The geographic range of plague has greatly expanded since the onset of the most recent pandemic ( Gage and Kosoy 2005) This expansion includes the Western United States, portions of India, and Southeast Asia ( Dennis 1998, Gage and Kosoy 2005, Pollitzer 1954) There has also been an increase in human plague cases From 1981 to 1995 approximately 20,000 human plague cases from 25 countries were reported to the World Health Organization (WHO). The Center for Disease Control (CDC) classifies Y. pestis as a Category A biological agent ( Rotz et al. 2002) Category A agents have the greatest potential for

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13 adverse public health impacts through mass casualties, which presents a bioterrorism concern. These agents require preparedness efforts including im proved surveillance ( Rotz et al. 2002) The greatest challenge related to plague control and surveillance is its presence and maintenance in rural, natural cycles ( Dennis 1998) Plague has a history of appearing in new populations or reemerging in a region that has not seen cases for extended time periods which is difficult to predict ( Dennis 1998) The 1994 pneumonic human outbreak in India exemplifies the necessity of monitoring this important pathogen because it reiterates the idea that there is a constant risk of human plague surrounding natural foci ( Dennis 1994 ) Y ersinia pestis is maintained in nature through a transmission cycle between partially resistant rodent hosts and adult hematophagous fleas ( Gage and Kosoy 2005, Meyer 1942) Yersinia pestis is a successful vector borne pathogen because it is able to survive in its host and also spreads from the site of a flea bite, which serves as a source of infection for feeding fleas ( Anisimov 2002) The infected flea spreads the bacteria to other rodent hosts. It is believe d that the bacteria can be maintained i ndefinitely in these enzootic or maintenance cycles ( Gage and Kosoy 2005, Beran 1994, Gage, Ostfeld and Olson 1995 ) The enzootic or primary host is able to maintain plague foci without the involvement of other hosts as long as sufficient numbers of flea vectors are present ( Gage and Kosoy 2005) When Y. pestis spreads from enzootic host s to more highly susceptible or secondary hosts then rapid die offs take place ( Gage and Kosoy 2005) Classically it is hypothesized that plague trans mission relies on the flea vector. High numbers of fleas tend to be correlated with a higher prevalence of plague ( Conrad, LeCocq and Krain 1968) There are more than 200 potential species of plague vectors

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14 that are specific to rodent hosts ( Gage and Kosoy 2005) Fleas are efficient vectors of Y. pestis as a result of a blocking process that takes place during the transmission cycles ( Bacot and Martin 1914) Once a flea has fed on an infected host the bacteria rapidly replicates in the fleas gut ( Bacot and Martin 1914, Bibikova 1977) The bacterial colonies grow large enough to block the movement of blood from the midgut to the foregut, which essent ially starves the flea. The starving flea feeds rapidly by using pharyngeal muscles to draw blood, but eventually has to relax those muscles, which leads to contaminated blood being flushed back to the feeding site infecting the host ( Webb et al. 2006, Bacot and Martin 1914) There is ongoing research on the role of partially blocked and unblocked fleas in plague transmission ( Gage and Kosoy 2005) It has been suggested that partially blocked fleas could play an important, short t erm role in transmission that helps sustain outbreaks ( Webb et al. 2006) Webb et al. ( 2006) f ound that blocked fleas cannot exclusively drive epizootics in prairie dogs. Short term reservoirs including other small mammals, infectious carcasses, and transmission from unblocked fleas likely drive disease spread during an outbreak. Over 200 species of rodents have been identified as playing a role in plague transmission cycles ( Gratz 1999) A successful host must have enough resistance to Y. pestis to allow bacteria to cycle through t he blood and infect fleas ( Meyer 1942) The amount of resistance in a host is related to variables including species, age, breeding status, immune and physiological status, and season ( Meyer 1942, Hubber t and Goldenberg 1970) A host population tends to contain a combination of susceptible individuals that die as a result of infection and more resistant individuals that survive

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15 infection ( Pollitzer 1954, Gage and Kosoy 2005) Recovered hosts likely become chronic carriers, which allows populations to maintain the bacteria between seasons ( Pollitzer 1954) It has been suggested that the impact of host populations on disease transmission depends on the ratio of resistant to susceptible individuals within the population ( Gage and Kosoy 2005) An effective host population tends to be heavily infected with multiple flea vectors, and live in burrows with high densities of rodents and fleas ( Pavlovsky, Plous JR and Levine 1966 ) Studi es have found that there is also a relationship between host abundance and plague prevalence in host communities. Davis et al. ( 2004) found that plague persistence in Kazakhstans desert region was related to the total abundance of the Great Gerbil, Rhombomys opimus hos t population. They suggest that the colonization and extinction dynamic affecting gerbil abundance determines the metapopulation context of plague ( Davis et al. 2004) In order to successfully monitor and control plague on the landscape, it is necessary to understand the distribution and abundance of hosts ( Stenseth et al. 2008, Gage and Kosoy 2005) Primary Host and Focus Large, natural foci of plague are active in Asia, part of the Russia Federation, and Asian republics ( Gratz 1999) Over the past twenty years, human plague cases have reemerged in this region ( Pollitzer 1954) Bertherat et al. ( 2007) reported a human plague outbreak in Algeria in 2003, which was the first reported instance of plague in the country for 50 years. Human plague cases have also been reported in Saudi Arabia ( Saeed, Al Hamdan and Fontaine 2005) Jordan ( Arbaji et al. 2005) Afghanistan ( Leslie et al. 2011) and a limited outbreak in Libya ( Tarantola et al. 2009) over the past decade. The reemergence of human plague in the region suggests that there are still

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16 active environmental reservoirs. The Republic of Azerbaijan is a country at the crossroads of western Asia and Eastern Europe that has three well documented historical plague foci ( Gurbanov and Akhmedova 2010) Meriones libycus is a major plague host in this part of the world ( Gratz 1999 Gage and Kosoy 2005, Gurbanov and Akhmedova 2010, Bakanidze et al. 2010) Meriones libycus has been documented as the primary plague host in the Trans continental lowland foothills plague focus in Azerbaijan ( Gurbanov and Akhmedova 2010) As early as 1953, M. libycus prevalence was linked to a plague epizootic in the Apshnon peninsula of Azerbaijan ( Bakanidze et al. 2010) In addition to its established role as a plague host, this ground dwelling gerbil plays a critical role in the maintenance of leishmaniasis in the greater Mediterranean area and Western Asia. Leishmanisis is a vector born disease caused by a protozoa transmitted by the bite of a sandfly, and presents a critical public health concern in several countries ( Gonzlez et al. 2009, Desjeux 2001) Meriones libycus is one species that maintains the zoonotic form of the disease in the environment ( Nadim and Faghih 1968) Human cases can result from humans comi ng into contact with sandflies inhabiting M. libycus burrows. In the Republic of Iran, M. libycus is the primary reservoir for zoonotic cutaneous leishmaniasis ( Rassi et al. 2006, Yag hoobi Ershadi, Akhavan and Mohebali 1996) Meriones libycus has also been linked to the maintenance of leishmaniasis in Saudi Arabia ( Ibrahim et al. 1994) It is clear that monitoring and controlling M. libycus populations has important implications for multiple public health initiatives.

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17 The natural range of M. libycus spans from the Western Sahara to Western Xinjiang, China ( Nowak and Paradiso 1999) They are found in a range of habitats including clay and sandy deserts, bush country, arid steppe, low plains, cultivated fields, grasslands, and mountain valleys ( Nowak and Paradiso 1999, Daly and Daly 2009) Meriones libycus has a rat like appearance characterized by narrow well developed ears, a tail the length of their head and body, elongated hind legs for leaping, and strong claws ( Nowak and Paradiso 1999 ) They eat green vegetation, roots, bulbs, seeds, cereal, fruits, and insects ( Nowak and Paradiso 1999) Meriones libycus live in complex multi entranced burrows, which are approximately 1.5 meters deep, and expand outward approximately 3 to 4 meters ( Nowak and Paradiso 1999) Their burrows generally have food storage chambers near the top, and nest ing chambers deeper in the ground ( Naumov et al. 1973) Individuals store as much as 10 kilograms of seeds at a time in the northern part of its range ( Naumov et al. 1973) Their preferred burrow location is under bush cover ( Daly and Daly 2009) which puts them at close proximity to flea vectors ( Gage and Kosoy 2005) Many individuals burrow in the same vicinity ( Naumov et al. 1973) They spend the majority of their time underground, and are prone to nocturnal activity ( Daly and Daly 2009) Males traverse large overlapping home ranges, while females prefer smaller more exclusive ranges ( Daly and Daly 2009, Nowak and Paradiso 1999) Femal es will remain in the same vegetative depression surrounded by desert for several consecutive months. Home ranges are between 50 and 120 meters in diameter ( Nowak and Paradiso 1999) Reproduction occurs year round, but usually takes place in late winter to early autumn. Each female produces 2

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18 to 3 litters, and litter sizes range from 1 to 12. The gestation period is 20 to 31 days ( Nowak and Paradiso 1999) Plague in Azerbaijan The concern about plague and its hosts has a long history in Azerbaijan. During the Soviet era, an Anti plague system (APS) was created to respond to outbreaks of plague and other bacterial and viral diseases ( Ouagrham Gormley 2006, Zilinskas 2006) These stations addressed disease through surveillance, research production and training efforts ; however, their primary objective was disease control ( Ouagrham Gormley 2006, Zilinskas 2006) During the Soviet era, the APS grew to include over 100 facilities throughout the region, which was the largest system of its kind the world had ever seen. Today, The APS in Baku is responsible for surveillance, identification, documentation and preventive measures against very dangerous infections (10 conditions including plague, cholera and anthrax). It has five regional branches known as Anti Plague Divisions (APD) that obtain laboratory samples and perform an initial diagnosis before referring samples to the APS for confirmation testing. However, contemporary field sampling for plague has been limited since independence from the Soviet Union. The first APD in Azerbaijan was a result of a plague outbreak in the Hadrut district of Azerbaijan in 1930. This outbreak prompted the establishment of a plague department within the Institute of microbiology in Baku, the capital city of Azerbaijan ( Ouagrham Gormley 2006) In 1934 the department became the central Anti plague station in Azerbaijan ( Ouagrham Gormley 2006) After several plague epizootic events in Azerbaijan the source was identified as a natural plague reservoir in Azerbaijan by Soviet scientists in 1953. T hree new f ield stations were established as a result

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19 ( Ouagrham Gormley 2006) As part of surveillance efforts in Azerbaijan, a detailed annual yearbook was published outlining every aspect of the APS effort for that year. Topics included preventative measures, prophylaxis of plague and other diseases, epidemiological observations, and epizootic observations. The yearbook also outlined lab research and field related work from the year. Other details such as the structure, financial status of the institute, and training efforts that took place at the institute were also discussed. In Azerbaijan, annual yearbooks were published for more than 40 years. Today, these yearbooks are maintained in the archival library at the Republican APS in Baku. APS yearbooks provide a unique and important opportunity to understand the history of plague in Azerbaijan. This is particularly relevant because surveillance efforts have been greatly limited since the collapse of the Soviet Union in 1991. The Republic of Azerbaijan gained its independence at this time; however, this collapse was characterized by diminished funding and maintenance for the APS system. With fewer resources available for surveillance, this thorough and detailed historic dataset can be used to inform modern surveillance efforts. One of the most thorough and repeated datasets in the yearbook collection outlined seasonal M. libycus abundance across the country. These hand drawn maps depicted M. libycus abundance using polygons, and cross hatched patterns to represent different levels of abundance. Each level of abundance is represented with a polygon of a particular pattern or color that differentiates it from the other abundance levels and host species. This is an important dataset to explore because of the continued significance of M. libycus as a plague host in Azerbaijan. The yearbooks spanned

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20 several years and represented the entire plague focus, allowing for the analysis of M. libycus abundance across space and over time. STAMP Exploring historical changes in M. libycus spatial patterns and abundance across the landscape can provide important insight into distribution and ecology of this important plague host. Identifying explicit regions with extended periods of high or low abundance can be particularly informative. Specifically, such analyses could provide a historical baseline of spatiotemporal patterns of host abundance that might inform contemporary effort s to direct enzootic sampling in Azerbaijan. The Space Time Analysis of Moving Polygons (STAMP) approach is one method for addressing these objectives with data such as those available in the APS yearbooks. STAMP uses polygons representing a phenomenon fro m two consecutive time periods and describes the type of change that is taking place between polygons. STAMP overlays polygons from consecutive time periods, and each incremental time change is categorized based on the associated spatial change ( Robertson et al. 2007) STAMPs change definitions, also called event types, are derived from the spatial proxi mity or overlap between the two time periods. The analysis includes the identification of regions that do not change, or that remain stable ( Robertson et al. 2007) STAMP has been applied to a variety of diverse research questions This method was initially employed to determine how a wildfire spread over time ( Robertson et al. 2007) Robertson et al. ( 2007) were able to determine the rate and direction of fire spread over a three week period using STAMP. This method was also used to determine differences in the area used by solitary female grizzly bears verses females with cubs over a two year time period ( Smulders et al. 2012) They were particularly

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21 interested in identifying differences in site fidelity between the two groups, which can be derived from areas classified as stable during a STAMP analysis ( Smulders et al. 2012) Nelson et al. ( 2011) employed STAMP to explor e changing caribou home ranges. A home range describes the space an animal uses over a specified time period and is commonly defined by polygons. A STAMP analysis of changing home ranges revealed the type of home range drift that occurred over the study interval ( Nelson 2011) As these applications reveal, STAMP can be used to compare two time periods, or can create a sequence to describe how a polygon changes over multiple time periods ( Robertson et al. 2007) Our analysis has many similarities to previous applications of STAMP. Our data consists of polygons to describe M. libycus abundance over a multiyear period. STAMP has the utilit y to analyze this type of data, and identify the regions of stability. The stable areas across years are of particular interest because human plague epidemics, as well as epizootic events, have been correlated to M. liby cus natural foci in the past ( Bakanidze et al. 2010, Daly and Daly 2009) Historical trends might be able to suggest current regions more likely to support high levels of plague host abundance. Plague and Climate Throughout history, links have been made between climatic conditions and plague prevalence. Precipitation, temperature, and relative humidity have been found to have the highest impact on the plague cycle ( Ben Ari et al. 2011) Seasonal plague events in India have been related to variations in temperature and humidity ( Rogers 1928) A pattern of fewer outbreaks in extreme hot or cold temperatures has been described for several African countries ( Davis 1953) Stenseth et al. ( 2006) fo und that warmer springs and wetter summers increase occurrence and levels of plague

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22 prevalence. Environmental foci tend to be found in semi arid to arid regions, and low humidity forests ( Perry and Fetherston 1997) Plague foci do not typically pe rsist for long periods in humid, tropical lowlands, or the highest, driest deserts ( Perry and Fetherston 1997) Elevation is another environmental variable that has been linked to plague persistence on the landscape. One study identified elevation as one of the most important variables in a model for predicting plague risk across the Lushoto district of Tanzania ( Neerinckx et al. 2010) A model of human plague risk in the s outhwest United States also identified elevation as a significant predictor ( Eisen et al. 2007b) Important relationships have been described between the plague host and climatic conditions. Cavanaugh and Marshall ( 1972) suggest that high intensity rainfall is detrimental to rodent survival, as burrows become flooded. There appears to be an association between annual rainfall, rodent densities and seasonal distribution of hosts ( Ben Ari et al. 2011) A recent study in New Mexico presented a trophic cascade hypothesis where precipitation resulted in increased plant production and rodent food sources ( Parmenter et al. 1999) The subsequent increase in host populations increases the likelihood of epi zootics and human cases ( Parmenter et al. 1999) There is a less apparent direct relationship between hosts and temperature. Though in temperate regions, low winter temperatures can impact food availability, which in fluences rodent densities and distribution ( Korslund and Steen 2005) Climate plays an important role in dictating the presence of plague on the la ndscape; therefore, climatic variables should be included when exploring questions relating to plague and its hosts. This analysis include d an exploration of the climatic conditions associated with rodent abundance over time. We focus ed on precipitation,

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23 temperature and elevation because they are known to influence the presence of plague and plague hosts on the landscape in other regions Understanding relationships between environmental factors and host abundance will help us to identify regions that mig ht be characterized by higher levels of host abundance. For example, if a region wa s historically characterized by high levels of rodent abundance we can hypothesize that stable climate conditions will maintain similar levels of plague and rodents in the region. Similarly, if there are climatic shifts this analysis can help detect new regions at risk of increasing host abundance and guide surveillance efforts. Human Plague Risk In order to thoroughly explore regions at the highest risk of plague transm ission, it is important to consider human population dynamics, as human plague cases frequently result from humans coming into contact with flea vectors ( Mann et al. 1979, Saeed et al. 2005) Plague epidemics still occur in developing countries and are commonly related to l arge epizootic events. When there is a large die off of host species, the flea vectors are forced to find another source of food, which causes the bacteria to spread outside of the enzootic, maintenance cycle ( Eskey and Haas 1940, Kartman 1970, Gage and Kosoy 2005) In California, studies have suggested that i ncreased serological p revalence of plague in coyotes, Canis latrans could be an indicator of a plague epizootic event in the region ( Thomas and Hughes 1992) Carnivores also provide a vehicle for infected fleas to travel to other populations ( Perry and Fetherston 1997) Flea vectors on dogs and cats is one method of facilitating human infection ( Mann et al. 1979) Human outbreaks are sometimes correlated with unsanitary or rat infested environments as the hosts, vectors and human populations are in a close spatial proximity ( Gage and Kosoy 2005) A human plague epidemic in

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24 Vietnam in the winter of 1967 was partially attributed to a rapidly increasing rat population and a high flea index ( Conrad et al. 1968) In the southwest United States, distance to host habitat is also a significant predictor of high risk human plague regions ( Eisen et al. 2007a) Handling or ingesting wild animal carcasses is another documented infection pathway. There was one reported human plague outbreak in Saudi Arabia linked to eating raw camel liver ( Saeed et al. 2005) More recently, a large outbreak with 83 cases, of which 17 were fatal, was attributed to eating camel meat in Afghanistan ( Leslie et al. 2011) Human cases generally start as the bubonic form of the disease, particularly if the bacterium was contracted from a flea bite. Symptoms include fever, headache, chills, and swollen lymph nodes, called buboes ( Perry and Fetherston 1997) Symptoms develop within 2 to 6 days of coming into contact with the bacteria. Septicemic plague develops as the infection spreads into the bloodstream ( Hull, Montes and Mann 1987) Pneumonic plague results from the lungs becoming infected. This is the most fatal form of plague. Pneumonic plague can be transmitted from person to person via respiratory droplets through close contact ( Perry and Fetherston 1997) Protected lands, such as national parks, create a dynamic that can bring humans and vectors into close proximity. This dynamic has the potential to effect Azerbaijan due to its inclusion in the Caucasus Biodiversity Hotspot, which is one of 34 biodiversity hotspots in the world ( Zazanashvili et al 2009) This designation is a result of the presence of diverse ecosystems, endangered species, and endangered vegetation ( CEPF 2003 ) The Caucasus region also has the greatest biodiversity out of any temperate forest in the world ( Zazanashvili et al. 2009) The bezoar goat, goitered

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25 gazelle, mouflon tar, and Caspian seal are all critically endangered species found in Azerbaijan ( Zazanashvili et al. 2009) Today approximately 10% of the country is protected lands, which includes national parks, stric t nature preserves, and wildlife sanctuaries. The number of protected lands in Azerbaijan has doubled since the collapse of the Soviet Union, and there are significant efforts to continue expanding the system in order to preserve the biodiversity in the c ountry ( Zazanashvili et al. 2009) The presence of nongovernmental organizations conc erned with conservation, and organizations such as the World Wildlife Fund, The Critical Ecosystem Partnership Fund, and the Eco Region Conservation Fund are all contributing to expanding the protected lands system ( Zazanashvili et al. 2009, CEPF 2003) Part of this effort includes the diversification of protected lands. Traditionally, Azerbaijan has created strict nature reserves that have minimal access and recreational opportunities for people. In recent years, the number of nat ional parks with recreational opportunities and public access has greatly increased ( Zazanashvili et al. 2009) The spatial proximity of human populations to natural reservoirs is clearly a risk factor for human cases. It is particularly important to monitor changing population densities in regions neighboring natural plague foci in order to gauge changing risks of human infection. Prioritizing limited resources for control efforts should incorporate an evaluation of regions at the greatest risk of human infection. Objectives The objective of this study was to inform and identify prioriti es for plague surveillance and control in Azerbaijan, which is critically important due to the limited resources available for public health efforts after the collapse of the Soviet Union. To achieve this objective, we explored changes in M. libycus abundance over space and

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26 time, and identified regions of historically stable host abundance. A second objective was to identify specific climatic factors associated with stable regions of mammal abundance by category The relationship between stable host abundance and changing population levels were also analyzed in order to identify regions characterized by an increased risk of human infection.

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27 CHAPTER 2 METHODS Study Area Azerbaijan is a small country located in the Caucasus region at the intersection of Western Asia and Eastern Europe ( Figure 2 1 ). There are 59 administrative districts, or rayons, in the country. Azerbaijan is bordered by the Caspian Sea to the east, Armenia and Georgia to the west and Russia to the north. The capital city, Baku, is on the east coast of Azerbaijan. The Greater and Lesser Caucasus mountain ranges run through the country. The Greater Caucasus range extends from Sochi Russia on the northeastern shore of the black sea and ends adjacent to Baku. The lesser Caucasus range runs parallel to the Greater range, about 100km to the south. In Azerbaijan, the Greater Caucasus mountain range parallels the northern border. The L esser Caucasus range spans the south western border between Armenia and Azerbaijan. This study focused on one of three plague foci in the country. APS scientists define the plague focus used for this study as the natural habitat of M. libycus in the region ( Figure 2 2 ). This area is characterized by constant presence of the Libyan jird, which was determined through year round perennial investigations. Meriones libycus natural habitat was employed to define this boundary because it is the primary carrier of plague in the Transcaucasian Plainsub Mountain Natural focus. There are currently 44 protected areas in Azerbaijan, which encompasses National parks, strict nature reserves, wildlife refuges and wildlife sanctuaries ( Zazanashvili et al. 2009) (Figure 2 2). Spatial data on protected lands was downloaded from the World Database on Protected Lands ( http://www.wdpa.org/ ). This database was derived from inf ormation from national governments, nongovernment

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28 organizations, academic institutions, and many other sources to provide a comprehensive global spatial dataset on marine and terrestrial protected areas. Meriones libycus Data Annual APS yearbooks thoroughly described every aspect of the stations activities for the year including lab activities, field work, and control efforts, which were reported using tables, charts, and maps. Historic yearbooks contained information on multiple plague hosts and vectors (Table 2 1). Host and vector data was displayed in hand drawn maps using polygons, colors, and patterns to represent different species, or abundance levels for the year. These datasets were found in the archival library at the Republican APS in Baku. Ou r research team extracted data from yearbooks in order to convert them to an electronic form more conducive to analysis in a Geographic Information System (GIS) (Figure 2 3). For this analysis, we use a subset of APS yearbook data from 1972 to 1985. We l imited this analysis to data on M. libycus because of its history as an important plague host in the country. Additionally, M libycus abundance maps were consistently published throughout the fourteen year period. The historic Azerbaijan dataset included M. libycus data collected during the fall season across the country. Meriones libycus themed maps defined abundance using 5 categories from 1972 to 1980 in the historic yearbooks: very low, low, average, high, and very high (Figure 2 4) Very low was de fined as 0 1 specimen per hectare. Low was 25 specimens per hectare. Average was defined as 6 10 specimens per hectare. 11 20 specimens per hectare was high abundance. Greater than 20 specimens per hectare defined very high abundance. Each defi nition was based on APS zoological sampling surveys conducted in the fall of each year. After 1980, very low and low were collapsed into one

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29 category defined as less than or equal to 5 specimens per hectare. Very low was no longer used due to the inexped iency in identifying areas with close to absent rodent populations. Instead, the regions of very low abundance were identified by zoologists based on visual inspection of the landscape for burrows or signs of recent rodent activity, but were not included in annual abundance maps. This analysis included an exploration of changes in M. libycus abundance over the historic time period. Database Development In order to analyze data available in annual yearbooks we photographed all maps from all yearbooks between 1972 and 1985; minus 1979 and 1984, as we could not locate these maps in the collection of yearbooks found in the Baku APS facility All photographs were captured as digital *.jpg images and organized by year. A small Olympus digital camera was used to capture high resolution photos. Each page for each yearbook was photographed two times to allow for quality comparisons. The digital camera was held near perpendicular to the map image laid flat on a table. All maps were cataloged according to translat ed titles and legends. Each map image was georeferenced using the georeferencing tools in ArcGIS v 9.3.1 (ESRI, Redlands CA) All maps were referenced back to a 1 m polygon outline of Azerbaijan from the GeoCommunity Geoportal. Each image was georefer enced to the WGS 1984 geographic projection of the world provided by ESRI using a minimum of eight control points. Control points are coordinate pairs assigned by the user that match the map position to real world coordinates. We employed an n+1 control point experiment to determine the most suitable number of control points from 5 to 25 to accurately georeferenced the images. There was minimal improvement after eight control points. We use the root meansquare error (RMS) and high spatial overlap

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30 between known Azerbaijani features (such as political boundaries) from existing GIS data and features on the images to minimize georeferencing error. Once images were georeferenced (with quality control), we constructed new GIS data layers to match each item in the map legend (points, line, and polygons) and then heads up digitized these shapes into spatially referenced shapefiles ( Curtis, Blackburn and Sansyzbayev 2006) ; the shapefile is an ESRI proprietary data format that is used worldwide. In this way, a single usable GIS layer was created for each map item. STAMP A STAMP ana lysis was used to explore the spatial and temporal variability of M. libycus abundance across the landscape from 1972 to 1985. A separate STAMP analysis was conducted on each of the five abundance categories. Each STAMP analysis included polygons from ev ery year that data were available for each abundance category. The very low abundance analysis incorporated 1972 to 1978, as very low and low abundance were collapsed after this time period. If a year was unavailable the next available year was used in i ts place. For example, 1979 was unavailable for all abundance categories, so polygons representing 1978 were compared to 1980. STAMP is a freely available toolbar extension for ArcGIS v 9.3 ( http://www.geog.uvic.ca/spar/stamp/help/index.html ). STAMP works by overlaying polygons from two consecutive time periods. The change between intervals is defined based on the type of spatial overlap (Figure 2 5). If polygons from two consecutive tim e periods are overlapping that area is classified as contraction, or expansion. Contraction indicates that the area was only present in the first time interval, while expansion indicates that a new area was created in the second time interval. Disappearance and generation events are spatially isolated, which means

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31 that they are not connected to any region delineating the opposing time period. Disappearance is only present in the first time period, while generation is only found in the second time period. Stable is an area common to both time periods. STAMP requires spatially un ique polygons To prepare digitized data, the erase tool was used to create unique polygons for each abundance level for each year. Georeferenced images of hand drawn maps were c onsulted to ensure the accurate categorization of polygons. All polygon layers were then projected ( WGS_1984_UTM_zone_38N ) Finally, multipart features were separated into single part features, which allowed STAMP to evaluate each polygon independently. The STAMP process i s comprised of four steps ( Robertson et al. 2007) The first step is to ensure that polygons input layers are spatially ex clusive. The second step creates change layers and assigns them to one of the five event categories: stable, generation, expansion, disappearance or contraction ( Robertson et al. 2007) The third step uses the change layers and computes the directional relationship between polygons by creating vorono i polygons ( Robertson et al. 2007) The final step, polygon metrics, calculates the metrics and ratios from the change layers ( Robertson et al. 2007) The area of each abundance category for each year was reported in square kilometers Stable Regions The STAMP analyses identified regions that remained stable between consecutive years. Those outputs were used to evaluate inter annual variability for each category across all consecutive time periods. We were also interested in identifying areas characterized by longterm persistence. To identify stable regions spanning more than two years, stable event polygons were extracted from all STAMP

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32 outputs for each abundance level. Overlapping stable layers from consecutive years within each abundance category were identified using the intersect tool in ArcGIS v 10. The overlapping portion of the polygon was used to create regions of stability. These stable regions were then used to evaluate environmental conditions associated wit h each abundance category. Environmental Data STAMP allowed us to identify regions where a particular abundance category persisted for an extended time interval, and we were interested in determining if there were climatic conditions associated with differ ent levels of stable M. libycus abundance. Interpolated world climate surfaces were used to explore potential relationships between the environment and stable regions. WorldClim climatic data are freely accessible on the WorldClim website ( www. WorldClim .org ) ( Hijmans et al. 2005) These data a re available at a 1km spatial resolution. WorldClim data w ere derived from a network of ground based weather stations, and reflect data collected between 1950 and 2000 ( Hijmans et al. 2005) A smoothing spline algorithm was used for interpolation using latitude, longitude and elevation as independent variables ( Hijmans et al. 2005) WorldClim includes over 20 variables describing climate in a variety of ways. Some of these variables include precipitation in the wettest month, precipitation in the driest month, minimum temperature of coldest month, and mean diurnal range. Annual mean temperature (BIO1), annual precipitation (BIO12), and altitude were downloaded for analyses. Similarly to our climate analysis, we attempted to identify unique land cover types associated with different levels of stable rode nt abundance. We obtained land cover data from GlobCover v 2.2 (ESA GlobCover project ). GlobCover is a land cover dataset

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33 at a 300 meter resolution with a thematic resolution of 22 classes ( http://www.ionia1. esrin.esa.int ). The data was created from satellite images obtained from 2005 to 2006. GlobCover has been employed for a variety of recent scientific analyses. Linard et al. ( 2011) found that using GlobCover resulted in the most accurate human population modelling across Africa compared to other available land cover datasets. Falcucci et al. ( 2013) incorporated GlobCover data into their model of wolf recolonization of the alpine r ange. The GlobC over dataset identified 16 land cover classifications found throughout Azerbaijan. We collapsed the land cover categories comprising a small percentage of Azerbaijan, which resulted in 8 categories used for analyses: rain fed cropland, mos aic cropland, deciduous forest, evergreen forest, mixed forest, shrubland/grassland, sparse/barren, and water (Figure 2 1, Table 2 2) Environmental Analysis Climatic data were paired with stable regions of abundance for each category to explore relationships between climatic conditions and M. libycus abundance. Identifying unique characteristics related to different levels of abundance could help to predict abundance levels for modern surveillance efforts. T o make WorldClim data compatible with stable regions, t he area of all stable regions from each abundance category were combined using the merge and dissolve tools in ArcGIS v 10. Temperature, precipitation, and altitude values were extracted from polygons representing the stable area for each abundanc e level using the raster clip tool in ArcGIS v 10. The resulting attribute tables were imported to the R statistical package for analyses ( http://www.rproject.org/ ). The maximum value, minimum value, mean, median and range were calculated for each variable at each abundance level. The Mann Whitney U test was

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34 used to determine if climatic conditions were significantly different for each abundance level. The Mann Whitney U test is a nonparametric test that compares the me dian differences between two distributions ( Crichton 2000) This is an appropriate test when data being compared are naturally linked and do not follow a normal distribution ( Crichton 2000) The null hypothesis of the Mann Whitney U test is that the median differenc e between paired values is equal to zero ( Wilcoxon 1945, Mann and Whitney 1947) This test run in R, was used to compare each abundance category with the other abundance categories for all three environmental variables. The level of confidence was set at 95%. To identify distinctive land cover descriptions for each abundance level, t he land cover data set was clipped to each of the polygons representing stability for each level of abundance to determine if there were unique land cover conditions for different abundance levels. The total number of raster cells within each polygon was calculated. The proportion of each land cover type for each abundance category w as computed by dividing the number of cells representing each land cover type by the total number of raster cells within the polygon. Human Population Analysis The risk of human infection should be considered when prioritizing regions on the landscape for control and preventative measures as human plague risk is inherently linked to the proximity of human populations to the pathogen. Toward this, t he objective of this analysis was to inform surveillance of natural plague foci throughout Azerbaijan. Hist ory Database of the Global Environment v 3.1 (HYDE) gridded time series population data were downloaded ( http://themasites.pbl.nl/tridion/en/themasites/hyde/ )

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35 in an effort to explore the relationship between M. libycus abundance and human population levels ( Klein Goldewijk et al. 2011) HYDE includes georeferenced historical gridded population data for the past 12,000 years at a 5 (9.56 km) resolution ( Goldewijk 2005) The data were derived from a combination of population statistics and satellite information with specific allocation algorithms that change over time ( Klein Goldewijk et al. 2011) Availabl e population totals for each country were crosschecked with other sources, which were primarily local country studies ( Goldewijk 2005) The Populstat database ( Lahmeyer 2000) and Gazetteer (2004) were the tw o primary sources employed for deriving HYDE population maps from 1700 to 2000 ( Goldewijk 2005) Gaps in data were overcome by interpolating data points ( Goldewijk 2005) HYDE data has a variety of applications including environmental assessments, and biological diver sity analyses. The Global environmental outlook for the United Nations Environmental Program (UNEP, 1997), have used HYDE data. Gaston et al. ( 2003) used HYDE data in their analysis of global avian biodiversity loss. In an effort to understand how population levels have changed from our historic study interval to modern times, the population grids for 1970 and 2005 (the most recent available surface) were downloaded. The 2005 surface was projected to 2010 using the United Nations, medium variant, inter censal growth rate by country (UNPD world population prospects), which is in line with the methods of Hay et al. ( 2009) The 2010 population surface was derived using Where is the population within each pixel, represents the population at year x in the same pixel, r is average growth rate, and t is the number of years between 2010 and

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36 x ( Hay et al. 2009) The resulting 2010 population grid was used to create a surface representing the percentage change in population from 1970 to 2010. All calculations were computed using the raster calculator in ArcGIS v 10.

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37 Table 2 1. List of host and vector species found in annual yearbooks Common Name Genus Species Hosts Libyan jird Meriones M. libycus Per sian jird Meriones M. persicus Tristram's jird, Malaysian jird Meriones M. tristami Vinogradovi's jird Meriones M. vinogradovi Common Vole Microtus M. arvalis Social Vole Microtus M. socialis Vectors Fleas Callopsylla C. caspius Ctenophthalmus C. wladimiri Nosopsyllus N. consilimis Nosopsyllus N. iranus Nosopsyllus N. laericeps Xenopsylla X. conformis

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38 Table 22. GlobCover classifications for land cover types found throughout Azerbaijan and definitions of land cover classifications. The definitions report the combined definitions of categories that were collapsed. Name Definition Mixed Forest Closed to open (>15%) mixed broadleaved and needleleaved forest (>5m) Deciduous Forest Closed or open Broadleaved Deciduous Forest (>5m) Ev ergreen Forest Closed or open Needleleaved Deciduous or Evergreen Forest (>5m) Shrubland / Grassland Mosaic grassland, shrubland (broadleaved or needleleaved, evergreen or deciduous, <5m), herbaceous vegetation (grassland, savannas or lichens/mosses) Rainfed Cropland Rainfed Croplands Mosaic Cropland and Vegetation 20 70% Cropland, 20 70% vegetation (grassland/shrubland/forest) Sparse / Barren Sparse (<15%) vegetation or bare areas Water Water Bodies

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39 Figure 21 Azerbaijan with land cover, bordering countries and important rayons identified. The land cover categories were derived from GlobCover v 2.2, and reflect the final eight categories resulting from collapsing the 16 categories identified in Azerbaijan by the GlobCover surface.

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40 Figur e 22. Plague focus and protected areas in Azerbaijan. The focus is defined by M. libycus natural habitat in the area. The protected areas are depicted based on the year of their designation.

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41 Note: Photos courtesy of Jason Blackburn Figure 23. Extracting data from annual yearbooks in the APS archival library in Baku, Azerbaijan

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42 bottom map is from 1981. Note: Photos courtesy of Jason Blackburn Figure 2 4. Hand drawn maps delineating Meri ones libycus abundance with translated legends from annual yearbooks. A) 1972 Meriones libycus abundance. B) 1980 Meriones libycus abundance. A Libyan Gerbil 0 1 Specimens per ha 1 5 Specimens per ha 6 10 Specimens per ha 11 20 Specimens per ha More than 20 Specimens per ha Settlement type pesthole Very High Low Average High Common Vole Vinograds Gerbil B

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43 Figure 25 Event definitions for Space Time Analysis of Moving Polygons (STAMP). E ach circle represents an area in one of two consecutive time periods. Concentration, stable, and expansion are defined by overlapping areas, but contraction is only in time period one while expansion is only in time period two. Disappearance and generation are events that are spatially isolated from other areas. Close Spatial Proximity Time 1 Contraction Time 2 Expansion Time 1 + Time 2 Stable Time 1 Disappearance Time 2 Generation Spatially Independent

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44 CHAPTER 3 RESULTS STAMP There w ere no data available on M. libycus abundance for 1979, or 1984 in any abundance category. Every year from 1972 to 1985 included M. libycus abundance for low, average, and high abundance categories. Very low abundance data was available from 1972 to 1978. Very high abundance was available for every year except 1973, 1976, and 1982 (Table 31 ) The boundaries for each abundance category changed every year ( Table1 ). There were no years when the area of any abundance category was completely stable. Low rodent abundance had the largest average area over the study interval. Very high abundance had the smallest area over the study area. Very high abundance was frequently found close to Samukh. Low abundance spanned the entire central portion of the country. The area calculations for all years and all abundance categories are shown in Table 2. All inter annual STAMP outputs are shown in Appendix A Stable Regions Stable r egions spanning more than two years were identified for every abundance category (Figure 3 2 ). Regions of low stable abundance were the most widespread across Azerbaijan, and tended to persist longer than other abundance categories Stable regions of low abundance were concentrated directly east of Baku, and bordered the lesser Caucasus region. The longest period of stability was a low abundance region that persisted from 1976 to 1985. S table areas associated with average and high abundance did not consis tently persist for more than five years. Areas of average abundance were more widespread, and tended to be smaller than low

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45 and very low abundance stable regions Average abundance stable regions were the most prominent in the Samukh region, and the west ern border of Baku. All stable regions defining high and very high abundance were in Samukh. There were four regions associated with stable high abundance, and only one region of stability was identified for very high abundance Environmental Data Precip itation, temperature, and altitude ranges across Azerbaijan are shown in Figure 3 3 The two Caucasus mountain ranges in Azerbaijan are characterized by unique environmental conditions compared to the rest of the country The highest altitudes are found in these regions in addition to the highest precipitation levels and lowest temperatures. The central portion of Azerbaijan, from the Samukh rayon to south of Baku, showed relatively stable levels of precipitation, temperature and altitude. Environmental Analysis Altitude, temperature, and precipitation variables were extracted and analyzed for each of the five abundance categories. The Mann Whitney U test revealed that there was not a significant difference between very high and high for any of the envi ronmental variables (Table 3 2 ). Data on very low abundance was not available after 1978. As a result, we were compelled to collapse very low and low into one category and high and very high into another category for environmental analyses. This resulted in three categories: low, average, and high abundanc e (Figure 3 4 ). These t hree abundance categories were used for all subsequent analyses. Each abundance category was characterized by significantly different climatic and land cover conditions. These di stinctive characteristics can help identify regions that should be prioritized for surveillance and control. Stable areas of high abundance

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46 had the highest average annual temperature, altitude, and annual precipitation (Table 3 3 ). Stable l ow regions had the lowest average annual temperature and altitude. Stable a verage abundance had the highest average precipitation, as a result of its overlap with the Lesser Caucasus mountain range along the western border of the country. Low abundance stretched up the northeast border of Azerbaijan and into the Greater Caucasus region, across a wider range of temperatures, altitudes and precipitation levels than the other two abundance categories. Stable high abundance was limited to Samukh, and was characterized by t he smallest ranges for all three variables. All abundance levels were significantly different for each environmental variable except temperature in high abundance regions compared to temperature in low abundance regions (Table 3 4 ). The region associated with each abundance category had a different land cover composition. The landscape delineating low rodent abundance was dominated by mosaic cropland based on GlobCover characterizations (Figure 3 5 Table 3 5 ). High abundance regions were dominated by s hrubland/grassland and sparse/barren land cover. The landscape associated with average abundance was approximately 30% mosaic cropland and 22% grassland / shrubland. Mixed forest, evergreen, and deciduous all comprised less than 1% of total land cover for each abundance category, but are the most prominent in low abundance. Human Population The highest percentage increase in human populations was along the southern border of the plague focus in the lesser Caucus region (Figure 3 6 Appendix B ). The area surrounding Samukh, which included the stable region of high abundance, was characterized by approximately 50% increases in population levels since 1970. The

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47 central portion of Azerbaijan also experienced approximately 50% increase in population levels over the 40 year period. The Greater Caucus region, which borders stable low abundance, was another region that experienced up to a 100% increase in human population between 1970 and 2010.

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48 Table 3 1 Changes in the area representing each abundanc e category over time. The total area associated with each abundance cat egory for each year is reported. No te: ND = No Data Year Very Low Abundance Area (Sq KM) Low Abundance Area (Sq Km) Average Abundance Area (Sq Km) High Abundance Area (Sq Km) Very High Abundance Area (sq KM) 1972 4859.67 15333.38 5419.4 717.91 305.05 1973 8738.92 13904.51 8478.61 6354.78 0 1974 4050.69 25070.44 5659.06 2639.57 290.63 1975 22564.16 9440.97 4178.55 1128.08 235.61 1976 10604.22 6824.64 2370.56 580.41 0 1977 15417.32 4303.45 2072.98 501.02 77.37 1978 7025.66 7687.52 2205.41 1026.39 165.53 1980 ND 27657.74 2853.18 626.12 241.45 1981 ND 21291.7 5033.66 544.52 948.64 1982 ND 28038.79 6114.36 56.77 0 1983 ND 30504.17 3815.76 6.64 160.36 1985 ND 29033.75 2108.9 305.42 172.22

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49 Table 3 2 Wilcoxon signed rank test results for temperature, precipitation, and altitude comparing five abundance categories The null hypothesis being tested is that there is no significant difference in environmental variables between abundance categories R ej ect the null hypothesis with 95% confidence ** R eject the null hypothesis with 99% confidence High v. Very high High v. Average High v. Low High v. Very Low Very High v. Average Very High v. Low Very High v. Very Low Average v. Low Average v. Very Low Low v. Very Low Temperature Statistic 667 394278 2780926 84699 7 43117 3 13012 98752 12856601 9 38356594 196215207 P.value 0.44 0.07 <0.001** <0.001 ** 0.57 0.04* <0.001** <0.001** <0.001** <0.001** Precipitation Statistic 958 2775322 3028050 75233 9 353292 392333 95538 55356675 6 146705200 173157853 P.value 0.14 <0.001** <0.001** <0.001 ** <0.001* <0.001** <0.001** <0.001** <0.001** <0.001** Altitude Statistic 840 461061 3234434 71202 5 50585 360680 79071 13316060 6 29822902 149264722 P.value 0.58 <0.001** <0.001** <0.001 ** 0.08 <0.001** 0.06 <0.001** <0.001** <0.001**

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50 Table 3 3 Descriptive statistics for the distribution of temperature, precipitation, and altitude associated with each of the three abundance levels. Low Av erage High Temperature (Degrees Celsius) Min. 10.1 10.1 13.7 1st Qu. 13.5 14 14.3 Median 14.2 14.6 14.5 Mean 14.03 14.31 14.55 3rd Qu. 14.7 14.8 14.8 Max. 15.4 15.3 15.2 Precipitation (Millimeters) Min. 243 243 337 1st Qu. 348 343 396 Median 373 371 416 Mean 377.9 369.7 406.9 3rd Qu. 398 395 429.5 Max. 672 601 473 Altitude (Meters) Min. 42 32 70 1st Qu. 7 15 154 Median 41 122 209 Mean 126.2 161.8 202.8 3rd Qu. 204 259 257.5 Max. 1023 993 402

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51 Table 3 4 Mann Whitney U test re sults for temperature, precipitation, and altitude comparing three abundance categories. The null hypothesis being tested is that there is no significant difference in environmental variables between abundance categories R eject the null hypothesis with 95% confidence ** R eject the null hypothesis with 99% confidence. High v. Average High v. Low Aver age v. Low Temperature (Degrees Celsius) Statistic 437395.00 4039687.00 167000000.00 P.value 0.05 >0.001** >0.001** Precipitation (Millimeters) Statistic 3128614.00 4268260.00 700271956.00 P.value >0.001** >0.001** >0.001** Altitude (Meters) S tatistic 511645.00 4386209.00 162983507.50 P.value >0.001** >0.001** >0.001**

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52 Table 3 5 The percentages of each land cover type t hat comprises the landscape for high, medium, and low M. libycus abundance. Land Cover Type Low Average High Rainfed Cropland 11.13% 7.49% 7.92% Mosaic Cropland 55.90% 30.10% 9.43% Deciduous 0.06% 0.03% 0.00% Evergreen 0.33% 0.20% 0.00% Mixed Forest 0 .20% 0.03% 0.00% Grassland / Shrubland 14.60% 22.19% 29.51% Sparse / Barren 16.30% 36.04% 36.38% Water 1.48% 3.85% 16.75%

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53 Figure 3 1 STAMP outputs from 1976 to 1977. A) is the change in very low abundance from 1976 to 1977; B ) is low abundance from 1976 to 1976. C ) is average abundance from 1976 to 1977. D ) is high abundance from 1976 to 1977. E) is very high abundance from 1976 to 1977.

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54 Figure 3 2 Stable regions for each abundance category representing regions that remained stable for at least 2 consecutive years. A) shows the region of Azerbaijan that each of the subsequent maps focuses on. B) is very low abundance. C) is low regions of stability that persisted for at least 5 year s D ) is average abundance stable regions E ) is high abundance stable regions. F ) is very high abundance stable regions

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55 Figure 3 3 The distribution of environmental variables across Az erbaijan. A) shows temperature. B) is precipitation. C) is alt itude across the country. All climatic data was downloaded from WorldClim.

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56 Figure 3 4 Regions of stability for each abundance level. Each polygon represents the area that was stable for at least 2 consecutive years anytime between 1972 and 1985. A ) is low abundance. B ) is average abundance. C ) is high abundance.

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57 Figure 3 5 The percentage of each land cover type associated with regions of high, average, and low rodent abundance

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58 Figure 36. The percentage population change between 1970 and 2010. Dark red indicates an increase in population. Stable regions for high, average, and low abundance area are also shown.

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59 CHAPTER 4 DISCUSSION Plague presents a pressing public health concern in the developing world. Plague has a history of devastating pandemics, and t here has been an increase in human cases in recent years. There is also evidence that climate change could further increase human disease risk. This threat is particularly relevant in the former Soviet Union, and its bordering countries The collapse of the Soviet Union was accompanied by a deteriorating public health system that was left with limited resources for disease control and surveillance efforts. There is also evidence of active historical foci in countries surrounding Azerbaijan. In Iran, a recent study found high numbers of host and vectors in a historically active focus. Yersinia pestis was detected in rodent hosts, which suggests that plague is being maintained in the environment ( Esmaeili 2013) Continued plague surveillance in these regions is essential. The goal of this study was to inform plague surveillance in one environmental focus in Azerbaijan. The first objective was to use a historic data set to evaluate patterns of persistence in M. libycus abundance in Azerbaijan from 1972 1985. It has been established in the literature that plague prevalence is related to the distribution and density of hosts on the landscape, and Meriones libycus is an important plague host in Azerbaijan ( Gage and Kosoy 2005, Davis et al. 2004) W e were particularly interested in identifying geographic regions of longterm stability in M. libycus abundance, as these regions of historical M. libycus persistence should be prioritized. A second objective was to associate environmental and climatic characteristics with different levels of M. libycus abundance. Environmental characteristics correlated to different levels of abundance would provide a way to predict M. libycus across the

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60 country. Similarly, stable environmental conditions have the potential to be associated with stable levels of M. libycus abundance. Finally, we explored changes in human population densities. Effectively prioritizing regions for surveillance must consider the risk of human infection. Overall, this study identified v ariability in the spatial distribution of M. libycus over the 13 year study period in all abundance categories. Regions characterized by low M. l ibycus abundance were the most stable over time with several regions persisting for more than five years. For the other abundance categories, regions of stability did not tend to persist for more than five years but every abundance category had a stable region that was maintained for at least two years. Stable regions of low rodent abundance were the most widespread and continuous across Azerbaijan. Areas of stable average rodent abundance were found on eastern and western portion of the country, but were not as continuous. Landscapes consistently characterized by high abundance were limited to Samukh in the northwest portion of Azerbaijan. It is important to consider the variability in abundance that the STAMP analysis established. There were no abundance levels that were spatially or temporally stable over the entire study period. Abundance levels fluctuated within the boundaries representing each category; however, those boundaries represent regions that have been characterized by the persistence of one abundance level for multiple years at some point between 1972 and 1985. From a surveillance perspective, these historically stable regions can help inform surveillance by prioritizing regions with a history of higher abundance levels. If a region was historically characterized by high abundance, modern surveillance should prioritize that region for control efforts.

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61 There were significant differences in environmental characteristics associated with different rodent abundance categories Higher count s of M. libycus wer e correlated with the greatest amount of annual precipitation, higher mean temperatures, and higher altitudes. There is little variability in temperature, precipitation, and altitude across the region of Azerbaijan delineated by M. libyc us data employed in this analysis, but these fine scale differences are important when considered within the context of the entire plague system. The distinguishing characteristics correlated with each abundance level can help predict changes or continued stability in M. libycus abundance. If climate remains stable, the levels of rodent abundance will likely reflect historical levels of M. libycus abundance. If conditions become warmer and wetter then we might hypothesize M. libycus abundance is more lik ely to increase. It is also important to consider the relationship between plague prevalence and host abundance. Ideally, control efforts would be prioritized for M. libycus populations with active Y. pestis Here we have shown a relationship between rel atively warm, wet climatic conditions and M. libycus host abundance in Azerbaijan. A n association between warm, moist climate and higher levels of flea vectors has also been discussed in the literature ( Davis 1953, Cavanaugh and Marshall 1972 ) Plague prevalence in several places worldwide have also been correlated to w arm springs and wet summers. Plague is a complex system with numerous factors affecting prevalence and spread; however, in general terms, high host abundance, high vector abundance and pathogen presence have been related to similar, broad scale environmental conditions. It is also important to consider that plague is more likely to persist in the environment with a higher abundance of rodent hosts ( Gage and Kosoy 2005, Stenseth et al. 2008) These

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62 findings suggest that regions associated with stable high rodent abundance are likely at a higher risk of plague prevalence. Our findings suggest that areas historically categorized as high abundance should be prioritized for surveillance efforts bec ause they are the most likely to support plague prevalence. The landscapes delineating each abundance category had different land cover compositions. The land cover in Samukh, which contains stable high abundance, is characterized by higher proportions of sparse/barren landscape, shrubland, and grassland than the remainder of the country. In contrast, northwestern Azerbaijan has more forested area and mosaic cropland than Samukh where high abundance stability occurred. These land cover compositions can be used to prioritize landscapes more likely to support high levels of plague hosts. Several studies have suggested that human proximity to plague hosts is a risk factor for human infection ( Schotthoefer et al. 2012, Eisen et al. 2007b, Kartman 1970) Schotthoefer et al. ( 2012) found that living close to environmental plague reservoirs in New Mexico was a significant risk factor for human plague. They also found that changing socioeconomic demographics were correlated to changes in the location of plague cases ( Schotthoefer et al. 2012) Essentially, changes in human population dynamics are important to consider when prioritizing surveillance. In Azerbaijan, human populations have increased in and around the plague focus. This is particularly concerning in the area surrounding regions of historically high M. libycus abundance. Increasing human populations, high levels of host abundance, and stable climate c ould create an intensified human plague risk in this region. Locations with growing human

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63 populations in close proximity to natural plague foci should be prioritized for surveillance and control efforts. The increasing number of protected lands, coupled with growing populations has potential implications for plague risk in Azerbaijan. In other parts of the world, national parks have been correlated with increased human disease risk. In Kyrgyzstan, the highest risk region of tick borne encephalitis is in Ala Archa National Park, which is close to the capital city ( Briggs et al. 2011) The park is a popular attraction for hikers, climbers, and tourists who come into close proximity with the rodent hosts and tick vectors that inhabit the park ( Briggs et al. 2011) In California, human plague cases have also been linked to host and vector populations in national parks. One model predicting plague host distribution identified national parks in California as a probable location for vector distribution ( Adjemian et al. 2006) These predicted distributions also reflected sites of previous human cases ( Adjemian et al. 2006) In the 1970 s, California experienced an increase in human plague cases, and many of those cases were attributed to host populations in national parks ( Nelson 1980) Wilderness areas, and national monuments were also locations marked as high risk for plague maintenance in the state ( Nelson 1980) The increase in National Parks in Azerbaijan has the potential to provide an opportunity for plague hosts, such as M. libycus and flea vectors to come into contact with people visiting the par k. National parks, particularly those in close proximity to large population centers, should be prioritized for surveillance. Working with historical data is inherently associated with challenges. Our original data w ere in the form of hand drawn maps t hat were photographed georeferenced and hand digitized. It is likely that there were errors associated with this process. As a

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64 result of the nature of the original data, the areas of polygons were not exact, and this analysis was based on comparing the relative size difference in polygons. The historic M. libycus dataset also contains some sampling bias. It is unclear if the same regions were sampled consistently over the fourteen year period. We know that sampling efforts were largely driven by expert opinion of known rodent habitat, which creates a biased sampling design. It is possible that some of the spatial variation identified in M. libycus abundance is due to this sampling bias. While it is important to consider the challenges related to histor ic datasets, the benefits associated with analyzing historical data are particularly relevant to the study of disease. Similarly to the challenges we encountered with our data, the literature has established sampling bias, or nonuniform reporting as the primary hurdle associated with employing historic data sets ( Cliff et al. 1997) Despite these complications historic data still has the potential to provide context for current outbreaks and should be used ( Cliff, Haggett and SmallmanRaynor 2008) Cliff et al. ( 1997) liken the use of historic publi c health records to the use of long term climate data. In order to effectively improve short term forecasts, it is necessary to understand the long term patterns ( Cliff et al. 1997) The reemergence and resilience of disease across the globe is another reason studying past patterns is important ( Cliff et al. 1997 Cliff et al. 2008) Using geographic information systems (GIS) is an effective method for analyzing historic data because of its capacity to integrate data from different sources and dates ( Gregory and Healey 2007) GIS also provides a framework for explori ng change over a historic time interval ( Gregory and Healey 2007) Cunfer ( 2005) used annual agricultural data and environmental data sets to explore the cause of the great plains dust storm. Skinner et

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65 al. ( 2000) also used GIS to analyze trends in fertility rates in Chinas from the 1960s to the 1990s. Some additional limitations associated with this study include the STAMP toolbar which is not compatible with ArcGIS v 10, which is the most recent version. The applicability of STAMP to a wide range of questions calls for an updated version of the software. The G lobCover dataset employed was derived from satellite images taken in 2005 and 2006, which might not reflect conditions at the time this M. libycus data was collected. Our research group is currently investigating historical land cover change in Azerbaijan to determine the degree of land cover stability over time using a remote sensing approach. Despite these limitations, valuable information was obtained from this analysis Our findings are important and relevant for three primary reasons. Plague still affects human populations worldwide, and needs to be carefully monitored ( Stenseth et al. 2008, Perry and Fetherston 1997) Impending climate change has the capacity to increase prevalence of gerbil hosts in the future, which can increase the frequency at which plague can occur ( Stenseth et al. 2006) Finally, changes in the public health system that accompanied the collapse of the Soviet Uni on have limited resources available for plague surveillance. Our results can be used to prioritize limited resources for the surveillance and control of environmental plague foci in Azerbaijan. Regions of historically high M. libycus abundance should be prioritized. Regions of the country with climatic conditions associated with high abundance should also be prioritized. Employing predictive climate change models is one way to identify regions likely to experience a climatic shift

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66 towards favorable pla gue conditions. Similarly, stable climate is likely to be associated with stable rodent abundance. Regions with increasing human populations bordering plague foci should be monitored, as these present a high risk of human infection. Finally, protected lands with public access should be monitored because of the close proximity of humans and vectors. Future Directions An important future direction will be to analyze M. libycus abundance at a finer temporal scale. In order to thoroughly understand the impact of climate on rodent abundance we need to study seasonal variations in M. libycus abundance and the correlated climatic variation. Ideally, future sampling efforts could take place on a seasonal basis throughout Azerbaijan. This effort would also requ ire a climatic dataset at a finer temporal scale to analyze seasonal variations. A modern analysis compared to historical data would allow us to determine if a shift in abundance levels has taken place since 1985. A more thorough understanding of stable regions could be obtained. A modern data set describing rodent abundance throughout Azerbaijan would be a necessary first step to meet these objectives. The annual historic yearbooks contain data on multiple other hosts and vectors. The exploration of these additional data sets could provide a more thorough picture of how plague hosts and vectors are spread across the landscape. Incorporating yearbook data that includes lab analysis and spatial information on plague isolates would provide an informative element to this analysis. In order to evaluate the plague risk in Azerbaijan, we need to understand the roles of all hosts, vectors and the prevalence of the pathogen in the region

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67 APPENDIX A STAMP OUTPUTS All STAMP outputs for all years and all five categories (very low, low, average, high, and very high) of M. libycus abundance are shown. A 1 includes Very low abundance STAMP outputs from 1972 to 1978. Each STAMP output reflects the change between two consecutive years. For example, the change in area representing very low M. libycus abundance from 1972 to 1973 is one map, and the change in area from 1973 to 1974 is shown on a separate map. A 2 includes the STAMP outputs for low abundance from 1972 to 1985, A 3 is the STAMP outputs for average abundanc e from 1972 to 1985, A 4 includes STAMP outputs for high abundance from 1972 to 1985, and A 5 is very high abundance STAMP outputs from 1972 to 1985.

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68 Figure A 1. STAMP outputs for very low Meriones libycus abundance. A) through F) shows STAMP outputs from 1973 to 1978. 1972 1973 1973 1974 Contraction Disappearance Expansion Generation Stable A B

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69 1974 1975 1975 1976 Contraction Disappearance Expansion Generation Stable C D Figure A 1 Continued

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70 Figure A 1 Continued 197 6 197 7 E 197 7 197 8 Contraction Disappea ranc e Expansion Generation Stable F

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71 Figure A 2. STAMP outputs for low Meriones libycus abundance. A) to K) shows STAMP outputs from 1973 to 1985. Contraction Disappearance Expansion Generation Stable A B 1972 1973 1973 1974

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72 Contraction Disappearance Expansion Generation Stable Figure A 2 Continued C D 1974 1975 1975 1976

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73 Contraction Disappearance Expansion Generation Stable Figure A 2 Continued E F 1976 1977 1977 1978

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74 Contraction Disappearance Expansion Generation Stable Figure A 2 Continued G H 1978 1980 1980 1981

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75 Contraction Disappearance Expansion Generation Stable Figure A 2 Continued I J 1981 1982 1 982 1983

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76 Contraction Disappearance Expansion Generation Stable Figure A 2 Continued K 1983 1985

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77 Figure A 3. STAMP outputs for average Meriones libycus abundance. A) to K ) shows STAMP out puts from 1973 to 1985. Contraction Disappearance Expansion Generation Stable A B 1972 1973 1973 1974

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78 Contraction Disappearance Expansion Generation Stable Figure A 3 Continued C D 197 4 197 5 197 5 197 6

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79 Contraction Disappear ance Expansion Generation Stable Figure A 3 Continued E F 1977 1978 1976 1977

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80 Contraction Disappearance Expansion Generation Stable Figure A 3 Continued G H 1978 1980 1980 1981

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81 Contraction Disap pearance Expansion Generation Stable Figure A 3 Continued I J 1981 1982 1982 1983

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82 Contraction Disappearance Expansion Generation Stable Figure A 3 Continued K 1983 1985

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83 Figure A 4 STAMP outputs for high Meriones libycus abundance. A ) to K ) shows STAMP outputs from 1973 to 1985. Contraction Disappearance Expansion Generation Stable A B 1972 1973 1973 1974

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84 Contraction Disappearance Expansion Generation Stable Figure A 4 Continued C D 1974 1975 1975 1976

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85 Contraction Disappearance Expansion Generation Stable Figure A .4 Continued E F 1976 1977 1977 1978

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86 Contraction Disappearance Expansion Generation Stable Fig ure A 4 Continued G H 1978 1980 1980 1981

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87 Contraction Disappearance Expansion Generation Stable Figure A 4 Continued I J 1981 1982 1982 1983

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88 Contraction Disappearance Expansion Generation Stable Figure A 4 Continued K 1983 1985

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89 Figure A 5 STAMP outputs for very high Meriones libycus abundance. A ) to H ) shows STAMP outputs from 1973 to 1985. Contraction Disappearance Expansion Generation Stable A B 1972 19 74 1974 1975

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90 Contraction Disappearance Expansion Generation Stable Figure A 5 Continued C D 1975 1977 1977 1978

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91 Contraction Disappearance Expansion Generation Stable Figure A 5 Continued E F 1978 1980 1980 1981

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92 Contraction Disappearance Expansion Generation Stable Figure A 5 Continued G H 1981 1983 1983 1985

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93 APPENDIX B POPULATION DISTRIBUTION Figure B 1 HYDE population grids showing the population distribution in Azerbaijan. A) for 1970. B) 2010.

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98 Nadim, A. & M. Faghih (1968) The epidemiology of cutaneous leishmaniasis in the Isfahan province of Iran: I. The reservoir II. The human disease. Transactions of the Royal Society of Tropical Medicine and Hygiene, 62 534542. Naumov, N. P., V. S. Lobachev, P. P. Dmitriev, V. Kanatov Iu & V. M. Smirin (1973) [Experience in studying the rate of spread and paths of transm ission of plague epizootics in the Northern Desert]. Zh Mikrobiol Epidemiol Immunobiol, 50, 7885. Neerinckx, S., A. T. Peterson, H. Gulinck, J. Deckers, D. Kimaro & H. Leirs (2010) Predicting potential risk areas of human plague for the Western Usambara Mountains, Lushoto District, Tanzania. Am J Trop Med Hyg, 82, 492500. Nelson, B. C. (1980) Plague studies in Californiathe roles of various species of sylvatic rodents in plague ecology in California. Nelson, T. A. (2011) Quantifying Wildlife Home Range Changes. Modern Telemetry Nowak, R. M. & J. L. Paradiso. 1999. Walker's mammals of the world. Cambridge Univ Press. Ouagrham Gormley, S. B. (2006) Growth of the Anti plague System during the Soviet Period. Critical reviews in microbiology, 32, 3346. Parmenter, R. R., E. P. Yadav, C. A. Parmenter, P. Ettestad & K. L. Gage (1999) Incidence of plague associated with increased winter spring precipitation in New Mexico. The American journal of tropical medicine and hygiene, 61, 814821. Pavlovsky, E. N., F. K. Plous JR & N. D. Levine (1966) Natural nidality of transmissible diseases. The American Journal of the Medical Sciences, 252, 161. Perry, R. D. & J. D. Fetherston (1997) Yersinia pestis --etiologic agent of plague. Clinical microbiology reviews, 10, 3566. Pollitzer, R. (1951) Plague studies: I. A summary of the history and a survey of the present distribution of the disease. Bulletin of the World Health Organization, 4 475. Pollitzer, R. (1954) Plague. Geneva: WHO Rassi, Y., E. Javadian, M. Ami n, S. Rafizadeh, H. Vatandoost & H. Motazedian (2006) Meriones libycus is the main reservoir of zoonotic cutaneous leishmaniasis in south Islamic Republic of Iran. Eastern Mediterranean Health Journal, 12, 474. Robertson, C., T. A. Nelson, B. Boots & M. A Wulder (2007) STAMP: spatial temporal analysis of moving polygons. Journal of Geographical Systems, 9 207227.

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101 BIOGRAPHICAL SKETCH Lillian Morris was born in 1989 in Baltimore, Maryland. She grew up in Baltimore and graduated from the Bryn Mawr School in 2007. She attended the University of Colorado in Boulder, and graduated with a B achelor of A rts in g eography in 2011. Sh e was accepted to the UF D epartment of Geography masters program, and was offered a research assistantship in the Spatial Epidemiology and Ecology Research lab in conjunction with the Emerging Pathogens Institute in 2011. She received her Master of Scienc e from the University of Florida in spring 2013.