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AJ-3 Q8 Report2 July 2012

-Cooperative Biological ResearchPROJECT QUARTERLY REPORT

CBR Project Number and Title: Mapping Especially Dangerous Pathogens in Azerbaijan (AJ-3)Quarter: Dates of Quarter: 1 April – 30 June, 2012 Prepared By: Rakif Abdullayev (APS), Jason K. Blackburn, Ian T. Kracalik, and Lillian R. Morris (UF SEER Lab)

1 OVERALL PROJECT SUMMARYBackground/Justification

Understanding the spatial patterns of infectious diseases can provide insight into ecological/environmental, socio-economic, and other risk factors that promote outbreaks or disease persistence and potential improvements for control or eradication strategies. Geographic information systems (GIS) are increasingly being used to analyze geographical distribution of diseases as well as relationships between pathogenic factors (causative agents, patients, vectors and hosts) and their geophysical environments. A GIS can be simply defined as the personnel, computer hardware and software, database technologies, and spatial analyses that can be integrated to evaluate spatial relationships between disparate (and often times idiosyncratic) data sets to better understand the geographic structure of biological or geophysical phenomena. Basic and analytical applications of GIS in epidemiology can help in visualizing (mapping) and analyzing geographic distributions of diseases through time, thus revealing geographic patterns, spatio-temporal trends, and relationships that would be more difficult or obscure to discover in tabular or other formats.

These analyses can generate disease baselines (quantitative expectations of disease events across discrete geographic areas and time periods) against which monitoring systems can calibrate and better prepare for prevention and response operations. Understanding the spatial spread and temporal dynamics of an outbreak is central to the design of surveillance, prevention, control, and response strategies. Well-trained personnel equipped with GIS technologies and analyses provide a means to meet these needs and can be centrally placed as a powerful decision support team/tool box within epidemiology and emergency preparedness.

An expansive archive of historical records remains relatively intact at the Republican Anti-Plague Station (APS) in Baku, Azerbaijan. Examination of these records through the AJ-3 Project Development Grant (PDG) period has revealed potentially valuable historical disease surveillance data for several especially dangerous pathogens ranging from approximately 1930 until the late 80s. Data since the collapse of the Soviet Union is also maintained in this archive, though the data points collected during that time are sparse due to the resource vacuum for APS in the post-Soviet rebuilding period. The availability of this archive presents a unique opportunity to map historical especially dangerous pathogen prevalence within the country of Azerbaijan as well as leverage the core of epidemiologists

Bechtel National, Inc. 1


who are equipped, trained and experienced in the utilization of GIS for disease surveillance and Geographic Information Science (GISc) methodologies for spatial analysis and statistics for disease ecology. The records are expected to provide information on Y. pestis, F. tularensis, Brucella species, and B. anthracis. It is less likely but nevertheless possible that some records will report smallpox cases, Crimean Congo hemorrhagic fever (CCHF), tick borne encephalitis (TBE), or fevers of unknown origin. If other records of interest to CBEP are identified during the course of the project DTRA and the US collaborators will be made aware of their existence and the data will be made available. A unique opportunity exists to exploit this data archive, in that one of the project participants, Dr. Ayden Talibzade has intimate knowledge of the archive contents, having worked with the records since 1961.

Contemporary data on the four especially dangerous pathogens (EDPs) of focus for this project may also be subjected to GIS analysis and integration with the historical analysis, when contemporary data is sufficient for meaningful analysis. Sources of contemporary data may include: a) reports of cases made through the TADR network; b) cases identified during TADR Activity Projects; and c) cases identified in other CBR projects.

Initial efforts on the AJ-3 PDG showed the feasibility of the full project and developed a historical, village-level data set of human anthrax outbreaks. The PDG led to the creation of a presence/absence data set of villages in Azerbaijan reporting at least one or more human cases of anthrax by year from 1937 – 1998. This data set has been used in a retrospective spatio-temporal analysis. In short, we used this data set to determine if, when, where, and for how many years clusters (statistically significant locations or periods of disease reporting) of anthrax persisted in Azerbaijan during that period. However, this data set did not provide needed information on disease incidence (or how much of the human population was at risk in any given year). Our efforts on AJ-3 will include developing data sets that can address the issue of prevalence and incidence. Likewise, the AJ-3 project is focused on zoonotic diseases, and must capture important surveillance data on livestock populations (domestic ruminants for anthrax and brucellosis) and wildlife populations (small mammals, rodents and vector arthropods for plague and tularemia).

A second effort in the AJ-3 PDG led to the development a 13-year near continuous plague host and vector atlas from historical maps in the APS epidemiological archive (1972 – 1985; minus 1984). During the course of the AJ-3 PDG, we developed nearly 1,000 shapefiles and georeferenced 184 maps from this 13-year period. The PDG efforts lead to the development of the data set, but limited analyses were conducted on the data set during the period. It took nearly a year to catalog, digitize, and quality control the data sets. We aim to employ these data to pose a series of questions on the spatial distribution and ecological conditions associated with plague control and surveillance efforts during this Soviet period and we aim to identify more recent comparable data sets during the first quarters of the full project. Coupling historical and contemporary records provides one means of calibrating the historical baseline of plague-carrying host and vector populations relative to current species’ distributions and plague transmission risk.



During the latter months of the PDG (including the training trip to UFL and the recent UFL SEER Lab site visit to APS – October 2009), we began working on human incidence data sets at the rayon-level (all cases are aggregated to individual rayons and mapped as polygons) for both anthrax and brucellosis for the time period 1982 – 2009. These data sets are in the very early stages of development, but will form the data sets for a series of spatio-temporal analyses and GIS training sessions for AJ-3.

To organize the AJ-3 efforts, we have divided the project into four specific diseases within two major categories. First, we will develop data sets for anthrax, for the time period 1936-2009, and brucellosis, for the time period 1975-2011. This will establish the data set on bacterial zoonoses important to livestock and humans in AJ. The second series of data sets will focus on plague and tularemia for the time period 1973 – 2009 and establish the data set on vector-borne bacterial zoonoses.

Overall Project Objectives/HypothesesThis project will utilize historical disease surveillance records from the Republican Anti-Plague Station and the Republican Veterinary Laboratory to establish a GIS database of especially dangerous pathogens within the country with maps of multiple EDP foci. Any available data on pathogens that are the focus of the project reported through TADR and EIDSS will be used for additional analysis of EDP foci. The project will use and expand the skills of a core of epidemiologists who were equipped, trained and practiced in the utilization of GIS for disease surveillance through the PDG. The goals of the full project are:

1) To generate Disease Baselines: to mine existing historical data sets on plague, tularemia, brucellosis, and anthrax to perform GIS analysis that will give robust identification of EDP foci, provide distributional estimates of the pathogens’ hosts and vectors involved in these diseases, and identify potential times and locations of substantial risk for exposures/outbreaks.

2) To generate maps of historical EDP foci that can readily be compared with information on contemporary plague, tularemia, brucellosis, and anthrax cases identified through other CBEP activities; refine identification of foci, distribution, and risk for diseases where contemporary data is of sufficient quality and quantity including:

a. TADR system detection of diseases

b. TADR Activity Project findings of disease incidentsc. Other CBR projects’ detection of diseases

3) To maintain and expand GIS capacity at appropriate Azerbaijani institutes and provide skills and GIS infrastructure that will promote long-term sustainability and continued use in future projects.



4) To upgrade data archiving and mapping capabilities of existing and future surveillance efforts in Azerbaijan to further support CBEP, CBR, TADR, and in-county efforts to track EDP infections/outbreaks.

5) To provide accurate and up-to-date training in spatial techniques that allow personnel to interact with other GIS facilities within the CBEP region of interest and other international collaborations (such as the Kyrgyz Consortium for GIS Excellence, “KCGE”), and generate the opportunity to conduct competitive research in the international GIS arena.

6) Apply GIS to Mobile Response Unit (MORU) activities and analyze job performance through GIS.

2 TARGETED BACTERIAL AND VIRAL PATHOGENS

Bacterial pathogens: Brucella species, Bacillus anthracis, Yersinia pestis, Francisella tularensisViral pathogens: None (incidental only)

3 DISCUSSION OF OVERALL PROGRESS: Republican Anti-Plague Station (APS)3.1 Summary and Project Tasks completed this quarter

From April through June 2012, the following tasks were performed:

The following tasks were performed at the facility from April through June 2012:

The SEER lab from the University of Florida conducted a GIS training seminar at the APS and SVS in Baku, Azerbaijan. This training successfully engaged both groups at their respective institutes.

Clusters of human anthrax were identified at rayon-levels. In Azerbaijan the collapse of the Soviet Union has brought about major changes to the livestock sector during 1983-2000. The breakdown of collective and state farms led to widespread privatization, resulting in diminished livestock control measures, which has further contributed to the occurrence of human zoonoses. Analyzing the spatial patterns of health events may offer insight into the etiology of a disease and provide crucial information on any potential changes in the distribution of a disease (Jacquez 1996). The purpose of job performed this quarter was Spatial analyses were conducted to examine space-time patterns of incident human disease during Soviet and post-Soviet governance to study the possible re-emergence of anthrax and brucellosistwo major livestock zoonoses, anthrax (Bacillus anthracis) and brucellosis (Brucella spp.). These analyses allowed for the evaluation of baseline disease reporting and provide insight into the changing disease landscape after the fall of the Soviet Union. The work performed illustrated the importance of using dynamic baseline measures of disease occurrence rather than static ones.

A database of disease records consisting of case counts and incident occurrences of human disease per rayon was developed. This database was used to analyze the data spatially while



comparing human anthrax and brucellosis records from Soviet (1983 to 1991) and post-Soviet (1992 to 2000) governance.

Linear trend analysis was used identify whether there was an increasing or decreasing trend in the incidence of anthrax and brucellosis. The bivariate local Moran’s I (Anselin 1995) was employed to identify patterns of incident disease (anthrax or brucellosis) for each rayon.

Rates of Soviet and post-Soviet governance were spatially compared here. This test will identify whether or not high or low incident rates during the Soviet period clustered around high or low incident rates from the post-Soviet period. Additionally, SaTScan was used to test for spatial variation in a temporal trend by identifying individuals rayons that may be contributing to a decreasing or increasing trend in the disease rate.

An abstract (summary) was developed applying data and methods obtained from analysis of the status of human anthrax and brucellosis during Soviet and post-Soviet period (1983-2000) ) for submission to the conference (Thailand, 2012).Abstracts were developed and accepted to the DTRA review meeting in Istanbul, Turkey in September 2012.

Human anthrax during 1983-2000 was spatially and temporally analyzed. Incident disease reporting was broken into nine separate time period to visualize any changes in the reprting of the disease and to assist in establishing appropriate baseline thresholds of occurrence.

‘Hot Spots” of human anthrax and brucellosis - or rayons reporting statistically significantly higher than expected incidence based on multiple spatial statistical techniques were defined for three years and analyses were conducted according to cases. These techniques will be described in full detail in a manuscript by Abdullayev, Kracalik, et al. that will be submitted to DTRA.

Mapping of the geographic distribution of Bacillus anthracis, Francisella tularensis, and Yersinia pestis from pathogen passports is continued. Data entry focused on date, location (village, rayon), and source of bacteria from each isolate passport. To date, we have focused on B. anthracis isolates that were shared with WRAIR prior to AJ-3, and Y. pestis and F. tularensis passports evaluated by AJ-3 personnel prior to full project initiation. To date, approximately forty passports have been translated by BNI and UF has the strain list for B. anthracis and Brucella species sent to WRAIR.

A STAMP analysis was completed for the time period 1972 – 1985 to understand the spatio-temporal patterns of plague host abundance across the central region of the country. This quarterly report captures the first effort with STAMP. All spatial analysis results and methods are included. Final interpretations will be presented in the AJ-3 Final Report.

Additional training and project closeout have been scheduled for August 2012.

3.2 Deliverables Due this Quarter



Deliverables were not finalized during visit by the US collaborators scheduled for April 30- May 4 and the following tasks were assigned. We have submitted results to our US collaborators after completing our workjob.

Deliverables Due this Quarter: Republican Anti-Plague Station (APS)Task #1: This database was used tUsetilize database of disease records to analyze the incident disease data spatially while comparing human anthrax and brucellosis records from Soviet (1983 to 1991) and post-Soviet (1992 to 2000) governance and. Perform epidemiological analysis of spatial and temporal distribution was performed in GIS.Deliverable #1: This database was used to analyze the data spatially while comparing human anthrax and brucellosis records from Soviet (1983 to 1991) and post-Soviet (1992 to 2000) governance. to the conference to be held in San-Francisco, USA.

Task #32: To define whether there was an increasing or decreasing trend in the incidence of anthrax and brucellosis.Deliverable #32: Linear trend analysis was used identify whether there was an increasing or decreasing trend in the incidence of anthrax and brucellosis. The bivariate local Moran’s I (Anselin 1995) was employed to identify patterns of incident disease (anthrax or brucellosis) for each rayon.

Task #43: Tto test for spatial variation in a temporal trend of the diseaseDeliverable #43: SaTScan was used to test for spatial variation in a temporal trend by identifying individuals rayons that may be contributing to a decreasing or increasing trend in the disease rate.

Task #4: The space-time distribution of human anthrax was analyzed by grouping the data into nine different time period to better understand changing patterns of incident disease across Azerbaijan..Deliverable #4: Maps were created that visualize changes in the incident reporting of human anthrax in Azerbaijan during the time period 1983 to 2009.



Figure 1:. Yearly incidence per 1,000,000 population and case totals of human brucellosis in Azerbaijan during the period 1983 to 20012000.

Grey bars show case totals during the period of Soviet governance and black bars show the period post-Soviet governance. The dotted red line shows the incidence per year and the blue line describes

the linear trend over time (R2 = 0.77)

Figure 2: Yearly incidence per 1,000,000 population and case totals of human anthrax in Azerbaijan during the period 1983 to 2000. Grey bars show case totals during the period of Soviet governance

and black bars show the period post-Soviet governance. The dotted red line shows the incidence per year and the blue line describes the linear trend over time (R2 = 0.0003)



Figure 3. Map shows the average incident reporting per 100,000 population for human anthrax and brucellosis during Soviet and post-Soviet governance. Map A1 shows the average anthrax incidence by rayon during the period 1983 to 1991 and map A2 shows the average anthrax incidence during the period 1992 to 2000. Map B1 average brucellosis incidence by rayon during the period 1983 to 1991 and map A2 shows the average brucellosis incidence during the period 1992 to 2000.



Figure 4. Map shows the results of the bivariate local Moran’s I. The top map shows clustering between periods for anthrax and the bottom map shows clustering between periods for brucellosis. Rayons in red show clustering of high values between Soviet and post-Soviet eras. Areas in dark blue show clustering low values and areas in light blue show clustering of low values during the Soviet period around High values during the post Soviet period.



Figure 5. The top map displays a 12.5% percent annual increase in anthrax inside the buffer compared to a 2.9% decrease outside. The bottom map displays a 18.4% percent annual increase in brucellosis inside the buffer compared to a 8.9% increase outside.

Figure 6. Average incidence of human anthrax per 100,000 persons from 1983 to 2009 broken into 9, three year periods. Inset A displays the crude cumulative incidence risk by districts across Azerbaijan while inset B displays Spatial Empirical Bayes smoothed estimates. Darker colors represent higher risk estimates while lighter colors represent lower risk estimates. Numbers indicate the corresponding three year time period, with group 1 representing the period 1983 to 1985 and so on.



3.3 Materials and Methods: All data necessary in this period were gathered from Anti-Plague Station and State statistical committee. Report forms №-1 on infectious diseases, which are regularly submitted to the State statistical committee by rayon facilities, were obtained from the State statistical committee. Collected archive materials were initially directly sent to the collaborators. Later, the collaborators suggested that information be entered into a specially prepared Excel file. A database of disease records consisting of case counts and incident occurrences of human disease per rayon wereas derived from the archival records at the Anti-Plague Station in Baku, Azerbaijan. This database was used to analyze the data spatially while comparing human anthrax and brucellosis records from Soviet (1983 to 1991) and post-Soviet (1992 to 2000) governance. Additionally, a database on human anthrax consisting of average human incidence aggregated into nine, 3 year time periods was used to analyze the distribution of case reporting across space and time.

Linear trend analysis was used identify whether there was an increasing or decreasing trend in the incidence of anthrax and brucellosis. Patterns of incident disease (anthrax or brucellosis) for each rayon

Task: Mapping M. libycus

Figure 2 (working draft from Blackburn SEER lab): Mapped levels of Meriones libycus abundance by year as classified by annual APS reports. Each polygon represents a year between 1973 and 1985 (1984

excluded, year book missing). Pink area are no data.

Figure 2 illustrates the spatial distribution of Meriones libycus, a primary rodent host of Yersinia pestis in this region of the world. SEER Lab and APS have collaborated to identify, photograph, and digitize over 120 maps of historical field data on rodents, fleas, and the disease in AJ. This figure shows the spatial patterns of the five categories used in the historical APS data to categorize mammal abundance (as was defined in the APS annual year books summarizing plague and



tularemia). In this map, we have overlaid the distribution of each category for all years. In other words, the bottom two maps show consistent areas of high and very high abundance for this host. In the absence of current mammal collection data, these maps illustrate areas where the host was regularly collected in large numbers thirty years ago. Our field work and forthcoming analyses on habitat change suggest that some of these areas, such as Gobustan, have had limited habitat change, or these areas still require surveillance. These activities were studied thoroughly during this quarter and analyzed in GIS.

During Quarter 8, SEER Lab will provide a spatio-temporal analysis of the polygons in Figure 2 using the STAMP (spatio-temporal analysis of moving polygons) tool box and . Blackburn and Morris provided a training in Q-8, but part of the training will be conducted in Q-9.Spatio-Temporal Analysis of Moving Polygonstamp analysis of Meriones libycus from 1972 - 1985:

MethodsA shapefile was created for each of the five M. libycus abundance categories for each year that

data was available between 1972 and 1985. Each shapefile was compared to its corresponding digitized map image to ensure accuracy. The arcgis erase tool was used to eliminate overlapping layers, and accurately categorize polygons.

A STAMP analysis was used to explore the spatial changes of M. libycus abundance from 1972 to 1985. A separate STAMP analysis was conducted on each of the five abundance categories. Each STAMP analysis included polygons from every year that data was available for each abundance category. The area of each abundance category for each year was also calculated.

STAMP intersects home range polygons from two time periods, and new polygons are formed from the intersection. The new polygon layers are assigned an event type defined by the topological relationship between the two time periods . There are five potential event categories. Events created from spatial overlap can be defined as contraction, expansion, or stable. Contraction describes a portion of the first time period that is not present in the second time period, but is still connected to polygons from the second interval. Stable describes an area that is common to both time periods. Expansion describes a polygon that is only present in second time interval, but connected to first time interval. Two other events are defined by the spatial proximity between the two time periods: disappearance, and displacement. Disappearance describes a portion of time period one that is not connected to, or


Sonya Narodny, 07/09/12,

This was all included in the last report; please update or remove


This is confusing. Please re-word the sentence.

Aliyeva, Saida (CRDF), 07/09/12,

Rita confirmed that they informed that this trainings will be conducted later, but she is not sure when.


Officially we have 8 quarters.


Should this be Quarter 9?


included in time period two. Displacement indicates a portion of time period two that is not present in, or attached to time period one.

The STAMP analysis is composed of four steps . The first step of a STAMP analysis is to ensure input polygon layers are spatially exclusive. The second step creates change layers . The T2 classification was selected in this step to indicate that analysis was looking forward. The third step, voronoi polygons, uses the change layers and computes the directional relationship between polygons. The final step, polygon metrics, calculates the metrics and ratios from the change layers. Results There was 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. STAMP very low abundance output results and area calculations are shown in figure 1. 1972 is the year with the lowest area of very low abundance. Contraction is the primary event type from 1972 to 1973. 1975 is the year with the greatest area of very low abundance at 22564.16 square Kilometers, which is reflected in the large amount of expansion from 1974 to 1975. The area of very low abundance decreases from 1975 to 1976, and remains fairly stable from 1976 to 1977. STAMP low abundance results are shown in figure 2. 1977 was the year with the smallest area of low abundance, and 1983 had the largest area of abundance. There appear to be similar amounts of contraction, stable, and expansion event types from 1972 to 1973. The area for these two years stays relatively stable with a decrease from 15333.38 square Kilometers to 13904.51 kilometers. There is a large increase in low abundance area in 1974 characterized by a large proportion of expansion, and minimal contraction and disappearance events. Low abundance decreases in 1975 to 9440.97 square Kilometers, and the area remains relatively stable until an increase in 1980 to 27657.74 square Kilometers. While the area remains stable from 1975 to 1980, all event types are found in each STAMP analysis. Average abundance area ranges from 2072.98 square Kilometers in 1977 to 8478.61 square Kilometers in 1973 (Figure 3). The 1972 to 1973 STAMP output is dominated by expansion, and the 1973 to 1974 analysis shows a greater proportion of contraction. There is a steady decrease in average abundance area from 1973 (8478.61 square Kilometers) to 1977 (2072.98 square Kilometers) resulting in contraction and disappearance as primary event types. 1978 to 1982 shows a continuous increase in area. Area decreases from 6114.36 square Kilometers in 1982 to 3815.76 square Kilometers in 1983 with a large area of disappearance on the eastern border on the country. The high abundance STAMP results are dominated by generation, and disappearance events (figure 4). Polygons from each year are spread out across the country, and do not tend to overlap. The smallest area of high abundance is in 1983 with an area of 6.64 square Kilometers. 1974 has the largest area of 2639.57 square Kilometers. High abundance area calculations fluctuate from year to year. STAMP very high abundance completely disappears in 1973, 1976, and 1982 (figure 5). The year with the highest very high abundance area is 1981 with an area of 948.64 square Kilometers. Similarly to the high abundance results, the majority of event types are disappearance and generation. Polygons for very high abundance are smaller and more spread out than other abundance classifications.

1. Robertson, C., et al., STAMP: spatial–temporal analysis of moving polygons. Journal of Geographical Systems, 2007. 9(3): p. 207-227.

2. Nelson, T.A., Quantifying Wildlife Home Range Changes. Modern Telemetry, 2011.



Very Low Abundance




Figure 1. Very low abundance STAMP output


Low Abundance




Figure 2. Low abundance STAMP output


Average Abundance




Figure 3. Average abundance STAMP output


High Abundance




Figure 4. High abundance STAMP output


Very High Abundance




Figure 5. Very high abundance STAMP output


Figure 3 (working draft from Blackburn SEER lab): Probability of plague occurrence

The map in Figure 3 displays the predicted probability of plague occurrence from a logistic regression model in Azerbaijan based on the records obtained from historical pathogen passports housed at the APS. Variables used in the final model include Bio12 (annual precipitation), Bio1 (annual mean temperature), NDVI (naturalized difference vegetation index), Alt_Cat (a categorical altitude which divided elevation in the country by the median value 216 m), and an interaction variable between Bio12 and Alt_Cat (this allows different values of precipitation to vary across each of the two categories of elevation). Areas in red present a higher probability of plague while areas in green represent a lower probability. The overall accuracy of the model is high with an AUC =0.86.

Figure 4: Map shows the locations of villages with known livestock anthrax outbreaks during the period 1930 to 1999. The size of the circles represents the number of confirmed outbreaks in

livestock at village during the study period with large circles representing a greater number of outbreaks. See Appendix 1 for a full white paper on analyzing spatio-temporal patterns of this

data set.

3.4 Conclusion and Next Steps Results and Discussion:

This equarter’s results show that there were 175 cases of human anthrax and 1,822 cases of brucellosis during the Soviet Period (1983 to 1991), and 250 cases of anthrax and 5,731 cases of brucellosis during the post-Soviet period (1992 to 2000). (Figure 1-65). Linear trend analysis indicated that there was a significant increase in the incidence of brucellosis over time R2 = 0.77 (Figure 11,73), howeveralthough there was no significant trend found for anthrax incidence over time R2 = 0.00053 (Figure 2,73). The bivariate local Moran’s I showed that there was persistence in the occurrence of high incidence for both anthrax and brucellosis across time periods with high clustering rayons shown in red (Figure 84). The SaTScan analysis revealed the presence of local fluctuations in the disease rate across time. Figure 9 shows there was a 12.5% percent annual increase in anthrax inside the buffer compared to a 2.9%



Please update ALL figure references in the following paragraph. They do not match figures in the report.






decrease outside, and a 18.4% percent annual increase in brucellosis inside the buffer compared to a 8.9% increase outside the buffer.

The analysis of human anthrax and brucellosis illustrate the potential for a changing baseline occurrence of disease. Political and economic changes represent a threat to public and veterinary health. The increased rates of disease following the collapse of the Soviet Union highlight the need for sustained livestock management as well as the potential for the emergence of new or current infectious diseases if current health policies are not successful.

Further discussion requires synthesis and analysis of all data currently being digitized and/or added to GIS. Preliminary results indicate positive spatial and temporal association of EDP cases among animals and humans. Next steps are to continue as indicated in Work Plan and according to feedback provided by US collaborators. During the upcoming visit plans for Q8 activities will be developed.

The variability documented in the Meriones libycus abundance maps is quite interesting and there are apparent core areas of average and high in the western most and eastern most regions of the focus. Currently, Blackburn and SEER Lab are heading up an analysis of these changes and a statistical method to define these core areas within the focus. SEER Lab will request a translation of the pathogen passports to map Y. pestis isolates in relation to these core areas to test a hypothesis as to whether the expansion of the focus relates to increases in Yersinia pestis isolates. Passports have not been completely translated yet.

4 DISCUSSION OF OVERALL PROGRESS: State Veterinary Service (SVS)4.1 Summary and Project Tasks completed this quarter

In April 2 , new SVS personnel started getting acquainted with an electronic version of the GIS program. During From April 16- to 21, they took part in training courses on “Introduction to GIS” training courses atin the facility of Kyrgyz Center of Geoinformation Systems under Kyrgyz State University of construction, transportation and architecture named after N.Isanov. The training started with the an overview of GIS, which included information about GIS capabilities, types of data, and some basic functions , followed byof GIS. They learned about study ArcGIS, and its applications like ArcMAP, ArcCataloq and ArcToollbox.

From 28th of April till- 2 of May they had a 3- day completed additional training with US collaborators during at which discussed matters of infectious diseases (brucellosis and anthrax), on, using the models of previously developed map models,s they were explained learned how to develop a database and enter it into the program, and. Moreover, analysis was conducted based on the developed maps. By applying received information they were entering They then applied these new lessons to enter data into the map of the country (consolidated knowledge). In order to develop brucellosis and anthrax maps, SVS personnel were authorized to collect data from the districts of the country for the years 2002-2010.



Please update to reflect Q8 activities


Some anthrax data were submitted to US collaborators for processing. Brucellosis data were prepared during a month and sent to US collaborators. Brucellosis and anthrax data had beenwere extracted from reports of the Republican expedition under SVS. Data from sixty-fiveof 65 districts of the country for 2002-2012 were sent in Excel form.


Task #1: Data mining from SVS archiveDeliverable #1: In order to develop brucellosis and anthrax maps, SVS personnel were authorized to collect data from the districts of the country for the years 2002-2010. Some anthrax data were submitted to US collaborators for processing. Brucellosis data were prepared and sent to US collaborators. Brucellosis and anthrax data were extracted from reports of the Republican expedition department under SVS. Data from sixty-five districts in Azerbaijan from 2002- to 2012 were sent in Excel form.

MethodsTraining courses conducted in 16-21 April, 2012 in the facility of Kyrgyz Center of Geoinformation Systems within Kyrgyz State University of construction, transportation and architecture named after N.Isanov and in 24-26 April in State Veterinary Service (please specify dates, I don’t remember). Reports of Republican Expedition within State Veterinary Service by 65 rayons for 2002-2010 were used in order to develop database. Data were processed in Excel. . Studying basics of GIS, acquaintance with ArcGis software package and its applications ArcMAP, ArcCatalog and ArcToollbox, also development of geodatabase by using brucellosis and anthrax data for Azerbaijani rayons during 2002-2010. During April 16-21 they took part in training courses on “Introduction to GIS” in the facility of Kyrgyz Center of Geoinformation Systems under Kyrgyz State University. In order to develop brucellosis and anthrax maps SVS personnel were authorized to collect data from the districts of the country for the years 2002-2010. Some anthrax data were submitted to US collaborators for processing. Brucellosis data were prepared during a month and sent to US collaborators. Brucellosis and anthrax data had been extracted from reports of Republican expedition department under SVS. Data of 65 districts of the country for 2002-2012 were sent in Excel form.


Task #1: Data mining from SVS archiveDeliverable #1: In order to develop brucellosis and anthrax maps, SVS personnel were authorized to collect data from the districts of the country for the years 2002-2010. Some anthrax data were submitted to US collaborators for processing. Brucellosis data were prepared and sent to US collaborators. Brucellosis and anthrax data were extracted from reports of the Republican expedition department under SVS. Data from sixty-five districts in Azerbaijan from 2002 to 2012 were sent in Excel formMethodsTraining courses conducted in 16-21 April, 2012 in the facility of Kyrgyz Center of Geoinformation Systems within Kyrgyz State University of construction, transportation and architecture named after N.Isanov and in 24-26 April in State Veterinary Service (please specify dates, I don’t remember). Reports of Republican Expedition within State Veterinary Service by 65 rayons for 2002-2010 were used in order to develop database. Data were processed in Excel. . Studying basics of GIS, acquaintance with ArcGis software package and its applications ArcMAP, ArcCatalog



Please update this section to describe methods used (currently just recaps the other sections)


Addition from SVS participants.


and ArcToollbox, also development of geodatabase by using brucellosis and anthrax data for Azerbaijani rayons during 2002-2010.

4.4 Results and Discussion

1. Participation at training courses on the subject of “Introduction to GIS”, which took place in 16-21 April, 2012 in the facility of Kyrgyz Center of Geoinformation Systems within Kyrgyz State University of construction, transportation and architecture named after N.Isanov and in 24-26 April in SVS.2. Guided by the studied material and obtained knowledge, everyone individually developed simple cartographic projects, using map of Azerbaijan. They got acquainted with development of database and entering it into the program, also analyses were conducted based on already developed maps.3. Brucellosis data obtained from reports of Republican expedition within SVS, were processed, entered into Excel and sent to Jas.Efforts are ongoing. In the 8th quarter, there were In order to develop brucellosis and anthrax maps SVS personnel were authorized to collect data from the districts of the country for the years 2002-2010. Some anthrax data were submitted to US collaborators for processing. Brucellosis data were prepared during a month and sent to US collaborators. Brucellosis and anthrax data had been extracted from reports of Republican expedition department under SVS. Data of 65 districts of the country for 2002-2012 were sent in Excel form.

4.5 Conclusion and Next StepsThe next steps include Since brucellosis, anthrax and rabies are zoonotic diseases, we would like to study the veterinary data for further comparison with human cases in upcoming quarters. We will also work to find correlation within pieces of data, to include statistical analysis of relationships between diseases. Finally, we plan to study risk factors and evaluate retrospective and prospective data. More detailed analysis of data from data mining will be completed in future quarters, once more data has been enteredInitiating the project closeout and finalizing the analyses of disease data from tghe APS and SVS for inclusion into sceintific manuscripts..

5 ADMINISTRATIVE SECTION: All Institutes5.1 Problems Encountered

Our English skills are limited, subsequently we cannot benefit from broad information and international literature. We kindly ask our US collaborators to organize English language courses for GIS specialists of APS. We would highly appreciate consideration if this matter.

5.2 Work with CollaboratorsLiaison with Bechtel (BNI team), translations, coordination, direct email collaboration.

5.3 Training



Please update this section for Q8; it still shows text from last quarter.


Please update this section to describe results seen, if any, or other relevant summary information (currently just recaps other sections)






1. Training conducted for APS and SVS personnel during 30 April-4 May, 2012. Trainings were conducted at SVS and APS, Baku, Azerbaijan. 2 was very useful.

2. Training conducted for new SVS personnel during April 16-21: SVS they participants took part in training courses on “Introduction to GIS” in the facility of at the Kyrgyz Center of Geoinformation Systems under Kyrgyz State University, Kyrgyzstan, Bishkek. The report from the training is attached to the AJ-3 Q 8 report.

5.4 PublicationsPeer reviews were received for the mManuscript submitted to BMC Infectious Diseases. Input wasobtained from AJ-3 coauthors during the April/May site visit conducted by the SEER Lab. Revisionsand comments addressing the peer review were drafted and resubmitted to the journal. We arenow awaiting final approval from the journal for the manuscript listed below. :Analyzing the spatial and temporal distribution of human brucellosis in Azerbaijan (1995 - 2009) using spatial and spatio-temporal statisticsRakif Abdullayev, Ian Kracalik, Rita Ismayilova, Narmin Ustun, Ayden Talibzade, and Jason K. Blackburn

Two posters were created for publication and presented at the following conferences:

(June 13-16, 2012, Bangkok, Thailand):“The Status of zoonoses in Azerbaijan during Soviet and post-Soviet Governance”

Rita Ismayilova, Ian Kracalik, Rakif Abdullayev, Narmin Ustun, Ayden Talibzadeand the ASM 112th General Meeting, (June 16-19, 2012, San Francisco, California):

Analyzing the spatial and temporal distribution of human anthrax cases in Azerbaijan (1983-2009)Rakif Abdullayev, Ian Kracalik, Rita Ismayilova, Narmin Ustun, Ayden Talibzade and Jason Blackburn

Rita Ismayilova and Narmin Ustun participated at the International Conference in Thailand on 13-16 June, 2012. Ayden Talibzade and Agharahim Mammadsalahov participated at the conference in San-Francisco, USA. Posters are attached to the report.

Two Abstracts were submitted and accepted to the DTRA review meeting in Istanbul, Turkey:

"Mapping hotspots of anthrax and genetic diversity of Bacillus anthracis in Azerbaijan".

Rakif Abdullayev, Ayden Talibzade Rita Ismayilova, Narmin Ustun, Shikhiyev Mazahir, BaghirovaMehriban , Kliment Asadov, Ted Hadfield, Matthew Van Ert, Ian Kracalik, Mikeljon Nikolich, AllisonSchlak, Jason K. Blackburn

"Identifying areas of plague habitat in Azerbaijan: Comparing ecological modeling techniques to provide a better estimation of geographic suitability".

Ayden Talibzade, Ian Kracalik, Rakif Abdullayev, Rita Ismayilova, Narmin Ustun, and Jason K. Blackburn



Please list where training was conducted

users.clas.ufl.eduusers.clas.ufl.edu/jkblackburn/aj3q8.doc · web viewin april, new svs personnel...

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