Application of modern spatio-temporal analysis technologies to identify and visualize patterns of rabies emergence among different animal species in Kazakhstan.

During the period 2013-2023, 917 cases of rabies among animals were registered in the Republic of Kazakhstan. Out of these, the number of cases in farm animals amounted to 515, in wild animals to 50 and in pets to 352. Data on rabies cases were obtained from the Committee for Veterinary Control and Supervision of Kazakhstan, as well as during expeditionary trips. This research was carried out to demonstrate the use of modern information and communication technologies, geospatial analysis technologies in particular, to identify and visualize spatio-temporal patterns of rabies emergence among different animal species in Kazakhstan. We also aimed to predict an expected number of cases next year based on time series analysis. Applying the 'space-time cube' technique to a time series representingcases from the three categories of animals at the district-level demonstrated a decreasing trend of incidence in most of the country over the study period. We estimated the expected number of rabies cases for 2024 using a random forest model based on the space-time cube in Arc-GIS. This type of model imposes only a few assumptions on the data and is useful when dealing with time series including complicated trends. The forecast showed that in most districts of Kazakhstan, a total of no more than one case of rabies should beexpected, with the exception of certain areas in the North and the East of the country, where the number of cases could reach three. The results of this research may be useful to the veterinary service in mapping the current epidemiological situation and in planning targeted vaccination campaigns among different categories of animals.

Rabies in the Republic of Kazakhstan: spatial and temporal characteristics of disease spread over one decade (2013-2022).

Rabies is a fatal zoonotic disease that remains endemic in Kazakhstan despite the implementation of annual vaccination campaigns. Using data collected over a 10-year time period, the objective of this study was to provide updated information on the epidemiological situation of the disease in the country, and quantitative data on the species-specific spatial distribution of rabies and on the epidemiological features associated with that clustering. Five significant (p < 0.05) clusters of disease were detected. Clusters in southern Kazakhstan were associated with companion animals, which are likely explained by the maintenance of a domestic cycle of the disease in the most densely populated region of the country. Livestock cases were most frequent in clusters in the eastern (where wildlife cases were also frequent) and western regions of Kazakhstan, with higher probability of occurrence in spring and summer, compared to the rest of the year. The results here are consistent with differential patterns for disease transmission in Kazakhstan and will contribute to the design and implementation of zoning approaches to support the progressive control of rabies in the country.

The progressive control of foot-and-mouth disease (FMD) in the Republic of Kazakhstan: Successes and challenges.

Foot-and-mouth disease (FMD) has historically caused far-reaching economic losses to many regions worldwide. FMD control has been problematic, and the disease is still prevalent in many West and Central Asia countries. Here, we review the progress made by Kazakhstan in achieving freedom from FMD and discuss some of the challenges associated with maintaining the FMD-free status, as evidenced by the occurrence of an outbreak in 2022. A combination of zoning, movement control, vaccination, and surveillance strategies led to eliminating the disease in the country. However, the circulation of the FMD virus in the region still imposes a risk for Kazakhstan, and coordinated strategies are ultimately needed to support disease elimination. The results presented here may help design effective pathways to progressively eliminate the disease in West and Central Asia while promoting the design and implementation of regional actions to support FMD control.

Mapping the risks of the spread of peste des petits ruminants in the Republic of Kazakhstan.

Peste des petits ruminants (PPR) is a viral transboundary disease seen in small ruminants, that causes significant damage to agriculture. This disease has not been previously registered in the Republic of Kazakhstan (RK). This paper presents an assessment of the susceptibility of the RK's territory to the spread of the disease in the event of its importation from infected countries. The negative binomial regression model that was trained on the PPR outbreaks in China, was used to rank municipal districts in the RK in terms of PPR spread risk. The outbreak count per administrative district was used as a risk indicator, while a number of socio-economic, landscape, and climatic factors were considered as explanatory variables. Summary road length, altitude, the density of small ruminants, the maximum green vegetation fraction, cattle density, and the Engel coefficient were the most significant factors. The model demonstrated a good performance in training data (R2  = 0.69), and was transferred to the RK, suggesting a significantly lower susceptibility of this country to the spread of PPR. Hot spot analysis identified three clusters of districts at the highest risk, located in the western, eastern, and southern parts of Kazakhstan. As part of the study, a countrywide survey was conducted to collect data on the distribution of livestock populations, which resulted in the compilation of a complete geo-database of small ruminant holdings in the RK. The research results may be used to formulate a national strategy for preventing the importation and spread of PPR in Kazakhstan through targeted monitoring in high-risk areas.

Modelling bluetongue risk in Kazakhstan.

BACKGROUND: Bluetongue is a serious disease of ruminants caused by the bluetongue virus (BTV). BTV is transmitted by biting midges (Culicoides spp.). Serological evidence from livestock and the presence of at least one competent vector species of Culicoides suggests that transmission of BTV is possible and may have occurred in Kazakhstan. METHODS: We estimated the risk of transmission using a mathematical model of the reproduction number R0 for bluetongue. This model depends on livestock density and climatic factors which affect vector density. Data on climate and livestock numbers from the 2466 local communities were used. This, together with previously published model parameters, was used to estimate R0 for each month of the year. We plotted the results on isopleth maps of Kazakhstan using interpolation to smooth the irregular data. We also mapped the estimated proportion of the population requiring vaccination to prevent outbreaks of bluetongue. RESULTS: The results suggest that transmission of bluetongue in Kazakhstan is not possible in the winter from October to March. Assuming there are vector-competent species of Culicoides endemic in Kazakhstan, then low levels of risk first appear in the south of Kazakhstan in April before spreading north and intensifying, reaching maximum levels in northern Kazakhstan in July. The risk declined in September and had disappeared by October. CONCLUSION: These results should aid in surveillance efforts for the detection and control of bluetongue in Kazakhstan by indicating where and when outbreaks of bluetongue are most likely to occur. The results also indicate where vaccination efforts should be focussed to prevent outbreaks of disease.

Risk for African Swine Fever Introduction Into Kazakhstan.

African swine fever (ASF) is a disease of swine that is endemic to some African countries and that has rapidly spread since 2007 through many regions of Asia and Europe, becoming endemic in some areas of those continents. Since there is neither vaccine nor treatment for ASF, prevention is an important action to avoid the economic losses that this disease can impose on a country. Although the Republic of Kazakhstan has remained free from the disease, some of its neighbors have become ASF-infected, raising concerns about the potential introduction of the disease into the country. Here, we have identified clusters of districts in Kazakhstan at highest risk for ASF introduction. Questionnaires were administered, and districts were visited to collect and document, for the first time, at the district level, the distribution of swine operations and population in Kazakhstan. A snowball sampling approach was used to identify ASF experts worldwide, and a conjoint analysis model was used to elicit their opinion in relation to the extent at which relevant epidemiological factors influence the risk for ASF introduction into disease-free regions. The resulting model was validated using data from the Russian Federation and Mongolia. Finally, the validated model was used to rank and categorize Kazakhstani districts in terms of the risk for serving as the point of entry for ASF into the country, and clusters of districts at highest risk of introduction were identified using the normal model of the spatial scan statistic. Results here will help to allocate resources for surveillance and prevention activities aimed at early detecting a hypothetical ASF introduction into Kazakhstan, ultimately helping to protect the sanitary status of the country.

Comparison of spatiotemporal patterns of historic natural Anthrax outbreaks in Minnesota and Kazakhstan.

Disease spread in populations is a consequence of the interaction between host, pathogen, and environment, i.e. the epidemiological triad. Yet the influences of each triad component may vary dramatically for different settings. Comparison of environmental, demographic, socio-economic, and historical backgrounds may support tailoring site-specific control measures. Because of the long-term survival of Bacillus anthracis, Anthrax is a suitable example for studying the influence of triad components in different endemic settings. We compared the spatiotemporal patterns of historic animal Anthrax records in two endemic areas, located at northern latitudes in the western and eastern hemispheres. Our goal was to compare the spatiotemporal patterns in Anthrax progression, intensity, direction, and recurrence (disease hot spots), in relation to epidemiological factors and potential trigger events. Reported animal cases in Minnesota, USA (n = 289 cases between 1912 and 2014) and Kazakhstan (n = 3,997 cases between 1933 and 2014) were analyzed using the spatiotemporal directionality test and the spatial scan statistic. Over the last century Anthrax occurrence in Minnesota was sporadic whereas Kazakhstan experienced a long-term epidemic. Nevertheless, the seasonality was comparable between sites, with a peak in August. Declining number of cases at both sites was attributed to vaccination and control measures. The spatiotemporal directionality test detected a relative northeastern directionality in disease spread for long-term trends in Minnesota, whereas a southwestern directionality was observed in Kazakhstan. In terms of recurrence, the maximum timespans between cases at the same location were 55 and 60 years for Minnesota and Kazakhstan, respectively. Disease hotspots were recognized in both settings, with spatially overlapping clusters years apart. Distribution of the spatiotemporal cluster radii between study sites supported suggestion of site-specific control zones. Spatiotemporal patterns of Anthrax occurrence in both endemic regions were attributed to multiple potential trigger events including major river floods, changes in land use, agriculture, and susceptible livestock populations. Results here help to understand the long-term epidemiological dynamics of Anthrax while providing suggestions to the design and implementation of prevention and control programs, in endemic settings.

Spatio-temporal analysis and visualisation of the anthrax epidemic situation in livestock in Kazakhstan over the period 1933-2016.

An analysis of the anthrax epidemic situation among livestock animals in the Republic of Kazakhstan over the period 1933-2016 is presented. During this time, 4,064 anthrax outbreaks (mainly in cattle, small ruminants, pigs and horses) were recorded. They fall into five historical periods of increase and decrease in the annual anthrax incidence (1933-1953; 1954-1968; 1969-1983; 1984- 2001; and 2002-2016), which has been associated with changes in economic activity and veterinary surveillance. To evaluate the temporal trends of incidence variation for each of these time periods, the following methods were applied: i) spatio-temporal analysis using a space-time cube to assess the presence of hotspots (i.e., areas of outbreak clustering) and the trends of their emergence over time; and ii) a linear regression model that was used to evaluate the annual numbers of outbreaks as a function of time. The results show increasing trends during the first two periods followed by a decreasing trend up to now. The peak years of anthrax outbreaks occurred in 1965-1968 but outbreaks still continue with an average annual number of outbreaks of 1.2 (95% confidence interval: 0.6-1.8). The space-time analysis approach enabled visualisation of areas with statistically significant increasing or decreasing trends of outbreak clustering providing a practical opportunity to inform decision-makers and allowing the veterinary services to concentrate their efforts on monitoring the possible risk factors in the identified locations.

Rabies in Kazakhstan.

BACKGROUND: Rabies is a neglected zoonotic disease. There is a sparsity of data on this disease with regard to the incidence of human and animal disease in many low and middle income countries. Furthermore, rabies results in a large economic impact and a high human burden of disease. Kazakhstan is a large landlocked middle income country that gained independence from the Soviet Union in 1991 and is endemic for rabies. METHODOLOGY/PRINCIPAL FINDINGS: We used detailed public health and veterinary surveillance data from 2003 to 2015 to map where livestock rabies is occurring. We also estimate the economic impact and human burden of rabies. Livestock and canine rabies occurred over most of Kazakhstan, but there were regional variations in disease distribution. There were a mean of 7.1 officially recorded human fatalities due to rabies per year resulting in approximately 457 Disability Adjusted Life Years (DALYs). A mean of 64,289 individuals per annum underwent post exposure prophylaxis (PEP) which may have resulted in an additional 1140 DALYs annually. PEP is preventing at least 118 cases of human rabies each year or possibly as many as 1184 at an estimated cost of $1193 or $119 per DALY averted respectively. The estimated economic impact of rabies in Kazakhstan is $20.9 million per annum, with nearly half of this cost being attributed to the cost of PEP and the loss of income whilst being treated. A further $5.4 million per annum was estimated to be the life time loss of income for fatal cases. Animal vaccination programmes and animal control programmes also contributed substantially to the economic losses. The direct costs due to rabies fatalities of agricultural animals was relatively low. CONCLUSIONS/SIGNIFICANCE: This study demonstrates that in Kazakhstan there is a substantial economic cost and health impact of rabies. These costs could be reduced by modifying the vaccination programme that is now practised. The study also fills some data gaps on the epidemiology and economic effects of rabies in respect to Kazakhstan.

Zoning the territory of the Republic of Kazakhstan as to the risk of rabies among various categories of animals.

This paper presents the zoning of the territory of the Republic of Kazakhstan with respect to the risk of rabies outbreaks in domestic and wild animals considering environmental and climatic conditions. The national database of rabies outbreaks in Kazakhstan in the period 2003-2014 has been accessed in order to find which zones are consistently most exposed to the risk of rabies in animals. The database contains information on the cases in demes of farm livestock, domestic animals and wild animals. To identify the areas with the highest risk of outbreaks, we applied the maximum entropy modelling method. Designated outbreaks were used as input presence data, while the bioclim set of ecological and climatic variables, together with some geographic factors, were used as explanatory variables. The model demonstrated a high predictive ability. The area under the curve for farm livestock was 0.782, for domestic animals -0.859 and for wild animals - 0.809. Based on the model, the map of integral risk was designed by following four categories: negligible risk (disease-free or favourable zone), low risk (surveillance zone), medium risk (vaccination zone), and high risk (unfavourable zone). The map was produced to allow developing a set of preventive measures and is expected to contribute to a better distribution of supervisory efforts from the veterinary service of the country.

Revealing spatio-temporal patterns of rabies spread among various categories of animals in the Republic of Kazakhstan, 2010-2013.

This study estimated the basic reproductive ratio of rabies at the population level in wild animals (foxes), farm animals (cattle, camels, horses, sheep) and what we classified as domestic animals (cats, dogs) in the Republic of Kazakhstan (RK). It also aimed at forecasting the possible number of new outbreaks in case of emergence of the disease in new territories. We considered cases of rabies in animals in RK from 2010 to 2013, recorded by regional veterinary services. Statistically significant space-time clusters of outbreaks in three subpopulations were detected by means of Kulldorff Scan statistics. Theoretical curves were then fitted to epidemiological data within each cluster assuming exponential initial growth, which was followed up by calculation of the basic reproductive ratio R0. For farm animals, the value of R0 was 1.62 (1.11-2.26) and for wild animals 1.84 (1.08- 3.13), while it was close to 1 for domestic animals. Using the values obtained, an initial phase of possible epidemic was simulated in order to predict the expected number of secondary cases if the disease were introduced into a new area. The possible number of new cases for 20 weeks was estimated at 5 (1-16) for farm animals, 17 (1-113) for wild animals and about 1 in the category of domestic animals. These results have been used to produce set of recommendations for organising of preventive and contra-epizootic measures against rabies expected to be applied by state veterinarian services.