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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.

Brucellosis is a widespread zoonotic disease considered as an emerging and re-emerging disease with a resulting threat of public health and animal health. Official reports document an animal incidence in Kazakhstan of about 0.6% per year, and the country still registers high number of human cases annually . The main objective of this paper was to evaluate the distribution and economic impact of brucellosis in Kazakhstan. We analysed human disease incidence data obtained from the Government Sanitary & Epidemiological Service with the aim to estimate the burden of disease in terms of disability-adjusted life years (DALYs). We also estimated the economic impact in terms of monetary losses. Additionally, we mapped the geographical distribution of the disease throughout Kazakhstan. In total, 1,334 human cases of brucellosis were registered in 2015 in Kazakhstan that resulted in 713 DALYs. Around US Dollar 21 million was spent on compensation for animals that had to be slaughtered due to brucellosis, and an additional US Dollar 24 million was spent on testing animals. Animal brucellosis and human brucellosis occur throughout the whole country, some trends of which are reviewed in this paper. We estimated the burden of the disease and explored possible explanation for high human incidence rates. This paper is the first to estimate the human burden of disease and the economic costs in Kazakhstan. Both of these are substantial.

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.

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.