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Mapping the risks of the spread of Peste des Petits Ruminants in the Republic of Kazakhstan
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  • Sarsenbay Abdrakhmanov,
  • Yersyn Mukhanbetkaliyev,
  • Akhmetzhan Sultanov,
  • Gulzhan Yessembekova,
  • Sergey Borovikov,
  • Aidar Namet,
  • Abdykalyk Abishov,
  • Andres Perez,
  • Fedor Korennoy
Sarsenbay Abdrakhmanov
S Seifullin Kazakh Agro Technical University
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Yersyn Mukhanbetkaliyev
S Seifullin Kazakh Agro Technical University
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Akhmetzhan Sultanov
Kazakh Scientific Research Veterinary Institute Almaty Kazakhstan
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Gulzhan Yessembekova
S Seifullin Kazakh Agro Technical University
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Sergey Borovikov
S Seifullin Kazakh Agro Technical University
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Aidar Namet
Kazakh Scientific Research Veterinary Institute Almaty Kazakhstan
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Abdykalyk Abishov
LTD NPC DiaVak-ABN Almaty Kazakhstan
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Andres Perez
University of Minnesota Department of Veterinary Population Medicine
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Fedor Korennoy
Federal'nyi centr ohrany zdorov'a zivotnyh
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Abstract

Peste des petits ruminants (PPR) is a viral transboundary disease of 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 Generalized Linear 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 outbreaks 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 (R 2 = 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.

Peer review status:UNDER REVIEW

02 Jun 2021Submitted to Transboundary and Emerging Diseases
05 Jun 2021Assigned to Editor
05 Jun 2021Submission Checks Completed
08 Jun 2021Reviewer(s) Assigned