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.
Bibliographical noteFunding Information:
The authors would like to thank the collaboration of the OIE reference centers in South Africa, Spain, the United Kingdom and a National Reference Center in the Russian Federation (Pokrov) that helped with the identification of experts, and the 11 experts that provided input for the conjoint analysis model. The authors are sincerely grateful to Dr. Eran Raizman, Senior Animal Health & Production Officer, Food and Agriculture Organization of the United Nation (FAO), Regional Office for Europe and Central Asia, for sharing the data on pig population distribution in Mongolia, and to Dr. Daniel Beltran-Alcrudo, Animal Health Officer, FAO, Hungary, Italy, for helping us with information regarding pig population and wild boar distribution in countries in Europe. Funding. This work had been supported in part by scientific researches of the Agro-Industrial Complex under a scientific-technical program Scientific basics of the veterinary well-being and food safety, the budgetary program #267, Research Project BR06249242.
© Copyright © 2021 Schettino, Abdrakhmanov, Beisembayev, Korennoy, Sultanov, Mukhanbetkaliyev, Kadyrov and Perez.
Copyright 2021 Elsevier B.V., All rights reserved.
- African swine fever
- conjoint analysis
- risk analysis
- risk map
PubMed: MeSH publication types
- Journal Article