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TDK conference 2020

Epidemiological risk analysis model development about the geographical spread of African swine fever
Karasszon Ervin András - year 6
University of Veterinary Medicine Budapest, Center for Bioinformatics
Supervisor: Dr. Norbert Solymosi


The African Swine fever (ASF) causes severe damages in Hungary for the first time. Western Europe fought for more than thirty years against the disease with severe livestock restrictions and euthanasia successfully, but the second wave, coming up from the east, threatens the whole continent again. The role of the epidemiological risk analysis is fundamental, although not really conspicuous. The ASF Risk analysis Team in Hungary is working hard on this background scenario, to provide the best and newest database for the authorities, to overcome on this infectious disease.

The goal of our research was to develop a risk analysis model, which can indicate the risk of infection by the non-infected areas, using the main characteristics and direction of the ASF virus spreading. The project was in cooperation with the Hungarian ASF risk analysis team, and hopefully, the model will be able to provide information in many other countries, scenarios. The stages of the model are always better and better, due to the selection of the uncertain, estimated data, using only proven cases and data. The quantitative results can predict the necessity of preparations, restrictions, wildlife reduction, giving information, which can help us, to protect the precious domestic pig livestock.

The development of the model was performed in R environment, and we used spatial epidemiological modules, which made us able to visualize the „Hungarian game management units” (VGE), as the smallest units of risk analysis.

The first stage was developed before the first Hungarian ASF outbreak, in this model the VGE’s were organized by the distance from the Ukrainian and Romanian border, due to the high wild boar infections in these countries. After the first Hungarian outbreak in 21.04.2018. the diagnosed and proved cases were also included in the model, resulting a larger amount of endangered VGE in the country. The third model is using a discovery from the previous modelling, which highlights the role of the Tisza river in affecting the direction of the spread. Some research paper also proved the idea of ours, so the third model was upgraded by this extra sensitization. From all these models we checked the „worst-case scenario”, to produce the safest database for the country.

The model, at last, provides a map for the user, which shows the possibilities of the new outbreaks in all VGE’s in Hungary. Of course, the highest risk, the „human factor”, ergo the moving of animal products, cannot be modelled, because of the uncontrollable amount of data. Besides that, the experiences coming from the practical use, proves that the model is helpful and capable of providing useful data for the authorities. Because we all know, that „All models are wrong, but some are useful.” (George E. P. Box)

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