Stochastic modelling of African swine fever in wild boar and domestic pigs: Epidemic forecasting and comparison of disease management strategies
African swine fever (ASF), caused by the African swine fever virus (ASFV), is highly virulent in domestic pigs and wild boar (Sus scrofa), causing up to 100% mortality. The recent epidemic of ASF in Europe has had a serious economic impact and poses a threat to global food security. Unfortunately, t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | Epidemics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1755436522000639 |
| _version_ | 1818055855068676096 |
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| author | Emmanuelle A. Dankwa Sébastien Lambert Sarah Hayes Robin N. Thompson Christl A. Donnelly |
| author_facet | Emmanuelle A. Dankwa Sébastien Lambert Sarah Hayes Robin N. Thompson Christl A. Donnelly |
| author_sort | Emmanuelle A. Dankwa |
| collection | DOAJ |
| description | African swine fever (ASF), caused by the African swine fever virus (ASFV), is highly virulent in domestic pigs and wild boar (Sus scrofa), causing up to 100% mortality. The recent epidemic of ASF in Europe has had a serious economic impact and poses a threat to global food security. Unfortunately, there is no effective treatment or vaccine against ASFV, limiting the available disease management strategies. Mathematical models allow us to further our understanding of infectious disease dynamics and evaluate the efficacy of disease management strategies. The ASF Challenge, organised by the French National Research Institute for Agriculture, Food, and the Environment, aimed to expand the development of ASF transmission models to inform policy makers in a timely manner. Here, we present the model and associated projections produced by our team during the challenge. We developed a stochastic model combining transmission between wild boar and domestic pigs, which was calibrated to synthetic data corresponding to different phases describing the epidemic progression. The model was then used to produce forward projections describing the likely temporal evolution of the epidemic under various disease management scenarios. Despite the interventions implemented, long-term projections forecasted persistence of ASFV in wild boar, and hence repeated outbreaks in domestic pigs. A key finding was that it is important to consider the timescale over which different measures are evaluated: interventions that have only limited effectiveness in the short term may yield substantial long-term benefits. Our model has several limitations, partly because it was developed in real-time. Nonetheless, it can inform understanding of the likely development of ASF epidemics and the efficacy of disease management strategies, should the virus continue its spread in Europe. |
| first_indexed | 2024-12-10T12:19:34Z |
| format | Article |
| id | doaj.art-ad5ee9e0575e40f389a7936bf62347d8 |
| institution | Directory Open Access Journal |
| issn | 1755-4365 |
| language | English |
| last_indexed | 2024-12-10T12:19:34Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Epidemics |
| spelling | doaj.art-ad5ee9e0575e40f389a7936bf62347d82022-12-22T01:49:07ZengElsevierEpidemics1755-43652022-09-0140100622Stochastic modelling of African swine fever in wild boar and domestic pigs: Epidemic forecasting and comparison of disease management strategiesEmmanuelle A. Dankwa0Sébastien Lambert1Sarah Hayes2Robin N. Thompson3Christl A. Donnelly4Department of Statistics, University of Oxford, Oxford, United KingdomCentre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, United KingdomDepartment of Infectious Disease Epidemiology, Faculty of Medicine, School of Public Health, Imperial College London, United KingdomMathematics Institute, University of Warwick, Coventry, United Kingdom; Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United KingdomDepartment of Statistics, University of Oxford, Oxford, United Kingdom; Department of Infectious Disease Epidemiology, Faculty of Medicine, School of Public Health, Imperial College London, United Kingdom; Correspondence to: Department of Statistics, University of Oxford, 24–29 St Giles', Oxford OX1 3LB, United Kingdom.African swine fever (ASF), caused by the African swine fever virus (ASFV), is highly virulent in domestic pigs and wild boar (Sus scrofa), causing up to 100% mortality. The recent epidemic of ASF in Europe has had a serious economic impact and poses a threat to global food security. Unfortunately, there is no effective treatment or vaccine against ASFV, limiting the available disease management strategies. Mathematical models allow us to further our understanding of infectious disease dynamics and evaluate the efficacy of disease management strategies. The ASF Challenge, organised by the French National Research Institute for Agriculture, Food, and the Environment, aimed to expand the development of ASF transmission models to inform policy makers in a timely manner. Here, we present the model and associated projections produced by our team during the challenge. We developed a stochastic model combining transmission between wild boar and domestic pigs, which was calibrated to synthetic data corresponding to different phases describing the epidemic progression. The model was then used to produce forward projections describing the likely temporal evolution of the epidemic under various disease management scenarios. Despite the interventions implemented, long-term projections forecasted persistence of ASFV in wild boar, and hence repeated outbreaks in domestic pigs. A key finding was that it is important to consider the timescale over which different measures are evaluated: interventions that have only limited effectiveness in the short term may yield substantial long-term benefits. Our model has several limitations, partly because it was developed in real-time. Nonetheless, it can inform understanding of the likely development of ASF epidemics and the efficacy of disease management strategies, should the virus continue its spread in Europe.http://www.sciencedirect.com/science/article/pii/S1755436522000639Mathematical modellingAfrican swine fever virusWildlife-livestock interfaceSpatial modelReal-time analysis |
| spellingShingle | Emmanuelle A. Dankwa Sébastien Lambert Sarah Hayes Robin N. Thompson Christl A. Donnelly Stochastic modelling of African swine fever in wild boar and domestic pigs: Epidemic forecasting and comparison of disease management strategies Epidemics Mathematical modelling African swine fever virus Wildlife-livestock interface Spatial model Real-time analysis |
| title | Stochastic modelling of African swine fever in wild boar and domestic pigs: Epidemic forecasting and comparison of disease management strategies |
| title_full | Stochastic modelling of African swine fever in wild boar and domestic pigs: Epidemic forecasting and comparison of disease management strategies |
| title_fullStr | Stochastic modelling of African swine fever in wild boar and domestic pigs: Epidemic forecasting and comparison of disease management strategies |
| title_full_unstemmed | Stochastic modelling of African swine fever in wild boar and domestic pigs: Epidemic forecasting and comparison of disease management strategies |
| title_short | Stochastic modelling of African swine fever in wild boar and domestic pigs: Epidemic forecasting and comparison of disease management strategies |
| title_sort | stochastic modelling of african swine fever in wild boar and domestic pigs epidemic forecasting and comparison of disease management strategies |
| topic | Mathematical modelling African swine fever virus Wildlife-livestock interface Spatial model Real-time analysis |
| url | http://www.sciencedirect.com/science/article/pii/S1755436522000639 |
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