Department of Statistics, University of Oxford, Oxford, United Kingdom.
Centre for Emerging, Endemic and Exotic Diseases, Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, United Kingdom.
Epidemics. 2022 Sep;40:100622. doi: 10.1016/j.epidem.2022.100622. Epub 2022 Aug 13.
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.
非洲猪瘟(ASF)由非洲猪瘟病毒(ASFV)引起,对家猪和野猪(Sus scrofa)具有高度致病性,死亡率高达 100%。最近欧洲发生的 ASF 疫情对经济造成了严重影响,并对全球粮食安全构成威胁。不幸的是,目前尚无针对 ASFV 的有效治疗或疫苗,这限制了现有的疾病管理策略。数学模型可以帮助我们深入了解传染病的动态,并评估疾病管理策略的效果。由法国国家农业、食品和环境研究院组织的 ASF 挑战赛旨在扩展 ASF 传播模型的开发,以便及时为决策者提供信息。在这里,我们展示了我们团队在挑战赛期间开发的模型和相关预测。我们开发了一个随机模型,将野猪和家猪之间的传播结合在一起,并根据描述疫情进展的不同阶段的合成数据进行了校准。然后,该模型用于生成描述在各种疾病管理情景下疫情可能的时间演变的前瞻性预测。尽管实施了干预措施,但长期预测仍预测 ASFV 将在野猪中持续存在,因此家猪将反复爆发疫情。一个关键发现是,重要的是要考虑评估不同措施的时间尺度:短期效果有限的干预措施可能会带来长期的实质性好处。我们的模型存在一些局限性,部分原因是它是实时开发的。尽管如此,它可以帮助我们了解 ASF 疫情的发展情况和疾病管理策略的效果,如果该病毒继续在欧洲传播。