Jolly岛上高致病性禽流感防控与家禽补栏的随机空间集合种群模型
Stochastic Spatial Metapopulation Modelling of HPAI Control and Poultry Restocking on Jolly Island
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中文总结 AI 辅助
本研究构建基于随机空间SEIR的集合种群模型，模拟Jolly岛HPAI暴发，评估防控与补栏策略，发现针对性措施可降低疫情负担与反弹风险。
中文摘要 AI 辅助
高致病性禽流感（HPAI）暴发期间，需要在活跃传播阶段实施快速控制，并对清空养殖场后的安全补栏做出循证决策。我们针对虚构的Jolly岛上的模拟HPAI暴发，开发了一种基于随机空间SEIR的集合种群模型。养殖场被分为“肉鸡2型”“有机鸭”或“其他”生产系统。该模型纳入了本地传播、环境传播、媒介传播和距离依赖型传播，同时包含反应性扑杀和预防性扑杀、生产特定的隔离措施，以及基于容量的补栏方式。模拟的疫情在地理上集中，且不同生产类别间差异显著。预防性扑杀将平均累计负担从16362.7个感染养殖场天降至13631.9个，总体降幅为16.7%；更早的隔离措施大幅降低了疫情规模，而更强的环境传播则提升了疫情峰值。随着疫情接近平息，补栏风险下降。在模型假设下，2026年5月24日是首个满足预设反弹概率阈值0.20的候选日期；若在2026年3月15日补栏，所有 tested 补栏比例均未达到该标准。与基于基准种群的补栏相比，基于容量的补栏使累计负担降低8.45%，反弹概率从0.780降至0.533。这些发现证明了在单一建模框架内整合疫情防控与疫情后恢复的价值，及时的隔离措施、有针对性的预防性扑杀以及分阶段的基于容量的补栏，可同时降低疫情负担和反弹风险，尽管运营决策还应纳入监测、生物安全、经济考量和监管要求。
英文摘要
Highly pathogenic avian influenza (HPAI) outbreaks require rapid control during active transmission and evidence-based decisions on the safe restocking of depopulated farms. We developed a stochastic spatial SEIR-based metapopulation model for a synthetic HPAI outbreak on the fictional Jolly Island. Farms were classified as `Broiler-2', `organic duck', or `Other' production systems. The model incorporated local, environmental, movement-mediated, and distance-dependent transmission, together with reactive and preventive culling, production-specific confinement, and capacity-based restocking. The simulated epidemic was geographically concentrated and differed substantially among production classes. Preventive culling reduced mean cumulative burden from 16,362.7 to 13,631.9 infectious-farm-days, with an overall reduction of 16.7\%. Earlier confinement substantially reduced epidemic magnitude, while stronger environmental transmission increased the epidemic peak. Restocking risk declined as the epidemic approached resolution. Under the model assumptions, 24 May 2026 was the first candidate date satisfying the predefined rebound-probability threshold of 0.20. For restocking on 15 March 2026, none of the tested restocking fractions met this criterion. Capacity-based restocking reduced cumulative burden by 8.45\% and rebound probability from 0.780 to 0.533, compared with restocking relative to the baseline population. These findings demonstrate the value of integrating epidemic control and post-outbreak recovery within a single modelling framework. Timely confinement, targeted preventive culling, and phased capacity-based restocking may reduce both epidemic burden and resurgence risk, although operational decisions should also incorporate surveillance, biosecurity, economic considerations, and regulatory requirements.
