针对环境持久性病原体的随机剂量-反应框架
A stochastic dose-response framework for environmentally persistent pathogens
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中文总结 AI 辅助
本研究开发了结合宿主感染动态与环境病原体储库的随机剂量-反应框架，将其应用于蛇真菌病，揭示了剂量-反应、随机性和季节性对环境持久性病原体暴发动态的影响。
中文摘要 AI 辅助
由环境持久性病原体引发的传染病会对宿主种群产生强烈影响，其传播不仅通过宿主间的直接接触，还可通过对受污染环境的间接暴露实现。在部分系统中，即便感染宿主数量较少，环境储库也能维持暴露水平；而依赖环境传播途径也可能增加病原体灭绝风险。感染风险可能同时取决于病原体剂量和暴露时间。因此，理解剂量-反应、随机性以及宿主易感性或接触率的季节性变化如何影响病原体入侵和持续存在，仍是环境传播疾病系统面临的重要挑战。为解决这一问题，我们开发了一种随机剂量-反应框架，将宿主感染动态与明确的环境病原体储库相结合。传播通过与感染宿主的直接接触和间接环境暴露两种途径发生，感染概率由剂量-反应函数决定。我们聚焦于随机连续时间马尔可夫链公式，并利用分支过程近似估计当感染宿主或环境病原体载量较低时的疾病灭绝概率。我们将该框架扩展为包含宿主易感性、环境接触和宿主-宿主接触的季节性变化。作为案例研究，我们将该模型应用于蛇真菌病。数值模拟显示，剂量-反应会影响流行的起飞和感染水平，而季节性会创造高、低灭绝风险窗口。这些灭绝风险强烈依赖于季节性周期内引入的途径和时间。这些结果结合全局敏感性分析，阐明了随机性、非线性剂量-反应和季节性时间如何塑造环境持久性病原体的暴发动态。
英文摘要
Infectious diseases caused by environmentally persistent pathogens can strongly affect host populations as transmission occurs not only through direct host-host contact but also via indirect exposure to contaminated environments. While in some systems environmental reservoirs help sustain exposure even when infected host numbers are low, reliance on environmental transmission pathway may also increase pathogen extinction risk. Infection risk may depend on both pathogen dose and timing of exposure. Thus, understanding how dose-response, stochasticity, and seasonal changes in host susceptibility or contact rates shape pathogen invasion and persistence remains an important challenge for environmentally transmitted disease systems. To address this, we develop a stochastic dose-response framework that integrates host infection dynamics with an explicit environmental pathogen reservoir. Transmission occurs through both direct contact with infectious hosts and indirect environmental exposure, with infection probability governed by dose-response functions. We focus on stochastic continuous-time Markov chain formulation and use branching process approximation to estimate disease extinction probabilities when infected hosts or environmental pathogen loads are low. We extend the framework to include seasonality in host susceptibility, environmental contact, and host-host contact. As a case study, we apply the model to snake fungal disease. Numerical simulations show that dose-response influences epidemic takeoff and infection levels, while seasonality creates windows of high and low extinction risk. These extinction risks depend strongly on the route and timing of introduction within the seasonal cycle. These results, coupled with global sensitivity analysis, illustrate how stochasticity, nonlinear dose-response, and seasonal timing shape outbreak dynamics for environmentally persistent pathogens.
