Laboratoire de Mathématiques Jean Leray, Université de Nantes, Nantes, France.
CEFE, CNRS, Univ Montpellier, Univ Paul Valéry Montpellier 3, EPHE, IRD, 34293 Montpellier Cedex 5, France.
PLoS Comput Biol. 2020 Jul 6;16(7):e1007954. doi: 10.1371/journal.pcbi.1007954. eCollection 2020 Jul.
Many infectious diseases exhibit seasonal dynamics driven by periodic fluctuations of the environment. Predicting the risk of pathogen emergence at different points in time is key for the development of effective public health strategies. Here we study the impact of seasonality on the probability of emergence of directly transmitted pathogens under different epidemiological scenarios. We show that when the period of the fluctuation is large relative to the duration of the infection, the probability of emergence varies dramatically with the time at which the pathogen is introduced in the host population. In particular, we identify a new effect of seasonality (the winter is coming effect) where the probability of emergence is vanishingly small even though pathogen transmission is high. We use this theoretical framework to compare the impact of different preventive control strategies on the average probability of emergence. We show that, when pathogen eradication is not attainable, the optimal strategy is to act intensively in a narrow time interval. Interestingly, the optimal control strategy is not always the strategy minimizing R0, the basic reproduction ratio of the pathogen. This theoretical framework is extended to study the probability of emergence of vector borne diseases in seasonal environments and we show how it can be used to improve risk maps of Zika virus emergence.
许多传染病表现出季节性动态，这是由环境的周期性波动驱动的。预测不同时间点病原体出现的风险对于制定有效的公共卫生策略至关重要。在这里，我们研究了季节性对不同流行病学情况下直接传播病原体出现概率的影响。我们表明，当波动的周期相对于感染的持续时间较大时，病原体在宿主群体中引入的时间会极大地影响出现的概率。特别是，我们确定了季节性的一个新效应（冬天来了效应），即使病原体传播率很高，出现的概率也几乎为零。我们使用这个理论框架来比较不同预防控制策略对平均出现概率的影响。我们表明，当无法根除病原体时，最佳策略是在一个狭窄的时间间隔内集中精力行动。有趣的是，最佳控制策略并不总是最小化病原体基本繁殖率 R0 的策略。这个理论框架被扩展到研究季节性环境中媒介传播疾病的出现概率，我们展示了如何利用它来改进寨卡病毒出现的风险图。
