IRD (Institut de Recherche pour le Développement), 32 avenue Henri Varagnat, 93143, Bondy, France.
Bull Math Biol. 2009 Nov;71(8):1954-66. doi: 10.1007/s11538-009-9433-7. Epub 2009 May 28.
We first study an SIR system of differential equations with periodic coefficients describing an epidemic in a seasonal environment. Unlike in a constant environment, the final epidemic size may not be an increasing function of the basic reproduction number R(0) or of the initial fraction of infected people. Moreover, large epidemics can happen even if R(0) < 1. But like in a constant environment, the final epidemic size tends to 0 when R(0) < 1 and the initial fraction of infected people tends to 0. When R(0) > 1, the final epidemic size is bigger than the fraction 1 - 1/R(0) of the initially nonimmune population. In summary, the basic reproduction number R(0) keeps its classical threshold property but many other properties are no longer true in a seasonal environment. These theoretical results should be kept in mind when analyzing data for emerging vector-borne diseases (West-Nile, dengue, chikungunya) or air-borne diseases (SARS, pandemic influenza); all these diseases being influenced by seasonality.
我们首先研究了一个带有周期系数的 SIR 微分方程组,该方程组描述了季节性环境中的传染病。与恒定环境不同,最终的传染病规模可能不是基本再生数 R(0)或初始感染人数比例的增函数。此外,即使 R(0) < 1,也可能发生大规模疫情。但是,与恒定环境一样,当 R(0) < 1 时,最终的传染病规模趋于 0,并且初始感染人数比例趋于 0。当 R(0) > 1 时,最终的传染病规模大于初始非免疫人群的比例 1 - 1/R(0)。总之,基本再生数 R(0)保持了其经典的阈值特性,但在季节性环境中,许多其他特性不再成立。在分析新兴的媒介传播疾病(西尼罗河病毒、登革热、基孔肯雅热)或空气传播疾病(SARS、大流行性流感)的数据时,应牢记这些理论结果;所有这些疾病都受到季节性的影响。