量化传染病流行风险:季节性病原体的实用方法

Alexander Richard Kaye, Giorgio Guzzetta, Michael Tildesley, Robin Thompson
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引用次数: 0

摘要

对于许多传染病来说,爆发的风险是随季节变化的。如果病原体通常不出现在宿主人群中,那么公共卫生政策的一个关键问题就是病原体的到来是否会引发本地传播,这取决于病原体到来的季节。要解决这个问题,可以通过估算重大疫情爆发的概率(传入病例引发持续的本地传播的概率)。对于季节性病原体,有一种基于分支过程数学理论的标准方法来推断这种概率(包括计算病例流行风险;CER)。根据该理论,可以估算出病原体灭绝的概率,但忽略易感个体的减少。然后,CER 为 1 减去灭绝概率。然而,正如我们所展示的,如果一年中长期(如冬季或夏季)不能发生传播,病原体将不可避免地灭绝,从而导致 CER 为零,即使季节性爆发也会发生。因此,在这些情况下,CER 无法提供信息。因此,我们设计了另一种方法来推断季节性病原体的爆发风险(包括计算阈值流行风险;TER)。估算阈值流行风险涉及计算引入病例引发局部疫情的概率,在疫情消亡前,感染人数超过阈值。对于简单的季节性流行病模型,如随机的 "易感-传染-清除 "模型,TER 可以通过数值计算得出(无需模型模拟)。对于更复杂的模型,如随机宿主-媒介模型,则可以通过模型模拟来估算 TER。我们以意大利北部的基孔肯雅病毒为案例,展示了我们的方法的应用。在这种情况下,传播最有可能发生在夏季,因为此时的环境条件会促进病媒的大量繁殖。我们的研究表明,TER 比 CER 能提供更有用的疫情风险评估,从而能对季节性病原体进行切实可行的风险量化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying infectious disease epidemic risks: A practical approach for seasonal pathogens
For many infectious diseases, the risk of outbreaks varies seasonally. If a pathogen is usually absent from a host population, a key public health policy question is whether the pathogen's arrival will initiate local transmission, which depends on the season in which arrival occurs. This question can be addressed by estimating the probability of a major outbreak (the probability that introduced cases will initiate sustained local transmission). A standard approach for inferring this probability exists for seasonal pathogens (involving calculating the Case Epidemic Risk; CER) based on the mathematical theory of branching processes. Under that theory, the probability of pathogen extinction is estimated, neglecting depletion of susceptible individuals. The CER is then one minus the extinction probability. However, as we show, if transmission cannot occur for long periods of the year (e.g., over winter or over summer), the pathogen will inevitably go extinct, leading to a CER of zero even if seasonal outbreaks can occur. This renders the CER uninformative in those scenarios. We therefore devise an alternative approach for inferring outbreak risks for seasonal pathogens (involving calculating the Threshold Epidemic Risk; TER). Estimation of the TER involves calculating the probability that introduced cases will initiate a local outbreak in which a threshold number of infections is exceeded before outbreak extinction. For simple seasonal epidemic models, such as the stochastic Susceptible-Infectious-Removed model, the TER can be calculated numerically (without model simulations). For more complex models, such as stochastic host-vector models, the TER can be estimated using model simulations. We demonstrate the application of our approach by considering Chikungunya virus in northern Italy as a case study. In that context, transmission is most likely in summer, when environmental conditions promote vector abundance. We show that the TER provides more useful assessments of outbreak risks than the CER, enabling practically relevant risk quantification for seasonal pathogens.
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