Seasonal temperature variation influences climate suitability for dengue, chikungunya, and Zika transmission

Dengue, chikungunya, and Zika virus epidemics transmitted by Aedes aegypti mosquitoes have recently (re)emerged and spread throughout the Americas, Southeast Asia, the Pacific Islands, and elsewhere. Understanding how environmental conditions affect epidemic dynamics is critical for predicting and responding to the geographic and seasonal spread of disease. Specifically, we lack a mechanistic understanding of how seasonal variation in temperature affects epidemic magnitude and duration. Here, we develop a dynamic disease transmission model for dengue virus and Aedes aegypti mosquitoes that integrates mechanistic, empirically parameterized, and independently validated mosquito and virus trait thermal responses under seasonally varying temperatures. We examine the influence of seasonal temperature mean, variation, and temperature at the start of the epidemic on disease dynamics. We find that at both constant and seasonally varying temperatures, warmer temperatures at the start of epidemics promote more rapid epidemics due to faster burnout of the susceptible population. By contrast, intermediate temperatures (24–25°C) at epidemic onset produced the largest epidemics in both constant and seasonally varying temperature regimes. When seasonal temperature variation was low, 25–35°C annual average temperatures produced the largest epidemics, but this range shifted to cooler temperatures as seasonal temperature variation increased (analogous to previous results for diurnal temperature variation). Tropical and sub-tropical cities such as Rio de Janeiro, Fortaleza, and Salvador, Brazil; Cali, Cartagena, and Barranquilla, Colombia; Delhi, India; Guangzhou, China; and Manila, Philippines have mean annual temperatures and seasonal temperature ranges that produced the largest epidemics. However, more temperate cities like Shanghai, China had high epidemic suitability because large seasonal variation offset moderate annual average temperatures. By accounting for seasonal variation in temperature, the model provides a baseline for mechanistically understanding environmental suitability for virus transmission by Aedes aegypti. Overlaying the impact of human activities and socioeconomic factors onto this mechanistic temperature-dependent framework is critical for understanding likelihood and magnitude of outbreaks.登革热（Dengue）、基孔肯雅热（chikungunya）与寨卡病毒（Zika virus）疫情由埃及伊蚊（Aedes aegypti）传播，近年再度出现并在美洲、东南亚、太平洋岛屿及其他地区广泛扩散。明确环境条件对疫情动态的影响，对于预测疾病的地理与季节传播模式并制定针对性应对策略至关重要，但目前我们仍缺乏关于温度季节变化如何作用于疫情规模与持续时间的机制性认知。 本研究构建了针对登革病毒与埃及伊蚊的动态疾病传播模型，整合了季节变化温度下的机制性、经验参数化且经独立验证的蚊媒与病毒性状热响应特征。研究探讨了季节温度均值、温度波动幅度以及疫情暴发初始温度对疾病动态的影响。 研究结果显示：无论在恒定温度还是季节变化温度场景下，疫情暴发初始阶段的更高温度会因易感人群快速耗尽，推动疫情更快发展；与之相对，疫情初始时的中等温度（24–25°C）在恒定及季节变化温度环境中，均能引发规模最大的疫情。当季节温度波动较小时，年平均温度处于25–35°C区间时疫情规模达到峰值，但随着季节温度波动加剧，该最优温度区间会向低温方向偏移——这与此前关于昼夜温度波动的研究结论高度相似。 热带及亚热带城市如巴西里约热内卢、福塔莱萨与萨尔瓦多，哥伦比亚卡利、卡塔赫纳与巴兰基亚，印度德里，中国广州以及菲律宾马尼拉，其年平均温度与季节温度范围恰好处于可引发最大规模疫情的区间内。而像中国上海这类温带城市却具备较高的疫情暴发适宜性，因为显著的季节温度波动抵消了中等年平均温度的限制。 本模型通过纳入温度季节变化，为从机制层面理解埃及伊蚊介导的病毒传播环境适宜性提供了基准框架。将人类活动与社会经济因素的影响叠加至这一基于温度的机制性框架中，对于精准研判疫情暴发的可能性与规模至关重要。