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Abstract：
BACKGROUND: Human contact patterns are a key determinant driving the spread of respiratory infectious diseases. However, the relationship between contact patterns and seasonality as well as their possible association with the seasonality of respiratory diseases is yet to be clarified.
METHODS: We investigated the association between temperature and human contact patterns using data collected through a cross-sectional diary-based contact survey in Shanghai, China, between December 24, 2017, and May 30, 2018. We then developed a compartmental model of influenza transmission informed by the derived seasonal trends in the number of contacts and validated it against A(H1N1)pdm09 influenza data collected in Shanghai during the same period.
RESULTS: We identified a significant inverse relationship between the number of contacts and the seasonal temperature trend defined as a spline interpolation of temperature data (p = 0.003). We estimated an average of 16.4 (95% PrI: 15.1-17.5) contacts per day in December 2017 that increased to an average of 17.6 contacts (95% PrI: 16.5-19.3) in January 2018 and then declined to an average of 10.3 (95% PrI: 9.4-10.8) in May 2018. Estimates of influenza incidence obtained by the compartmental model comply with the observed epidemiological data. The reproduction number was estimated to increase from 1.24 (95% CI: 1.21-1.27) in December to a peak of 1.34 (95% CI: 1.31-1.37) in January. The estimated median infection attack rate at the end of the season was 27.4% (95% CI: 23.7-30.5%).
CONCLUSIONS: Our findings support a relationship between temperature and contact patterns, which can contribute to deepen the understanding of the relationship between social interactions and the epidemiology of respiratory infectious diseases.
METHODS: We investigated the association between temperature and human contact patterns using data collected through a cross-sectional diary-based contact survey in Shanghai, China, between December 24, 2017, and May 30, 2018. We then developed a compartmental model of influenza transmission informed by the derived seasonal trends in the number of contacts and validated it against A(H1N1)pdm09 influenza data collected in Shanghai during the same period.
RESULTS: We identified a significant inverse relationship between the number of contacts and the seasonal temperature trend defined as a spline interpolation of temperature data (p = 0.003). We estimated an average of 16.4 (95% PrI: 15.1-17.5) contacts per day in December 2017 that increased to an average of 17.6 contacts (95% PrI: 16.5-19.3) in January 2018 and then declined to an average of 10.3 (95% PrI: 9.4-10.8) in May 2018. Estimates of influenza incidence obtained by the compartmental model comply with the observed epidemiological data. The reproduction number was estimated to increase from 1.24 (95% CI: 1.21-1.27) in December to a peak of 1.34 (95% CI: 1.31-1.37) in January. The estimated median infection attack rate at the end of the season was 27.4% (95% CI: 23.7-30.5%).
CONCLUSIONS: Our findings support a relationship between temperature and contact patterns, which can contribute to deepen the understanding of the relationship between social interactions and the epidemiology of respiratory infectious diseases.
摘要：
背景：人类接触模式是驱动呼吸道传染病传播的关键决定因素。然而,接触模式与季节性之间的关系以及它们与呼吸系统疾病季节性之间可能的关联尚待澄清。
方法：我们使用通过在上海进行的基于横断面日记的接触调查收集的数据，调查了温度与人类接触模式之间的关联，中国,2017年12月24日至2018年5月30日。然后，我们根据得出的接触人数的季节性趋势开发了流感传播的隔室模型，并根据同期在上海收集的A（H1N1）pdm09流感数据进行了验证。
结果：我们确定了接触数量与季节性温度趋势之间的显着反比关系，该趋势定义为温度数据的样条插值（p=0.003）。我们估计2017年12月平均每天有16.4次（95％PrI：15.1-17.5）接触，2018年1月增加到平均17.6次（95％PrI：16.5-19.3），然后在2018年5月下降到平均10.3次（95％PrI：9.4-10.8）。通过隔室模型获得的流感发病率估计符合观察到的流行病学数据。繁殖数量估计从12月的1.24（95％CI：1.21-1.27）增加到1月的1.34（95％CI：1.31-1.37）的峰值。季节结束时估计的中位感染发生率为27.4％（95％CI：23.7-30.5％）。
结论：我们的发现支持温度和接触模式之间的关系，有助于加深对社会交往与呼吸道传染病流行病学关系的认识。
方法：我们使用通过在上海进行的基于横断面日记的接触调查收集的数据，调查了温度与人类接触模式之间的关联，中国,2017年12月24日至2018年5月30日。然后，我们根据得出的接触人数的季节性趋势开发了流感传播的隔室模型，并根据同期在上海收集的A（H1N1）pdm09流感数据进行了验证。
结果：我们确定了接触数量与季节性温度趋势之间的显着反比关系，该趋势定义为温度数据的样条插值（p=0.003）。我们估计2017年12月平均每天有16.4次（95％PrI：15.1-17.5）接触，2018年1月增加到平均17.6次（95％PrI：16.5-19.3），然后在2018年5月下降到平均10.3次（95％PrI：9.4-10.8）。通过隔室模型获得的流感发病率估计符合观察到的流行病学数据。繁殖数量估计从12月的1.24（95％CI：1.21-1.27）增加到1月的1.34（95％CI：1.31-1.37）的峰值。季节结束时估计的中位感染发生率为27.4％（95％CI：23.7-30.5％）。
结论：我们的发现支持温度和接触模式之间的关系，有助于加深对社会交往与呼吸道传染病流行病学关系的认识。
