Spatiotemporal heterogeneity of social contact patterns related to infectious diseases in the Guangdong Province, China
Spatiotemporal heterogeneity of social contact patterns related to infectious diseases in the Guangdong Province, China
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中国广东省传染病相关社会接触模式的时空异质性
DOI：
10.1038/s41598-020-63383-z
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发表时间：
2020-04-15
影响因子：
4.6
通讯作者：
Ma, Wenjun
中科院分区：
文献类型：
--
作者：
Huang, Yulin;Cai, Xiaoshuang;Ma, Wenjun
与通过空气飞沫或密切接触传播的传染病相关的社会接触模式遵循特定的规则。了解这些过程可以提高疾病传播模型的准确性，允许将其集成到模型模拟中。本研究以中国珠江三角洲三个城市为研究对象，采用大规模人群调查方法，收集了冬夏两季的社会接触模式。共有5，818名参与者接受了面对面采访，并记录了35，542次联系。考虑到补充专业联系人，每人每天的平均联系次数为16.7次。每天发生、持续4小时以上、在家庭中发生的接触更有可能涉及身体接触。社交接触的季节性特征是异质的，例如与夏季相比，冬季的接触更有可能涉及身体接触。接触的空间特征相似。社会交往模式因年龄而异，但所有年龄段的人都与同龄人保持定期联系。综上所述，这些发现描述了中国广东省与感染相关的社会接触模式的时空分布。这些信息为传染病的数学模型提供了重要的参数。
The social contact patterns associated with the infectious disease transmitted by airborne droplets or close contact follow specific rules. Understanding these processes can improve the accuracy of disease transmission models, permitting their integration into model simulations. In this study, we performed a large-scale population-based survey to collect social contact patterns in three cities on the Pearl River Delta of China in winter and summer. A total of 5,818 participants were face-to-face interviewed and 35,542 contacts were recorded. The average number of contacts per person each day was 16.7 considering supplementary professional contacts (SPCs). Contacts that occurred on a daily basis, lasted more than 4 hours, and took place in households were more likely to involve physical contact. The seasonal characteristics of social contact were heterogeneous, such that contact in the winter was more likely to involve physical contact compared to summer months. The spatial characteristics of the contacts were similar. Social mixing patterns differed according to age, but all ages maintained regular contact with their peers. Taken together, these findings describe the spatiotemporal distribution of social contact patterns relevant to infections in the Guangdong Province of China. This information provides important parameters for mathematical models of infectious diseases.