TY - JOUR
T1 - Social contact patterns and their impact on the transmission of respiratory pathogens in rural China
AU - Liang, Yuxia
AU - You, Qian
AU - Wang, Qianli
AU - Yang, Xiaohong
AU - Zhong, Guangjie
AU - Dong, Kaige
AU - Zhao, Zeyao
AU - Liu, Nuolan
AU - Yan, Xuemei
AU - Lu, Wanying
AU - Peng, Cheng
AU - Zhou, Jiaxin
AU - Lin, Jiqun
AU - Litvinova, Maria
AU - Jit, Mark
AU - Ajelli, Marco
AU - Yu, Hongjie
AU - Zhang, Juanjuan
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2025/6
Y1 - 2025/6
N2 - Introduction: Social contact patterns significantly influence the transmission dynamics of respiratory pathogens. Previous surveys have quantified human social contact patterns, yielding heterogeneous results across different locations. However, significant gaps remain in understanding social contact patterns in rural areas of China. Methods: We conducted a pioneering study to quantify social contact patterns in Anhua County, Hunan Province, China, from June to October 2021, when there were minimal coronavirus disease-related restrictions in the area. Additionally, we simulated the epidemics under different assumptions regarding the relative transmission risks of various contact types (e.g., indoor versus outdoor, and physical versus non-physical). Results: Participants reported an average of 12.0 contacts per day (95% confidence interval: 11.3–12.6), with a significantly higher number of indoor contacts compared to outdoor contacts. The number of contacts was associated with various socio-demographic characteristics, including age, education level, income, household size, and travel patterns. Contact patterns were assortative by age and varied based on the type of contact (e.g., physical versus non-physical). The reproduction number, daily incidence, and infection attack rate of simulated epidemics were remarkably stable. Discussion: We found many intergenerational households and contacts that pose challenges in preventing and controlling infections among the elderly in rural China. Our study also underscores the importance of integrating various types of contact pattern data into epidemiological models and provides guidance to public health authorities and other major stakeholders in preparing and responding to infectious disease threats in rural China.
AB - Introduction: Social contact patterns significantly influence the transmission dynamics of respiratory pathogens. Previous surveys have quantified human social contact patterns, yielding heterogeneous results across different locations. However, significant gaps remain in understanding social contact patterns in rural areas of China. Methods: We conducted a pioneering study to quantify social contact patterns in Anhua County, Hunan Province, China, from June to October 2021, when there were minimal coronavirus disease-related restrictions in the area. Additionally, we simulated the epidemics under different assumptions regarding the relative transmission risks of various contact types (e.g., indoor versus outdoor, and physical versus non-physical). Results: Participants reported an average of 12.0 contacts per day (95% confidence interval: 11.3–12.6), with a significantly higher number of indoor contacts compared to outdoor contacts. The number of contacts was associated with various socio-demographic characteristics, including age, education level, income, household size, and travel patterns. Contact patterns were assortative by age and varied based on the type of contact (e.g., physical versus non-physical). The reproduction number, daily incidence, and infection attack rate of simulated epidemics were remarkably stable. Discussion: We found many intergenerational households and contacts that pose challenges in preventing and controlling infections among the elderly in rural China. Our study also underscores the importance of integrating various types of contact pattern data into epidemiological models and provides guidance to public health authorities and other major stakeholders in preparing and responding to infectious disease threats in rural China.
KW - Infectious disease
KW - Mathematical modeling
KW - Respiratory pathogens
KW - Rural areas
KW - Social contact
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U2 - 10.1016/j.idm.2024.12.006
DO - 10.1016/j.idm.2024.12.006
M3 - Article
AN - SCOPUS:85213286475
SN - 2468-2152
VL - 10
SP - 439
EP - 452
JO - Infectious Disease Modelling
JF - Infectious Disease Modelling
IS - 2
ER -