Social contact patterns relevant for infectious disease transmission in Cambodia
Issued Date
2023-12-01
Resource Type
eISSN
20452322
Scopus ID
2-s2.0-85151777919
Pubmed ID
37015945
Journal Title
Scientific Reports
Volume
13
Issue
1
Rights Holder(s)
SCOPUS
Bibliographic Citation
Scientific Reports Vol.13 No.1 (2023)
Suggested Citation
Leung W.T.M., Meeyai A., Holt H.R., Khieu B., Chhay T., Seng S., Pok S., Chiv P., Drake T., Rudge J.W. Social contact patterns relevant for infectious disease transmission in Cambodia. Scientific Reports Vol.13 No.1 (2023). doi:10.1038/s41598-023-31485-z Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/82109
Title
Social contact patterns relevant for infectious disease transmission in Cambodia
Other Contributor(s)
Abstract
Social mixing patterns are key determinants of infectious disease transmission. Mathematical models parameterised with empirical data from contact pattern surveys have played an important role in understanding epidemic dynamics and informing control strategies, including for SARS-CoV-2. However, there is a paucity of data on social mixing patterns in many settings. We conducted a community-based survey in Cambodia in 2012 to characterise mixing patterns and generate setting-specific contact matrices according to age and urban/rural populations. Data were collected using a diary-based approach from 2016 participants, selected by stratified random sampling. Contact patterns were highly age-assortative, with clear intergenerational mixing between household members. Both home and school were high-intensity contact settings, with 27.7% of contacts occurring at home with non-household members. Social mixing patterns differed between rural and urban residents; rural participants tended to have more intergenerational mixing, and a higher number of contacts outside of home, work or school. Participants had low spatial mobility, with 88% of contacts occurring within 1 km of the participants’ homes. These data broaden the evidence-base on social mixing patterns in low and middle-income countries and Southeast Asia, and highlight within-country heterogeneities which may be important to consider when modelling the dynamics of pathogens transmitted via close contact.