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Social contact patterns relevant for infectious disease transmission in Cambodia.
Leung, William T M; Meeyai, Aronrag; Holt, Hannah R; Khieu, Borin; Chhay, Ty; Seng, Sokeyra; Pok, Samkol; Chiv, Phiny; Drake, Tom; Rudge, James W.
  • Leung WTM; Communicable Diseases Policy Research Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK.
  • Meeyai A; Communicable Diseases Policy Research Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK.
  • Holt HR; Department of Epidemiology, Faculty of Mahidol Public Health, Mahidol University, Bangkok, 10400, Thailand.
  • Khieu B; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7LG, UK.
  • Chhay T; Communicable Diseases Policy Research Group, Department of Global Health and Development, London School of Hygiene and Tropical Medicine, Keppel St, London, WC1E 7HT, UK. Hannah.Holt@lshtm.ac.uk.
  • Seng S; Livestock Development for Community Livelihood Organization, St 181, Phnom Penh, Cambodia.
  • Pok S; Livestock Development for Community Livelihood Organization, St 181, Phnom Penh, Cambodia.
  • Chiv P; Livestock Development for Community Livelihood Organization, St 181, Phnom Penh, Cambodia.
  • Drake T; Livestock Development for Community Livelihood Organization, St 181, Phnom Penh, Cambodia.
  • Rudge JW; National Institute of Science, Technology and Innovation, Ministry of Industry, Science, Technology and Innovation, National Road 2, Phnom Penh, Cambodia.
Sci Rep ; 13(1): 5542, 2023 04 04.
Artículo en Inglés | MEDLINE | ID: covidwho-2268549
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.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Enfermedades Transmisibles / COVID-19 Tipo de estudio: Estudio observacional / Ensayo controlado aleatorizado Límite: Humanos País/Región como asunto: Asia Idioma: Inglés Revista: Sci Rep Año: 2023 Tipo del documento: Artículo País de afiliación: S41598-023-31485-z

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Enfermedades Transmisibles / COVID-19 Tipo de estudio: Estudio observacional / Ensayo controlado aleatorizado Límite: Humanos País/Región como asunto: Asia Idioma: Inglés Revista: Sci Rep Año: 2023 Tipo del documento: Artículo País de afiliación: S41598-023-31485-z