Social mixing in Fiji: Who-eats-with-whom contact patterns and the implications of age and ethnic heterogeneity for disease dynamics in the Pacific Islands

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Watson, CH, Coriakula, J, Ngoc, DTT, Flasche, S, Kucharski, AJ, Lau, CL, Thieu, NTV, le Polain de Waroux, O, Rawalai, K, Van, TT, Taufa, M, Baker, S, Nilles, EJ, Kama, M and Edmunds, WJ. 2017. Social mixing in Fiji: Who-eats-with-whom contact patterns and the implications of age and ethnic heterogeneity for disease dynamics in the Pacific Islands. [Online]. PLOS One. Available from: - https://doi.org/10.1371/journal.pone.0186911

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Empirical data on contact patterns can inform dynamic models of infectious disease transmission. Such information has not been widely reported from Pacific islands, nor strongly multi-ethnic settings, and few attempts have been made to quantify contact patterns relevant for the spread of gastrointestinal infections. As part of enteric fever investigations, we conducted a cross-sectional survey of the general public in Fiji, finding that within the 9,650 mealtime contacts reported by 1,814 participants, there was strong like-with-like mixing by age and ethnicity, with higher contact rates amongst iTaukei than non-iTaukei Fijians. Extra-domiciliary lunchtime contacts follow these mixing patterns, indicating the overall data do not simply reflect household structures. Inter-ethnic mixing was most common amongst school-age children. Serological responses indicative of recent Salmonella Typhi infection were found to be associated, after adjusting for age, with increased contact rates between meal-sharing iTaukei, with no association observed for other contact groups. Animal ownership and travel within the geographical division were common. These are novel data that identify ethnicity as an important social mixing variable, and use retrospective mealtime contacts as a socially acceptable metric of relevance to enteric, contact and respiratory diseases that can be collected in a single visit to participants. Application of these data to other island settings will enable communicable disease models to incorporate locally relevant mixing patterns in parameterisation.

Published in a 3rd party system Date: 12 December 2017
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Questionnaire: Fixed form
Data Creators(s): Watson, CH, Coriakula, J, Ngoc, DTT, Flasche, S, Kucharski, AJ, Lau, CL, Thieu, NTV, le Polain de Waroux, O, Rawalai, K, Van, TT, Taufa, M, Baker, S, Nilles, EJ, Kama, M and Edmunds, WJ
LSHTM Faculty/Department: Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology
Participating Institutions: London School of Hygiene & Tropical Medicine, London, United Kingdom

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