Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors [version 2; peer review: 2 approved]
Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between indiv...
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Format: | Article |
Language: | English |
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Wellcome
2019-08-01
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Series: | Wellcome Open Research |
Online Access: | https://wellcomeopenresearch.org/articles/4-84/v2 |
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author | Moses Chapa Kiti Alessia Melegaro Ciro Cattuto David James Nokes |
author_facet | Moses Chapa Kiti Alessia Melegaro Ciro Cattuto David James Nokes |
author_sort | Moses Chapa Kiti |
collection | DOAJ |
description | Background: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing. |
first_indexed | 2024-12-20T21:29:01Z |
format | Article |
id | doaj.art-11ef1cd68649464f89e887cff4660848 |
institution | Directory Open Access Journal |
issn | 2398-502X |
language | English |
last_indexed | 2024-12-20T21:29:01Z |
publishDate | 2019-08-01 |
publisher | Wellcome |
record_format | Article |
series | Wellcome Open Research |
spelling | doaj.art-11ef1cd68649464f89e887cff46608482022-12-21T19:26:05ZengWellcomeWellcome Open Research2398-502X2019-08-01410.12688/wellcomeopenres.15268.216859Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors [version 2; peer review: 2 approved]Moses Chapa Kiti0Alessia Melegaro1Ciro Cattuto2David James Nokes3Epidemiology and Demography Department, KEMRI-Wellcome Trust Research Programme, Kilifi, 80108, KenyaDepartment of Social and Political Sciences, Bocconi University, Milan, ItalyData Science Laboratory, Institute for Scientific Interchange Foundation, Turin, ItalyZeeman Institute of Systems Biology and Infectious Disease Research, University of Warwick, Coventry, UKBackground: Social contact patterns shape the transmission of respiratory infections spread via close interactions. There is a paucity of observational data from schools and households, particularly in developing countries. Portable wireless sensors can record unbiased proximity events between individuals facing each other, shedding light on pathways of infection transmission. Design and methods: The aim is to characterize face-to-face contact patterns that may shape the transmission of respiratory infections in schools and households in Kilifi, Kenya. Two schools, one each from a rural and urban area, will be purposively selected. From each school, 350 students will be randomly selected proportional to class size and gender to participate. Nine index students from each school will be randomly selected and followed-up to their households. All index household residents will be recruited into the study. A further 3-5 neighbouring households will also be recruited to give a maximum of 350 participants per household setting. The sample size per site is limited by the number of sensors available for data collection. Each participant will wear a wireless proximity sensor lying on their chest area for 7 consecutive days. Data on proximal dyadic interactions will be collected automatically by the sensors only for participants who are face-to-face. Key characteristics of interest include the distribution of degree and the frequency and duration of contacts and their variation in rural and urban areas. These will be stratified by age, gender, role, and day of the week. Expected results: Resultant data will inform on social contact patterns in rural and urban areas of a previously unstudied population. Ensuing data will be used to parameterize mathematical simulation models of transmission of a range of respiratory viruses, including respiratory syncytial virus, and used to explore the impact of intervention measures such as vaccination and social distancing.https://wellcomeopenresearch.org/articles/4-84/v2 |
spellingShingle | Moses Chapa Kiti Alessia Melegaro Ciro Cattuto David James Nokes Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors [version 2; peer review: 2 approved] Wellcome Open Research |
title | Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors [version 2; peer review: 2 approved] |
title_full | Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors [version 2; peer review: 2 approved] |
title_fullStr | Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors [version 2; peer review: 2 approved] |
title_full_unstemmed | Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors [version 2; peer review: 2 approved] |
title_short | Study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in Kenya using wearable proximity sensors [version 2; peer review: 2 approved] |
title_sort | study design and protocol for investigating social network patterns in rural and urban schools and households in a coastal setting in kenya using wearable proximity sensors version 2 peer review 2 approved |
url | https://wellcomeopenresearch.org/articles/4-84/v2 |
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