About: 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

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About: 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 Goto Sponge NotDistinct Permalink

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
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
Creator	Cattuto, Ciro Kucharski, Adam Melegaro, Alessia Kiti, Moses Nokes, David
source	PMC
abstract	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.
has issue date	2019-08-22(xsd:dateTime)
bibo:doi	10.12688/wellcomeopenres.15268.2
bibo:pmid	31489381
has license	cc-by
sha1sum (hex)	72b1f124ded8f8297f0f02ea6dbc0f9b7b27873a
schema:url	https://doi.org/10.12688/wellcomeopenres.15268.2
resource representing a document's 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
has PubMed Central identifier	PMC6719676
has PubMed identifier	31489381
schema:publication	Wellcome Open Res
resource representing a document's body	covid:72b1f124ded8f8297f0f02ea6dbc0f9b7b27873a#body_text
is schema:about of	named entity 'observational' named entity 'investigating' named entity 'social network' named entity 'wearable' named entity 'COASTAL' »more»

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