ArticleBMC public health2021
A cross-sectional study measuring contact patterns using diaries in an urban and a rural community in South Africa, 2018.
Article in BMC public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- The roles of pre-season immunity, age, viral shedding, and community exposures in shaping influenza household transmission dynamics.Nature communications · 2026Article
- Modelling the impact of increasing tuberculosis treatment coverage and addressing determinants of risk in men.Communications medicine · 2026Article
- Relationship between household attributes and contact patterns in urban and rural South Africa.PloS one · 2026Article
- Characterising non-household contact patterns relevant to respiratory transmission in the USA: analysis of a cross-sectional survey.The Lancet. Digital health · 2025Article
- Article
- Characterising social contacts under COVID-19 control measures in Africa.BMC medicine · 2022Article
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDescribing contact patterns is crucial to understanding infectious disease transmission dynamics and guiding targeted transmission mitigation interventions. Data on contact patterns in Africa, especially South Africa, are limited. We measured and compared contact patterns in a rural and urban community, South Africa. We assessed participant and contact characteristics associated with differences in contact rates.
methodsWe conducted a cross-sectional study nested in a prospective household cohort study. We interviewed participants to collect information on persons in contact with for one day. We described self-reported contact rates as median number people contacted per day, assessed differences in contact rates based on participant characteristics using quantile regression, and used a Poisson model to assess differences in contact rates based on contact characteristics within age groups. We also calculated cumulative person hours in contact within age groups at different locations.
resultsWe conducted 535 interviews (269 rural, 266 urban), with 17,252 contacts reported. The overall contact rate was 14 (interquartile range (IQR) 9-33) contacts per day. Those ≤18 years had higher contact rates at the rural site (coefficient 17, 95% confidence interval (95%CI) 10-23) compared to the urban site, for those aged 14-18 years (13, 95%CI 3-23) compared to < 7 years. No differences were observed for adults. There was a strong age-based mixing, with age groups interacting more with similar age groups, but also interaction of participants of all ages with adults. Children aged 14-18 years had the highest cumulative person hours in contact (116.3 rural and 76.4 urban).
conclusionsAge played an important role in the number and duration of contact events, with children at the rural site having almost double the contact rate compared to the urban site. These contact rates can be utilized in mathematical models to assess transmission dynamics of infectious diseases in similar communities.
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