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Characterising social contacts under COVID-19 control measures in Africa

BACKGROUND: Early in the COVID-19 pandemic, countries adopted non-pharmaceutical interventions (NPIs) such as lockdowns to limit SARS-CoV-2 transmission. Social contact studies help measure the effectiveness of NPIs and estimate parameters for modelling SARS-CoV-2 transmission. However, few contact...

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Autores principales: Dobreva, Zlatina, Gimma, Amy, Rohan, Hana, Djoudalbaye, Benjamin, Tshangela, Akhona, Jarvis, Christopher I., van Zandvoort, Kevin, Quaife, Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553295/
https://www.ncbi.nlm.nih.gov/pubmed/36221094
http://dx.doi.org/10.1186/s12916-022-02543-6
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author Dobreva, Zlatina
Gimma, Amy
Rohan, Hana
Djoudalbaye, Benjamin
Tshangela, Akhona
Jarvis, Christopher I.
van Zandvoort, Kevin
Quaife, Matthew
author_facet Dobreva, Zlatina
Gimma, Amy
Rohan, Hana
Djoudalbaye, Benjamin
Tshangela, Akhona
Jarvis, Christopher I.
van Zandvoort, Kevin
Quaife, Matthew
author_sort Dobreva, Zlatina
collection PubMed
description BACKGROUND: Early in the COVID-19 pandemic, countries adopted non-pharmaceutical interventions (NPIs) such as lockdowns to limit SARS-CoV-2 transmission. Social contact studies help measure the effectiveness of NPIs and estimate parameters for modelling SARS-CoV-2 transmission. However, few contact studies have been conducted in Africa. METHODS: We analysed nationally representative cross-sectional survey data from 19 African Union Member States, collected by the Partnership for Evidence-based Responses to COVID-19 (PERC) via telephone interviews at two time points (August 2020 and February 2021). Adult respondents reported contacts made in the previous day by age group, demographic characteristics, and their attitudes towards COVID-19. We described mean and median contacts across these characteristics and related contacts to Google Mobility reports and the Oxford Government Response Stringency Index for each country at the two time points. RESULTS: Mean reported contacts varied across countries with the lowest reported in Ethiopia (9, SD=16, median = 4, IQR = 8) in August 2020 and the highest in Sudan (50, SD=53, median = 33, IQR = 40) in February 2021. Contacts of people aged 18–55 represented 50% of total contacts, with most contacts in household and work or study settings for both surveys. Mean contacts increased for Ethiopia, Ghana, Liberia, Nigeria, Sudan, and Uganda and decreased for Cameroon, the Democratic Republic of Congo (DRC), and Tunisia between the two time points. Men had more contacts than women and contacts were consistent across urban or rural settings (except in Cameroon and Kenya, where urban respondents had more contacts than rural ones, and in Senegal and Zambia, where the opposite was the case). There were no strong and consistent variations in the number of mean or median contacts by education level, self-reported health, perceived self-reported risk of infection, vaccine acceptance, mask ownership, and perceived risk of COVID-19 to health. Mean contacts were correlated with Google mobility (coefficient 0.57, p=0.051 and coefficient 0.28, p=0.291 in August 2020 and February 2021, respectively) and Stringency Index (coefficient −0.12, p = 0.304 and coefficient −0.33, p=0.005 in August 2020 and February 2021, respectively). CONCLUSIONS: These are the first COVID-19 social contact data collected for 16 of the 19 countries surveyed. We find a high reported number of daily contacts in all countries and substantial variations in mean contacts across countries and by gender. Increased stringency and decreased mobility were associated with a reduction in the number of contacts. These data may be useful to understand transmission patterns, model infection transmission, and for pandemic planning. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-022-02543-6.
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spelling pubmed-95532952022-10-12 Characterising social contacts under COVID-19 control measures in Africa Dobreva, Zlatina Gimma, Amy Rohan, Hana Djoudalbaye, Benjamin Tshangela, Akhona Jarvis, Christopher I. van Zandvoort, Kevin Quaife, Matthew BMC Med Research Article BACKGROUND: Early in the COVID-19 pandemic, countries adopted non-pharmaceutical interventions (NPIs) such as lockdowns to limit SARS-CoV-2 transmission. Social contact studies help measure the effectiveness of NPIs and estimate parameters for modelling SARS-CoV-2 transmission. However, few contact studies have been conducted in Africa. METHODS: We analysed nationally representative cross-sectional survey data from 19 African Union Member States, collected by the Partnership for Evidence-based Responses to COVID-19 (PERC) via telephone interviews at two time points (August 2020 and February 2021). Adult respondents reported contacts made in the previous day by age group, demographic characteristics, and their attitudes towards COVID-19. We described mean and median contacts across these characteristics and related contacts to Google Mobility reports and the Oxford Government Response Stringency Index for each country at the two time points. RESULTS: Mean reported contacts varied across countries with the lowest reported in Ethiopia (9, SD=16, median = 4, IQR = 8) in August 2020 and the highest in Sudan (50, SD=53, median = 33, IQR = 40) in February 2021. Contacts of people aged 18–55 represented 50% of total contacts, with most contacts in household and work or study settings for both surveys. Mean contacts increased for Ethiopia, Ghana, Liberia, Nigeria, Sudan, and Uganda and decreased for Cameroon, the Democratic Republic of Congo (DRC), and Tunisia between the two time points. Men had more contacts than women and contacts were consistent across urban or rural settings (except in Cameroon and Kenya, where urban respondents had more contacts than rural ones, and in Senegal and Zambia, where the opposite was the case). There were no strong and consistent variations in the number of mean or median contacts by education level, self-reported health, perceived self-reported risk of infection, vaccine acceptance, mask ownership, and perceived risk of COVID-19 to health. Mean contacts were correlated with Google mobility (coefficient 0.57, p=0.051 and coefficient 0.28, p=0.291 in August 2020 and February 2021, respectively) and Stringency Index (coefficient −0.12, p = 0.304 and coefficient −0.33, p=0.005 in August 2020 and February 2021, respectively). CONCLUSIONS: These are the first COVID-19 social contact data collected for 16 of the 19 countries surveyed. We find a high reported number of daily contacts in all countries and substantial variations in mean contacts across countries and by gender. Increased stringency and decreased mobility were associated with a reduction in the number of contacts. These data may be useful to understand transmission patterns, model infection transmission, and for pandemic planning. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-022-02543-6. BioMed Central 2022-10-12 /pmc/articles/PMC9553295/ /pubmed/36221094 http://dx.doi.org/10.1186/s12916-022-02543-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Dobreva, Zlatina
Gimma, Amy
Rohan, Hana
Djoudalbaye, Benjamin
Tshangela, Akhona
Jarvis, Christopher I.
van Zandvoort, Kevin
Quaife, Matthew
Characterising social contacts under COVID-19 control measures in Africa
title Characterising social contacts under COVID-19 control measures in Africa
title_full Characterising social contacts under COVID-19 control measures in Africa
title_fullStr Characterising social contacts under COVID-19 control measures in Africa
title_full_unstemmed Characterising social contacts under COVID-19 control measures in Africa
title_short Characterising social contacts under COVID-19 control measures in Africa
title_sort characterising social contacts under covid-19 control measures in africa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9553295/
https://www.ncbi.nlm.nih.gov/pubmed/36221094
http://dx.doi.org/10.1186/s12916-022-02543-6
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