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A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata

BACKGROUND: There is a lack of research investigating the confluence of risk factors in urban slums that may make them accelerators for respiratory, droplet infections like COVID-19. Our working hypothesis was that, even within slums, an inverse relationship existed between living density and access...

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Autores principales: Hasan, Shaikh Mehdi, Das, Susmita, Hanifi, Syed Manzoor Ahmed, Shafique, Sohana, Rasheed, Sabrina, Reidpath, Daniel D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957470/
https://www.ncbi.nlm.nih.gov/pubmed/33722207
http://dx.doi.org/10.1186/s12889-021-10230-z
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author Hasan, Shaikh Mehdi
Das, Susmita
Hanifi, Syed Manzoor Ahmed
Shafique, Sohana
Rasheed, Sabrina
Reidpath, Daniel D.
author_facet Hasan, Shaikh Mehdi
Das, Susmita
Hanifi, Syed Manzoor Ahmed
Shafique, Sohana
Rasheed, Sabrina
Reidpath, Daniel D.
author_sort Hasan, Shaikh Mehdi
collection PubMed
description BACKGROUND: There is a lack of research investigating the confluence of risk factors in urban slums that may make them accelerators for respiratory, droplet infections like COVID-19. Our working hypothesis was that, even within slums, an inverse relationship existed between living density and access to shared or private WASH facilities. METHODS: In an exploratory, secondary analysis of World Bank, cross-sectional microdata from slums in Bangladesh we investigated the relationship between intra-household population density (crowding) and access to private or shared water sources and toilet facilities. RESULTS: The analysis showed that most households were single-room dwellings (80.4%). Median crowding ranged from 0.55 m(2) per person up to 67.7 m(2) per person. The majority of the dwellings (83.3%), shared both toilet facilities and the source of water, and there was a significant positive relationship between crowding and the use of shared facilities. CONCLUSION: The findings highlight the practical constraints on implementing, in slums, the conventional COVID19 management approaches of social distancing, regular hand washing, and not sharing spaces. It has implications for the management of future respiratory epidemics.
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spelling pubmed-79574702021-03-15 A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata Hasan, Shaikh Mehdi Das, Susmita Hanifi, Syed Manzoor Ahmed Shafique, Sohana Rasheed, Sabrina Reidpath, Daniel D. BMC Public Health Research Article BACKGROUND: There is a lack of research investigating the confluence of risk factors in urban slums that may make them accelerators for respiratory, droplet infections like COVID-19. Our working hypothesis was that, even within slums, an inverse relationship existed between living density and access to shared or private WASH facilities. METHODS: In an exploratory, secondary analysis of World Bank, cross-sectional microdata from slums in Bangladesh we investigated the relationship between intra-household population density (crowding) and access to private or shared water sources and toilet facilities. RESULTS: The analysis showed that most households were single-room dwellings (80.4%). Median crowding ranged from 0.55 m(2) per person up to 67.7 m(2) per person. The majority of the dwellings (83.3%), shared both toilet facilities and the source of water, and there was a significant positive relationship between crowding and the use of shared facilities. CONCLUSION: The findings highlight the practical constraints on implementing, in slums, the conventional COVID19 management approaches of social distancing, regular hand washing, and not sharing spaces. It has implications for the management of future respiratory epidemics. BioMed Central 2021-03-15 /pmc/articles/PMC7957470/ /pubmed/33722207 http://dx.doi.org/10.1186/s12889-021-10230-z Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver (http://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
Hasan, Shaikh Mehdi
Das, Susmita
Hanifi, Syed Manzoor Ahmed
Shafique, Sohana
Rasheed, Sabrina
Reidpath, Daniel D.
A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata
title A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata
title_full A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata
title_fullStr A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata
title_full_unstemmed A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata
title_short A place-based analysis of COVID-19 risk factors in Bangladesh urban slums: a secondary analysis of World Bank microdata
title_sort place-based analysis of covid-19 risk factors in bangladesh urban slums: a secondary analysis of world bank microdata
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957470/
https://www.ncbi.nlm.nih.gov/pubmed/33722207
http://dx.doi.org/10.1186/s12889-021-10230-z
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