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Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh
We developed a novel method to align two data sources (TB notifications and the Demographic Health Survey, DHS) captured at different geographic scales. We used this method to identify sociodemographic indicators – specifically population density – that were ecologically correlated with elevated TB...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479848/ https://www.ncbi.nlm.nih.gov/pubmed/35506926 http://dx.doi.org/10.1017/S0950268821001679 |
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author | Jo, Youngji Baik, Yeonsoo Shrestha, Sourya Pennington, Jeffrey Gomes, Isabella Reja, Mehdi Islam, Shamiul Roy, Tapash Hussain, Hamidah Dowdy, David |
author_facet | Jo, Youngji Baik, Yeonsoo Shrestha, Sourya Pennington, Jeffrey Gomes, Isabella Reja, Mehdi Islam, Shamiul Roy, Tapash Hussain, Hamidah Dowdy, David |
author_sort | Jo, Youngji |
collection | PubMed |
description | We developed a novel method to align two data sources (TB notifications and the Demographic Health Survey, DHS) captured at different geographic scales. We used this method to identify sociodemographic indicators – specifically population density – that were ecologically correlated with elevated TB notification rates across wards (~100 000 people) in Dhaka, Bangladesh. We found population density was the variable most closely correlated with ward-level TB notification rates (Spearman's rank correlation 0.45). Our approach can be useful, as publicly available data (e.g. DHS data) could help identify factors that are ecologically associated with disease burden when more granular data (e.g. ward-level TB notifications) are not available. Use of this approach might help in designing spatially targeted interventions for TB and other diseases in settings of weak existing data on disease burden at the subdistrict level. |
format | Online Article Text |
id | pubmed-8479848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84798482021-10-08 Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh Jo, Youngji Baik, Yeonsoo Shrestha, Sourya Pennington, Jeffrey Gomes, Isabella Reja, Mehdi Islam, Shamiul Roy, Tapash Hussain, Hamidah Dowdy, David Epidemiol Infect Short Paper We developed a novel method to align two data sources (TB notifications and the Demographic Health Survey, DHS) captured at different geographic scales. We used this method to identify sociodemographic indicators – specifically population density – that were ecologically correlated with elevated TB notification rates across wards (~100 000 people) in Dhaka, Bangladesh. We found population density was the variable most closely correlated with ward-level TB notification rates (Spearman's rank correlation 0.45). Our approach can be useful, as publicly available data (e.g. DHS data) could help identify factors that are ecologically associated with disease burden when more granular data (e.g. ward-level TB notifications) are not available. Use of this approach might help in designing spatially targeted interventions for TB and other diseases in settings of weak existing data on disease burden at the subdistrict level. Cambridge University Press 2021-09-02 /pmc/articles/PMC8479848/ /pubmed/35506926 http://dx.doi.org/10.1017/S0950268821001679 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. |
spellingShingle | Short Paper Jo, Youngji Baik, Yeonsoo Shrestha, Sourya Pennington, Jeffrey Gomes, Isabella Reja, Mehdi Islam, Shamiul Roy, Tapash Hussain, Hamidah Dowdy, David Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh |
title | Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh |
title_full | Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh |
title_fullStr | Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh |
title_full_unstemmed | Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh |
title_short | Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh |
title_sort | sub-district level correlation between tuberculosis notifications and socio-demographic factors in dhaka city corporation, bangladesh |
topic | Short Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479848/ https://www.ncbi.nlm.nih.gov/pubmed/35506926 http://dx.doi.org/10.1017/S0950268821001679 |
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