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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.
Afiliação
  • Jo Y; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Baik Y; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Shrestha S; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Pennington J; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Gomes I; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Reja M; Challenge TB Project, Interactive Research & Development (IRD), Dhaka, Bangladesh.
  • Islam S; Interactive Research & Development (IRD), Dhaka, Bangladesh.
  • Roy T; National Tuberculosis Control Program (NTP), Dhaka, Bangladesh.
  • Hussain H; Interactive Research & Development (IRD), Dhaka, Bangladesh.
  • Dowdy D; Interactive Research & Development (IRD) Global, Singapore.
Epidemiol Infect ; 149: e209, 2021 09 02.
Article em En | MEDLINE | ID: mdl-35506926
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tuberculose Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans País como assunto: Asia Idioma: En Ano de publicação: 2021 Tipo de documento: Article