Sub-district level correlation between tuberculosis notifications and socio-demographic factors in Dhaka City corporation, Bangladesh

Author:

Jo YoungjiORCID,Baik Yeonsoo,Shrestha SouryaORCID,Pennington Jeffrey,Gomes Isabella,Reja Mehdi,Islam Shamiul,Roy Tapash,Hussain Hamidah,Dowdy David

Abstract

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.

Funder

United States Agency for International Development

Publisher

Cambridge University Press (CUP)

Subject

Infectious Diseases,Epidemiology

Reference21 articles.

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4. Tobler's First Law and Spatial Analysis

5. Using the Fusion Proximal Area Method and Gravity Method to Identify Areas with Physician Shortages

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