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ISPRS Int. J. Geo-Inf. 2019, 8(1), 14; https://doi.org/10.3390/ijgi8010014

A Spatial Analysis Framework to Monitor and Accelerate Progress towards SDG 3 to End TB in Bangladesh

1
KIT Royal Tropical Institute, Center for Applied Spatial Epidemiology, 1092AD Amsterdam, The Netherlands
2
National TB Control Program, Directorate General of Health Services, Mohakhali, Dhaka 1212, Bangladesh
*
Author to whom correspondence should be addressed.
Received: 5 October 2018 / Revised: 12 December 2018 / Accepted: 21 December 2018 / Published: 29 December 2018
(This article belongs to the Special Issue Geo-Information and the Sustainable Development Goals (SDGs))
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Abstract

Global efforts to end the tuberculosis (TB) epidemic by 2030 (SDG3.3) through improved TB case detection and treatment have not been effective to significantly reduce the global burden of the TB epidemic. This study presents an analytical framework to evaluate the use of TB case notification rates (CNR) to monitor and to evaluate TB under-detection and under-diagnoses in Bangladesh. Local indicators of spatial autocorrelation (LISA) were calculated to assess the presence and scale of spatial clusters of TB CNR across 489 upazilas in Bangladesh. Simultaneous autoregressive models were fit to the data to identify associations between TB CNR and poverty, TB testing rates and retreatment rates. CNRs were found to be significantly spatially clustered, negatively correlated to poverty rates and positively associated to TB testing and retreatment rates. Comparing the observed pattern of CNR with model-standardized rates made it possible to identify areas where TB under-detection is likely to occur. These results suggest that TB CNR is an unreliable proxy for TB incidence. Spatial variations in TB case notifications and subnational variations in TB case detection should be considered when monitoring national TB trends. These results provide useful information to target and prioritize context specific interventions. View Full-Text
Keywords: tuberculosis; case notification; National Tuberculosis program; MATCH; patient pathway; access to care; health system performance; GIS; spatial analysis; SDG 3 tuberculosis; case notification; National Tuberculosis program; MATCH; patient pathway; access to care; health system performance; GIS; spatial analysis; SDG 3
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Rood, E.; Khan, A.H.; Modak, P.K.; Mergenthaler, C.; Van Gurp, M.; Blok, L.; Bakker, M. A Spatial Analysis Framework to Monitor and Accelerate Progress towards SDG 3 to End TB in Bangladesh. ISPRS Int. J. Geo-Inf. 2019, 8, 14.

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