Abstract

In this study, we investigate differences in tuberculosis (TB) treatment outcomes between urban and rural India and estimate their impact on epidemiological outcomes such as TB incidence, prevalence and mortality using a mathematical model of TB transmission dynamics. Publicly available district-level treatment outcomes data for new and previously treated TB cases was analyzed in conjunction with census data providing the proportion of urban population in each district to determine the effect of urbanity/rurality on treatment outcomes. Districts were grouped in clusters based on the proportion of urban population in each district, wherein the clusters were identified by applying machine learning methods. Regression analyses revealed that average treatment success rates among both new and previously treated cases decline with increase in the proportion of urban population in a district cluster, with substantially sharper declines in treatment success rates with degree of urbanity observed for previously treated cases. The impact of differences in treatment outcomes on epidemiological outcomes was estimated using a dynamic transmission model developed for this purpose. For example, the cluster with highest treatment success rates is projected to have an average of 3.2% fewer deaths per 100,000 population in comparison with the national average across 2019–24, and the cluster with the lowest treatment success rates has an average of 4.5% more deaths per 100,000 in comparison with the national average. We anticipate that these disparities in TB treatment outcomes and epidemiology between urban and rural India may motivate investigations into the associated causes and their redressal.

Highlights

  • A more comprehensive approach towards calibration might have been to calibrate the model to a similar set of calibration targets for each cluster, and use the cluster-specific model along with the cluster-specific treatment success rates among new and previously treated cases to project the effect of differences in treatment outcomes on epidemiological outcomes

  • We investigate the differences in TB outcomes between urban and rural India using district-level treatment outcomes data from the annual TB India reports published by the Central TB Division, Government of India

  • This is the first study, based on our survey of the literature, which has investigated how TB treatment outcomes vary across districts in conjunction with the proportion of urban population in each district

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Summary

Introduction

We utilize most recently published district-level data for RNTCP treatment outcomes in conjunction with census data for the proportion of a district’s population residing in urban areas for our analysis (referred to hereafter as degree of urbanity). We utilize a model of TB transmission dynamics, which we developed and calibrated to published incidence and prevalence trends, to develop projections and conduct simulation analyses around incidence, prevalence, and mortality trends for each cluster. We develop this TB transmission dynamics model by substantially modifying Mandal and colleagues’ model [7], to incorporate across-cluster differences in outcomes between previously treated cases and new cases. We anticipate that our analysis can assist stakeholders in identifying districts with RNTCP programmes that require particular attention and help motivate improvement of treatment outcomes in these districts

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