TB Research

Geospatial Distribution of Tuberculosis Incidence and Determinants of Tuberculosis Treatment Outcomes in Nzema East Municipality, Ghana

Charles Afriyie Agyapong, Ali Davod Parsa, Richard Hayhoe, Russell Kabir, Mark Cortnage

Public Health Challenges · 2025-08

Abstract

ABSTRACT Background Ghana has seen a notable rise in tuberculosis (TB) cases with mired treatment outcomes. However, evidence suggests disparities in the incidence of TB and its treatment outcomes across the country. Nzema East Municipality specifically reported a 62.34% increase in TB incidence in 2023 compared to 2022. The study, therefore, aims to determine the geospatial distribution of TB incidence and predictors of TB treatment outcomes in Nzema East Municipality. Methods The study used a retrospective cohort with a quantitative approach, utilising health records of 545 TB cases from 2018 to 2023 in Nzema East. Data were processed with Microsoft Excel and analysed using ArcGIS Pro version 3.3.2, Joinpoint Regression Programme 5.2.0 and STATA MP version 17. Results The Moran's index was 0.03 ( p < 0.001). All the subdistricts had at least one settlement with 2–26 TB cases per square kilometre. Significant TB hotspots were identified in the population‐dense communities and mining communities. Overall, the successful TB treatment outcome was 76.70%. There was a significant decline in successful TB treatment outcomes from 2018 to the end of 2020 and through 2023 ( p = 0.03 and p < 0.001), respectively. Having at least one follow‐up lab (aRR = 0.43; 95% CI = 0.32, 0.58) and having a treatment supporter (aRR = 0.56; 95% CI = 0.40, 0.79) lessens the risk of having an unsuccessful TB treatment outcome. Having started the TB treatment in 2020 increases the chances of having an unsuccessful outcome (aRR = 1.97; 95% CI = 1.13, 3.43). Conclusion TB incidence in Nzema East was spatially dependent, with statistically significant higher incidence in the highly populated and mining communities. The overall successful treatment outcome is suboptimal, which demands targeted intervention to mitigate these menaces.

MeSH terms

  • Tuberculosis
  • Geospatial analysis
  • Incidence (geometry)
  • Geography
  • Distribution (mathematics)
  • Environmental health
  • Medicine
  • Socioeconomics