Geospatial analysis of shared risks for tuberculosis transmission in an urban cohort

  • Michael Asare-Baah
  • , Tan M. Luong
  • , Ernest Kwarteng
  • , Charles Domotey
  • , Nellie Arthur
  • , Magalie Zoungrana
  • , Sheila Mireku-Apah
  • , Honesty Ganu
  • , Michael Amo Omari
  • , Adelaide Sackey
  • , Awewura Kwara
  • , Jane Sandra Afriyie-Mensah
  • , Marie Nancy Séraphin

Research output: Contribution to journalArticlepeer-review

Abstract

Effective TB control in rapidly changing sociodemographic settings with high TB prevalence requires understanding the evolving social and behavioral determinants of disease risk. This study examined the spatial distribution of TB cases and assessed whether shared clinical and social characteristics were associated with closer residential proximity in the Greater Accra Region, Ghana. Between June 2022 and July 2023, individuals with new and previously treated TB were enrolled at a referral hospital in the Accra Metropolitan Area. Participants completed structured questionnaires on demographic, clinical, and behavioral risk factors, and residential coordinates were collected during home-based contact tracing. Spatial clustering was evaluated using local Moran’s I statistics. A Bayesian cross-random effects gamma regression model examined the association between shared characteristics and residential proximity, with distances shifted, centered, and rescaled for interpretation. The study population (N = 150) was predominantly male (68.0%) and of working age (80.0% aged 25–64 years), with 51.3% engaged in unskilled labor. Spatial analysis identified localized clusters of TB cases in high-density residential areas. Sharing the same religious affiliation, reporting recent exposure to household or non-household individuals with cough, and hemoptysis were modestly associated with closer residential proximity, although the effect sizes were small and credible intervals were close to the null. Treatment history demonstrated strong spatial patterns, with previously treated cases clustering more tightly than newly diagnosed cases. TB cases exhibited spatial clustering linked to shared clinical and social risk factors. Although residential proximity does not directly indicate transmission sites, tighter clustering among previously treated cases may reflect both sustained exposure to high-transmission environments and barriers to completing effective treatment. Other shared characteristics, including religious affiliation, non-household exposure to individuals with cough, and hemoptysis, were modestly associated with closer proximity, but their clinical and public health significance remains uncertain. Targeted interventions in identified hotspots, alongside strategies to improve treatment completion and long-term outcomes, may support TB control efforts in this urban high TB/HIV burden setting.

Original languageEnglish
Article number39470
JournalScientific Reports
Volume15
Issue number1
DOIs
Publication statusPublished - Dec 2025

Keywords

  • Bayesian regression
  • Ghana
  • Spatial analysis
  • Tuberculosis
  • Urban health

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