Affiliation:
1. University of Florida
2. Korle-Bu Teaching Hospital
3. National Tuberculosis Control Programme, Ghana Health Service
Abstract
Abstract
Background In emerging economies experiencing rapid sociodemographic transitions and historically high tuberculosis (TB) prevalence, effective TB control requires acknowledging the evolving socio-behavioral characteristics of diverse patient populations shaping community-level TB risk. This study aimed to explore the spatial distribution and clustering of shared modifiable clinical and social risk factors for TB in a clinic-based population in Accra, Ghana.Methods We prospectively enrolled new and previously treated TB patients between June 2022 and July 2023. At diagnosis, patients provided informed consent to collect their residential coordinates and completed a questionnaire assessing their demographic and modifiable clinical and social risks for TB. We used geospatial scan statistics to describe the spatial distribution of cases and PERMANOVA to examine the correlation between spatial proximity and shared socio-behavioral risks, with a 1.5 square kilometer threshold defining significant residential proximity.Results The study population (N = 150) was predominantly male (68.0%) and of working age (80.0% aged 25–64 years), with half the sample engaged in unskilled labor (51.3%). Approximately one-third reported heavy alcohol (36.0%) and recreational drug use (26.7%) in the past year. Fifteen percent were HIV-positive, of whom more than 80% were diagnosed at the time of TB diagnosis. Local Moran's I statistics revealed spatial clusters of TB cases in separate sections of the study area. Unskilled labor, recreational drug use, and a history of cough in patients’ social contacts were significantly associated with residential proximity, explaining 1.26% of the variance in our model (F = 1.89, R^2 = 1.3%, p = 0.004).Conclusions Shared modifiable risks, including unskilled labor, recreational drug use, and close contact with TB, exhibited spatial clustering, suggesting their potential to enhance TB disease progression and transmission in this setting. Targeted interventions addressing these socio-behavioral risks within identified hotspots may improve TB control efforts.
Publisher
Research Square Platform LLC
Reference47 articles.
1. WHO. WHO. 2022 [cited 2023 Sep 5]. 2.1 TB incidence. https://www.who.int/teams/global-tuberculosis-programme/tb-reports/global-tuberculosis-report-2022/tb-disease-burden/2-1-tb-incidence.
2. Bagcchi S, WHO’s Global Tuberculosis Report 2022. The Lancet Microbe [Internet]. 2023 Jan 1 [cited 2023 Sep 5];4(1):e20. http://www.thelancet.com/article/S2666524722003597/fulltext.
3. Gyimah FT, Dako-Gyeke P. Perspectives on TB patients’ care and support: A qualitative study conducted in Accra Metropolis, Ghana. Global Health [Internet]. 2019 Mar 5 [cited 2024 Mar 25];15(1):1–9. https://globalizationandhealth.biomedcentral.com/articles/10.1186/s12992-019-0459-9.
4. Teibo TKA, Andrade RL, de Rosa P, Tavares RJ, Berra RBV, Arcêncio TZ. RA. Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review. BMC Public Health [Internet]. 2023 Dec 1 [cited 2024 Mar 25];23(1):1–10. https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-023-16493-y.
5. Wang L, Xu C, Hu M, Qiao J, Chen W, Li T et al. Spatio-temporal variation in tuberculosis incidence and risk factors for the disease in a region of unbalanced socio-economic development. BMC Public Health [Internet]. 2021 Dec 1 [cited 2024 Mar 25];21(1):1–11. https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-021-11833-2.