Identifying Hotspots of People Diagnosed of Tuberculosis with Addiction to Alcohol, Tobacco, and Other Drugs through a Geospatial Intelligence Application in Communities from Southern Brazil

Abstract

(1) Background: tuberculosis (TB) is considered one of the leading causes of death worldwide by a single infectious agent. This study aimed to identify hotspots of people diagnosed with tuberculosis and abusive use of alcohol, tobacco, and other drugs in communities through a geospatial intelligence application; (2) Methods: an ecological study with a spatio-temporal approach. We considered tuberculosis cases diagnosed and registered in the Notifiable Diseases Information System, which presented information on alcoholism, smoking, and drug abuse. Spatial Variations in Temporal Trends (SVTT) and scan statistics were applied for the identification of Hotspots; (3) Results: between the study period, about 29,499 cases of tuberculosis were reported. When we applied the SVTT for alcoholism, three Hotspots were detected, one of which was protective (RR: 0.08–CI95%: 0.02–0.32) and two at risk (RR: 1.42–CI95%: 1.11–1.73; RR: 1.39–CI95%: 1.28–1.50). Regarding smoking, two risk clusters were identified (RR: 1.15–CI95%: 1.01–1.30; RR: 1.68–CI95%: 1.54–1.83). For other drugs, a risk cluster was found (RR: 1.13–CI95%: 0.99–1.29) and two protections (RR: 0.70–CI95%: 0.63–0.77; RR: 0.76–CI95%: 0.65–0.89); (4) Conclusion: it was evidenced that in the communities being studied, there exists a problem of TB with drug addiction. The disordered use of these substances may harm a person’s brain and behavior and lead to an inability to continue their treatment, putting the community at further risk for TB.

Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review

“…The result points to the presence of vulnerable populations in specific territories affecting people of specific socioeconomic status (social determinants of health). This points to specific locations having high TB prevalence and this is in support [ 17 ] that evidenced that TB burden was associated with specific communities, evidencing three high-risk detected in the Northwest, Northcentral and Metropolitan regions. In this sense, the high-risk were concentrated in the northern region (66.7%) similar to our study.…”

Geospatial Health (GeoHealth): Current Trends, Methods, and Applications

“…Among the two studies on tuberculosis in this Special Issue, Yu et al analyzed the diagnostic performance of QFG-GIT and the need for personalized cutoff values in diagnosis [ 10 ], while Scholze et al reported the hotspot regions with tuberculosis and alcohol, tobacco, and other drugs in southern Brazil using a geospatial intelligence application. The evidence suggested the existence of an association between tuberculosis and drug addiction within the investigated hotspot regions [ 11 ]. The use of geospatial videos to map environments with cholera risk in Congo was conducted by Curtis et al, highlighting the use of data science and machine learning to detect infectious diseases in health-risk regions [ 12 ].…”