Drug-Resistant Tuberculosis Hotspots in Eastern Cape, South Africa
Author Information
Author(s): Faye Lindiwe Modest, Hosu Mojisola Clara, Apalata Teke
Primary Institution: Walter Sisulu University
Hypothesis
This study aimed to assess DR-TB transmission patterns and predict future cases using geospatial and predictive modeling techniques.
Conclusion
The study highlights the need for targeted interventions in vulnerable populations to curb DR-TB transmission and improve treatment outcomes.
Supporting Evidence
- DR-TB incidence was 11.89 cases per 100,000 population.
- Key risk factors included poverty, lack of education, and occupational exposure.
- Spatial analysis revealed significant clustering in socio-economically disadvantaged areas.
- The Linear Regression model predicts a continued decline to zero cases by 2026.
- The Random Forest model forecasts stabilization to around 30–50 cases annually after 2021.
Takeaway
This study looked at where drug-resistant tuberculosis is spreading in a specific area of South Africa and how to stop it.
Methodology
A retrospective cross-sectional study was conducted across five decentralized DR-TB facilities from January 2018 to December 2020, using patient GPS coordinates for clustering analysis.
Potential Biases
Potential biases may arise from the retrospective nature of the study and reliance on existing patient records.
Limitations
The study is limited to a specific geographic area and may not be generalizable to other regions.
Participant Demographics
56.1% males and 43.9% females, mean age 37.5 years.
Statistical Information
P-Value
0.000035
Confidence Interval
−9.30 to −9.21
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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