AI Article Synopsis
- The study aimed to assess and compare tuberculosis (TB) prevalence rates across districts in Tamil Nadu using data from two rounds of the National Family Health Survey (2014-2015 and 2019-2021).
- Researchers employed spatial analysis tools to visualize and identify areas with high TB prevalence, leveraging software like SPSS, QGIS, and Geoda.
- The findings revealed a notable decline in TB prevalence over the years, providing critical insights for health officials to target interventions effectively in high-prevalence zones.
Article Abstract
Background: The objective of the current study was to estimate the self-reported individual-level crude prevalence and cluster-level adjusted prevalence of TB for the districts of Tamil Nadu and to understand the spatial distribution of TB cases through spatial autocorrelation and hotspot analysis.
Methods: National Family Health Survey (NFHS) data, gathered during 2014-2015 (NFHS-4) and 2019-2021 (NFHS-5), were used in the current study to estimate district-wise, individual-level crude and cluster-level adjusted TB prevalence per 100 000 population in Tamil Nadu. This was illustrated with the help of spatial geographic representation for various districts of Tamil Nadu using SPSS and QGIS software. The spatial autocorrelation and hotspot analysis were performed using Geoda software.
Results: The overall self-reported individual-level crude prevalence of TB was 337 (95% CI 302 to 375) and 169 (95% CI 144 to 197) per 100 000 population, whereas the cluster-level adjusted prevalence of TB was 356 (95% CI 311 to 405) and 184 (95% CI 154 to 219) per 100 000 population in NFHS-4 and NFHS-5, respectively.
Conclusions: This study highlights those geographical areas with high rates of TB prevalence. This information would be useful for the state and district programme managers to identify areas of high TB prevalence where interventions can be focused.
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| http://dx.doi.org/10.1093/inthealth/ihae072 | DOI Listing |
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