Spatiotemporal analysis of drug-resistant TB patients registered in selected districts of Karnataka, South India: a cross-sectional study
| Autor: | Ashwin Kamath, Poonam R. Naik, Basavaraj Poojar, Pruthu Thekkur, Narasimhaswamy Nagalakshmi, Jaya Prasad Tripathy, Amrita N. Shamanewadi, Vivek Sharma, K Ashok Shenoy, M. N. Badarudeen, Prasanna Mithra, Mukta N Chowta |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Tuberculosis
lcsh:Arctic medicine. Tropical medicine 020205 medical informatics Cross-sectional study lcsh:RC955-962 02 engineering and technology law.invention 03 medical and health sciences 0302 clinical medicine Kilometer law Environmental health 0202 electrical engineering electronic engineering information engineering medicine 030212 general & internal medicine Risk factor Geographic mapping Drug-resistant tuberculosis Spatiotemporal Analysis Drug resistant tuberculosis Research Public Health Environmental and Occupational Health Spatial analysis Spatial epidemiology medicine.disease GIS Infectious Diseases Geography Transmission (mechanics) Spatial heterogeneity |
| Zdroj: | Tropical Medicine and Health Tropical Medicine and Health, Vol 48, Iss 1, Pp 1-10 (2020) |
| ISSN: | 1349-4147 1348-8945 |
| Popis: | Background Tuberculosis (TB) depicts heterogeneous spatial patterns with geographical aggregation of TB cases due to either ongoing person-to-person transmission or reactivation of latent infection in a community sharing risk factor. In this regard, we aimed to assess the spatiotemporal aggregation of drug-resistant TB (DR-TB) patients notified to the national TB program (NTP) from 2015 to 2018 in selected districts of Karnataka, South India. Methods This was a cross-sectional study among DR-TB patients notified from Dakshina Kannada, Udupi, and Chikamagalur districts of the state of Karnataka. Clinico-demographic details were extracted from treatment cards. The registered addresses of the patients were geocoded (latitude and longitude) using Google Earth. Using the QGIS software, spot map, heat maps and grid maps 25 km2 with more than the expected count of DR-TB patients were constructed. Results Of the total 507 patients studied, 376 (74%) were males and the mean (standard deviation) age of the study participants was 41.4 (13.9) years. From 2015 to 2018, the number of patients increased from 85 to 209 per year, the area of aggregation in square kilometers increased from 113.6 to 205.7, and the number of rectangular grids with more than the expected DR-TB patients (> 1) increased from 12 to 47. Conclusions The increase in the number of DR-TB patients, area of aggregation, and grids with more than the expected count is a cause for concern. The NTP can use routine programmatic data to develop maps to identify areas of aggregation of disease for targeted TB control activities. |
| Databáze: | OpenAIRE |
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