Poojar Basavaraj, Shenoy K Ashok, Naik Poonam R, Kamath Ashwin, Tripathy Jaya Prasad, Mithra P Prasanna, Chowta Mukta N, Badarudeen M N, Nagalakshmi Narasimhaswamy, Sharma Vivek, Shamanewadi Amrita N, Thekkur Pruthu
1Department of Pharmacology, Kasturba Medical College, Mangalore, Manipal Academy of Higher Education (MAHE), Manipal, Karnataka India.
2Department of Community Medicine, Yenepoya Medical College, Mangalore, Yenepoya (Deemed to be University), Mangalore, Karnataka India.
Trop Med Health. 2020 Mar 10;48:15. doi: 10.1186/s41182-020-00199-7. eCollection 2020.
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.
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 km with more than the expected count of DR-TB patients were constructed.
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.
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.
结核病呈现出异质性的空间分布模式，由于社区中存在人传人传播或潜伏感染因共同危险因素而重新激活，结核病病例存在地理聚集现象。在此方面，我们旨在评估2015年至2018年期间印度南部卡纳塔克邦选定地区向国家结核病规划（NTP）通报的耐多药结核病（DR-TB）患者的时空聚集情况。
这是一项对卡纳塔克邦达欣纳卡纳达、乌度皮和奇卡马古鲁地区通报的DR-TB患者进行的横断面研究。从治疗卡中提取临床人口统计学详细信息。使用谷歌地球对患者的登记地址进行地理编码（纬度和经度）。使用QGIS软件构建了点地图、热图和25公里的网格地图，其中DR-TB患者数量超过预期计数。
在总共研究的507名患者中，376名（74%）为男性，研究参与者的平均（标准差）年龄为41.4（13.9）岁。从2015年到2018年，患者数量从每年85例增加到209例，聚集面积（平方公里）从113.6增加到205.7，DR-TB患者数量超过预期（>1）的矩形网格数量从12个增加到47个。
DR-TB患者数量、聚集面积以及超过预期计数的网格数量增加令人担忧。NTP可以利用常规规划数据绘制地图，以识别疾病聚集区域，开展有针对性的结核病控制活动。
