ABSTRACT

Background and objectives: Extra Pulmonary Tuberculosis (EPTB) is one of the most important bacterial diseases caused by Mycobacterium tuberculosis. It includes any organ of the body viz., bronchus, larynx, lungs, pleura, intrathoracic bronchopulmonary lymph nodes, abdominal sites, joints, bones, CNS, pericardial cavity, kidneys, and urogenital tract. The spectrum of the EPTB ranges in different proportions at different organs and remains dormant for years at a specific site before disease expression. The directly observed treatment of shortterm (DOTS) is a rapid expansion of EPTB that comes under the revised national tuberculosis control programme (RNTCP) all over India and Karnataka in the past decades. The present study aims at identifying the magnitude, incidence, hot spots and diversity of the disease with the consortium of GIS tool with the statistics of EPTB for the year 2011-16. Methods: Some of the records show the individual reports of EPTB in DOTS centres. Identification of hotspots and extent of diversity are explored using Arc-GIS 10.2.2 software. Spatial autocorrelation analysis and spatial pattern analysis was performed to detect the geographic basis for the occurrence of the disease. Results: Record of the RNTCP against the pulmonary and extrapulmonary disease has revealed the TB situation in Karnataka as one of the trounce in the State. Mysore is the major district of Karnataka facing incalculable problems. The number of reported EPTB in Mysore city is about 50-75 cases per month according to the district tuberculosis centre (DTC). Most of the reported cases convey males aged 45 and above showed drastic growth in EPTB in recent years. From 2011-16, EPTB in Mysore City accounts for 1,835 cases, the highest incidence in Nanjangud (642), Heggadadevanakote (508), Tirumakudalu Narasipura (538) Krishnarajanagara (415) and least in Hunsur (221) and Piriyapatna (225). Conclusion: The spatial autocorrelation analysis was found effective for further focus on improving the socio-economic status and targeting the hot spot region with health care measures. This adds up to the existing scientific scenario and can be extrapolated to any other disease assessment of public health. Keywords: Extra Pulmonary Tuberculosis Incidence, GIS Software, Spatial Autocorrelation, Interpolation, Temporal analysis
Publication date: 01/09/2021

https://ijbpas.com/pdf/2021/September/MS_IJBPAS_2021_5631.pdf

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https://doi.org/10.31032/IJBPAS/2021/10.9.5631