Spatial mapping of acute diarrheal disease using GIS and estimation of relative risk using empirical Bayes approach

摘要: Abstract Background/objectives Diarrheal disease is one among the top five causes of death in low- and middle-income countries. It second leading cause children under years age. contributes to mortality nearly 1.5 million globally there are about two billion cases diarrheal diseases every year. In present study, we studied spatio-temporal pattern acute (ADD) ward-wise estimate compare widely used Bayesian models study measuring relative risk ADD Chennai Corporation, Tamilnadu, India. Materials methods Data on were obtained from Communicable hospital, Chennai, India 2009–11. Geographical Information System (GIS) technique was map data ward- wise estimated using empirical Bayes approach Poisson gamma log normal models. Results Over a period three 2009–11, 7661 reported Corporation. The cumulative incidence rate diarrhea 142.6 per 100,000 population ranging minimum 0 maximum 1699.7 Males had higher average 147.4 than females with 137.7 Also, age group 0–4 (306.8 cases) that any other category. Higher observed during months Apr–Jun (55.2 seasons. Choropleth indicates more prevailed northern part near coastal area which includes wards Tondiarpet, Basin bridge, Pulianthope zones. posterior identified 23, 30, 19 having significantly greater 1 for 2009, 2010, 2011, respectively. Fitting standardized morbidity ratio (SMR) showed that, consistently Tondiarpet ward highest all (relative (95% credible interval) based SMR, 13.3 (11.6, 15.2), 13.0 (11.3, 14.8), (11.5, 15.1) 2009 8.0 (6.9, 9.2), 7.8 (6.7, 8.9), 9.1) 2010 19.6 (17.0, 22.3), 19.0 (16.5, 21.7), 19.5 (16.9, 22.1) Conclusion GIS mapping 2009–11 area. Thus estimation would help us accurate despite small observations take precautionary measure prevent control spread disease.