Bayesian kriging of tuberculosis in Chennai: A small scale analysis.

Srinivasan, R.; Venkatesan, P

Indian Journal of Applied Research; 2013; 3; 480-482.     

Abstract: Bayesian Kriging would be more appropriate in the case of tuberculosis risk where we know that other factors are strong predictors. Kriging the residuals and adding the predicted residuals to the model predictions produce predictions that are closer to the observed SMR in each ward. Kriging method used to extrapolate the location from unmeasured locations. The aim is to study the spatial pattern of tuberculosis within a Chennai ward population to gain insight into the disease spread and also, to extrapolate the location from the unmeasured locations. SAS software was used for spatial analysis of tuberculosis spread. Data was obtained from National Institute for Research in Tuberculosis for Chennai district. The location of the each case was geographically marked through their co-ordinates in the Chennai map. Kriging were used to extrapolate the location from the unmeasured locations. The results of the spread of tuberculosis in chennai ward has been diverse, with many wards having a low rate of infection and the epidemic being most extreme in slum areas. Spatial analysis is proved to be more useful for studying spread of Tuberculosis analysis and modeling of disease prediction.

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