PREDICTION OF JAPANESE ENCEPHALITIS VECTORS IN KURNOOL DISTRICT OF ANDHRA PRADESH, INDIA BY USING BAYESIAN NETWORK

Abstract

Japanese encephalitis (JE), a complex viral disease transmitted by mosquitoes. Determination of vector (mosquito) density is a prerequisite for devising effective control measures against this disease. Bayesian network is a widely used tool that has recently found application in the epidemiological surveillance studies. This article describes the application of Bayesian network tool to predict the Japanese encephalitis vector density using the longitudinal data collected from the Kurnool district of Andhra Pradesh, India, from 2001 to 2006. The entomological parameter from the study area indicates that various contributing factors are responsible for the prevalence of these vectors, making it difficult to estimate the importance of any particular parameter contributing to the increase of vector density. The application of this approach resulted in 73.12% to 95.12% accuracy compared to the test data with the corrected data.

The authors are grateful to Director, IICT for his encouragement and support. The authors are thankful to the Indian Council of Medical Research (ICMR), New Delhi, for sponsoring and supporting the project.