Prediction mapping of human leptospirosis using ANN, GWR, SVM and GLM approaches.

ABSTRACT: BACKGROUND:Recent reports of the National Ministry of Health and Treatment of Iran (NMHT) show that Gilan has a higher annual incidence rate of leptospirosis than other provinces across the country. Despite several efforts of the government and NMHT to eradicate leptospirosis, it remains a public health problem in this province. Modelling and Prediction of this disease may play an important role in reduction of the prevalence. METHODS:This study aims to model and predict the spatial distribution of leptospirosis utilizing Geographically Weighted Regression (GWR), Generalized Linear Model (GLM), Support Vector Machine (SVM) and Artificial Neural Network (ANN) as capable approaches. Five environmental parameters of precipitation, temperature, humidity, elevation and vegetation are used for m

SUBMITTER: Mohammadinia A 

PROVIDER: S-EPMC6854714 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature