A correlation study for determination risk area of dengue fever and dengue hemorrhagic fever: a case study of Sisaket province, Thailand

Abstract

This study has purpose on analyzing dengue fever and dengue hemorrhagic fever (DF/DHF) risk zone area in Sisaket province, Thailand, by using the subdistrict-level (Tumbon) data in sick ratio, average temperature, maximum temperature, minimum temperature, relative humidity, precipitation, population density, and housing density. The meteorological data are acquired from POWER, NASA. The data is stored in points, griding by 30 minutes of latitude and longtitude, going through the inverse distance weighting tool to interpolate the meteorological data into each Tumbon. The physical socio data are from government authority, are population from each Tumbon by monthly and housing amount from each Tumbon by yearly. Correlation analysis is used to find the correlation between sick ratio and other variables to find the risk area in the study area. Hot spots analysis (Getis ord-Gi*) is used to find the clustering area of sick ratio among each Tumbon. Results are classified into cluster maps and risk zone maps, each by yearly and monthly.