Spatio-temporal patterns of dengue hemorrhagic fever (DHF) cases with local indicator of spatial association (LISA) and cluster map at areas risk in Java-Bali Indonesia

Abstract

Spatial analysis is used to analyze the correlation between endemic dengue areas (geographical location) and DHF incidence. The measure of the correlation is determined using spatial autocorrelation, global index, and Moran’s index (Moran’s I). Moran’s index is a global index used to determine the absence/ presence of spatial autocorrelation in disease transmission. However, it does not provide information on spatial patterns in certain areas (it merely globally represents spatial autocorrelation). For that reason, Local indicator of spatial association (LISA) is required. In addition to being able to determine local index used to evaluate the tendency of the presence of local spatial clustering, LISA enables to indicate spatial autocorrelation. The LISA for each observation gives an indication of the extent of significant spatial clustering of similar values around that observation. Based on the results of LISA, the mapping was conducted using LISA cluster map. Spatial autocorrelation of LISA can be classified into four spatial autocorrelations, including high-high (H-H), low-low (L-L), high-low (H-L), low-high (L-H). The present study seeks to determine the mapping of DHF and distribution patterns of DHF cases in Java and Bali using LISA and LISA cluster map. Data include those of the number of DHF sufferers in Java and Bali, while the source of data involves the Data Center and Information of Ministries of the Republic of Indonesia. The mapping was carried out with observational units every month. This article maps and identifies DHF for January, June, August, and November.