Identification of Spatial Patterns of Community Health Centers and Health Disasters: Learning from the Covid-19 Pandemic in Magelang District, Central Java, Indonesia

Abstract

Regional development in an area will have consequences for the health status of the surrounding community. This paper discusses the adequacy of community health center (CHC) facilities in taking an important role in managing health disasters such as the Covid-19 pandemic. Covid-19 is one of the most infectious environmental-based diseases. The research objective was to spatially identify the availability of CHC and their relationship to Covid-19 cases during the pandemic. Ecological studies are used with a spatial approach. The population in this study were all sub-districts in Magelang District with a total sampling. Spatial analysis makes use of the QGIS and Geoda applications. The results showed that there was grouped spatial autocorrelation (Moran's I = 0.089, Io = 0.05) between CHC in Magelang. Covid-19 in Magelang residents has a positive autocorrelation with CHC (Moran's I = 0.248, Io = 0.05) and forms a cluster pattern. The spatial lag regression further clarifies that there is a spatial autocorrelation between the two variables (Coef: -0.175; p value= 0.569), and the Covid-19 variable has a significant influence on the CHC (p=0.0022). Analysis using the Local Indicator Spatial Association (LISA) method found that Ngluwar Sub-district is in the High-High quadrant, while Mungkid Sub-district is in the Low-High quadrant and the other sub-districts are not significant. Spatial pattern heterogeneity is formed in CHC and there is a spatial autocorrelation relationship between Covid-19 cases and CHC. Systematic planning is needed to overcome the adequacy of the CHC to help improve the quality of public health.