Spatial Distribution Pattern of Covid-19 Cases and Their Characteristics In DKI Jakarta and Surrounding Areas - Martono, Dwi Nowo Nowo; Saiya, Halvina Grasela (Indonesian Journal of Geography, 2024)
The COVID-19 pandemic has significantly affected various countries worldwide, including Indonesia. This study specifically examines the spatial distribution pattern of COVID-19 cases among sub-districts in DKI Jakarta and its neighboring areas. The study investigates the impact of spatial characteristics such as building density, population density, road network connectivity, and accessibility, as well as infrastructure completeness. A spatial regression model was employed to analyze the influence and pattern of COVID-19 case distribution among sub-districts. Spatial modeling indicates that geographic location has an effect on the data, often referred to as the autocorrelation effect. Moran’s Index was used to test the relationship between district locations and the number and growth rate of cases.The study findings reveal a positive spatial autocorrelation in the growth rate pattern of COVID-19 cases among sub-districts and clusters in DKI Jakarta and its surrounding areas. The spatial regression model, specifically the Spatial Autoregressive Model (SAR), identifies road connectivity, number of health centers, building density, and population density as spatial variables that significantly influence the rate of COVID-19 cases.