Spatial Distribution Pattern of Covid-19 Cases and Their Characteristics In DKI Jakarta and Surrounding Areas
Dwi Nowo Nowo Martono(1*), Halvina Grasela Saiya(2)
(1) School of Environmental Science, Universitas Indonesia, Indonesia.
(2) School of Environmental Science, Universitas Indonesia, Indonesia.
(*) Corresponding Author
Abstract
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.
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DOI: https://doi.org/10.22146/ijg.90542
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Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)
ISSN 2354-9114 (online), ISSN 0024-9521 (print)
IJG STATISTIC