Geospatial approach to accessibility of referral hospitals using geometric network analysts and spatial distribution models of covid-19 spread cases based on gis in bekasi city, west java

Abstract

Bekasi City has a high population density, as seen from its growth rate in 2020. Therefore, geospatial analysis is required to support and provide effective and efficient health services, evaluate the need for referral hospital capacity, and minimize the spread of COVID-19 cases in this city. The geospatial methods used in this study are Geometric Network Analyst and Geographic Weighted Regression (GWR), with Service Area (SA) used for analysis. The results based on the distance between the referral hospitals and settlements in Bekasi City showed that more than 2.201 million people, or 90%, have been well covered. Meanwhile, regarding travel time, 1.792 million people or 73% in eight sub-districts are in wellserved areas. Conversely, referral hospitals do not cover four sub-districts, namely Bantar Gebang, Jati Sampurna, Medan Satria, and Jati Asih. The spatial modeling analysis results using GWR with spatialtemporal data recapitulation of data reports for eight months showed predictions for the spread of confirmed cases in six sub-districts, namely West Bekasi, North Bekasi, East Bekasi, Medan Satria, Mustika Jaya, and Rawalumbu. This implies that local governments need to suggest more referral hospitals serving people who live far from the existing referral hospitals.

Quantitative Study on American COVID-19 Epidemic Predictions and Scenario Simulations

“…Geography has an essential contribution to COVID-19 epidemic research [23], which is reflected in four aspects-the spread of the pandemic, social management, public behavior, and impacts of the pandemic. Some geographical models have been widely used in the prediction of COVID-19, such as the GWR model [24][25][26], the GTWR model [27][28][29], and the MGWR model [24]. In addition, geographic models have long been used to predict infectious diseases, such as the GWR model in Schistosoma haematobium [30], human leptospirosis [31], Dengue Fever [32], leptospirosis [33], GTWR in Porcine Reproductive and Respiratory Syndrome [34], MGWR in tropical parasitic diseases [35].…”