Jumadi Jumadi, Vidya N. Fikriyah, Hamim Z. Hadibasyir, Muhammad I. T. Sunariya, Kuswaji D. Priyono, Noor A. Setiyadi, Steve J. Carver, Paul D. Norman, Nick S. Malleson, Arif Rohman, Aynaz Lotfata
During the first year of the COVID-19 pandemic in Jakarta, Indonesia, the government designated some hospitals as specific COVID-19 healthcare centers to meet demand and ensure accessibility. However, the policy demand evaluation was based on a purely spatial approach. Studies on accessibility to healthcare are widely available, but those that consider temporal as well as spatial dynamics are lacking. This study aims to analyze the spatiotemporal dynamics of healthcare accessibility against COVID-19 cases within the first year of the COVID-19 pandemic, and the overall pattern of spatiotemporal accessibility. A two-step floating catchment area (2SFCA) was used to analyze the accessibility of COVID-19 healthcare against the monthly data of the COVID-19 infected population, as the demand. Such a spatiotemporal approach to 2SFCA has never been used in previous studies. Furthermore, rather than the traditional buffer commonly used to define catchments, the 2SFCA in this study was improved with automated delineation based on the road network using ArcGIS Service Areas Analysis tools. The accessibility tends to follow the distance decay principle, which is relatively high in the city’s center and low in the outskirts. This contrasts with the city’s population distribution, which is higher on the outskirts and lower in the center. This research is a step toward optimizing the spatial distribution of hospital locations to correspond with the severity of the pandemic condition. One method to stop the transmission of disease during a pandemic that requires localizing the infected patient is to designate specific healthcare facilities to manage the sick individuals. ‘What-if’ scenarios may be used to experiment with the locations of these healthcare facilities, which are then assessed using the methodology described in this work to obtain the distribution that is most optimal. © 2022 by the authors.
Faculty of Geography, Universitas Muhammadiyah Surakarta, Surakarta, 57162, Indonesia; Department of Public Health, Faculty of Health, Universitas Muhammadiyah Surakarta, Surakarta, 57162, Indonesia; Centre for Spatial Analysis & Policy, School of Geography, University of Leeds, Leeds, LS2 9JT, United Kingdom; Geomatic Engineering, Institut Teknologi Sumatera, Kabupaten Lampung Selatan, 35365, Indonesia; Department of Geography, Chicago State University, Chicago, 60628, IL, United States
Research at a Glance
Register to unlock
Topics & SDG Alignment
Register to unlock
Collaboration
Register to unlock
Author Profile (Selected)
Register to unlock
References Overview
Register to unlock
Journal & Source
Register to unlock
Metadata & Integrity
Register to unlock