Spatial analysis of COVID-19 outbreak to assess the effectiveness of social restriction policy in dealing with the pandemic in Jakarta. (November 2021)

• Record Type: Journal Article
• Authors: Pribadi, Didit Okta; Saifullah, Khalid; Putra, Andi Syah; Nurdin, Muhammad; Iman, La Ode Syamsul; Rustiadi, Ernan
• Is Part Of: Spatial and spatio-temporal epidemiology. Volume 39(2021)
• Publication Date: 2021-11
• Subjects: COVID-19 -- Large scale social restriction (LSSR) -- Jakarta -- Emerging hot spot analysis -- Scan statistic -- Geographical weighted regression; Epidemiology -- Statistical methods -- Periodicals; Epidemiology -- Periodicals; 614.4072
• DOI: 10.1016/j.sste.2021.100454
• Languages: English
• ISSNs: 1877-5845

Abstract

Abstract: Coronavirus disease 2019 (COVID-19) has been spread globally and brought health and socioeconomic issues. Jakarta tried to accommodate health and economic interests through the Large-Scale Social Restriction (LSSR) policy that should be assessed. This study aims to (1) visualize the spatial patterns of confirmed Covid-19 cases and the locations of potential risk of transmission, and (2) determine the spatial processes underlying the spatial patterns of Covid-19 cases. The emerging hot spot analysis and space-time scan statistic were employed to analyze the dynamic of infected cases and transmission risk. A Geographical Weighted Regression (GWR) model was developed to define factors that influence the spatial transmission. The result shows that spatial transmission keeps continuing, despite a decline in the aggregate pandemic curve during LSSR implementation. This was likely affected by settlements types and population density distribution, and transportation networks. Spatial analysis supports the aggregate pandemic curve to increase the pandemic surveillance effectiveness.