COVID-19 Pandemic in Urban Environment and Household Population: An Exploratory Spatial Risk Analysis in Selangor, Malaysia

Abstract

Malaysia faced the COVID-19 epidemic which had a huge impact on the community and environmental health in 2020. This paper was conducted to perform exploratory analysis on the feasible factors influencing the COVID-19 pandemic in Selangor using Geographical Information System (GIS) techniques. Two central objectives were carried out, specifically: i) to analyse the spatial-temporal distribution of COVID-19 cases by months and districts in the state; and ii) to identify the environmental factors that contribute to the increase of COVID-19 cases, including population, housing, urbanisation, gradient, and industrial area. Natural break classification method in ArcGIS was used to produce the COVID-19 map and analysis, followed by the possible correlation between the cases, and selected risk factors were determined using correlation analysis. Every district had experienced the pandemic, especially in the populous and urbanised district of Petaling and Klang. The cases rose in the last three months of 2020 namely October, November, and December. Although there were no dominant factors shaping the increasing cases as the correlation strength was mostly moderate and low trends, the number of population was suggested as the main local factor as there was a moderately strong correlation (r=0.56) due to uncontrolled human movements and crowded conditions in certain areas. GIS has also demonstrated its methodological capabilities and responsive planning to spot the spatial distribution and correlation of COVID-19 cases with the potential risk factors.