Spatial Dynamics of COVID-19 in Malaysia

Introduction: Understanding infectious disease transmissibility in the context of “place” is crucial for implementing disease control and harm reduction strategies. This study was aimed to determine the dynamics of spatial dispersion of COVID-19 in Malaysia and its associated indicators. Methodology: This ecological study included all active COVID-19 cases between 22nd January 2021 and 4th February 2021 using secondary data from multiple sources. Incidence, Bayesian incidence, global and local Moran indices were calculated. A geographical weighted regression (GWR) analysis in addition to ordinary least squares regression (OLS) was executed to assess the relationships between incidence of COVID-19 with population level socio-economic and health coverage indicators. All analyses were conducted using SPSS and Geo Da software.  Results: A total of 51,476 cases were included in the analysis. The global Moran's index of incidence rate was 0.499 (P=0.01), indicative of positive spatial autocorrelation with high standards between districts and regions. The Local Indicators of Spatial Association (LISA) maps identified spatial clusters, particularly the main high-high patterns in Central and Southern regions, and low-low concentrated districts in Northern and Borneo regions of Malaysia. The GWR yielded average income per capita and population density as two crucial population level indicators of COVID-19 dispersion in Malaysia (P<0.001). Discussion: Incidence cases were highly clustered within the Central Region of Malaysia, configuring that propagation occurs rapidly in highly populous places.1 The significantly positive indicator of population density yielded via GWR confirmed this association, consistent with a study from Brazil.2 ➢ Average income per capita was significantly associated with incidence cases. Within metropolitans with rapid economic activities, it could be anticipated higher income per capita to facilitate population access in carrying out greater number of diagnostic tests, thus reporting cases escalation. Whereas districts with socioeconomic vulnerabilities reverberates prevention and control measures. Conclusion: The dispersion of COVID-19 in Malaysia was significantly associated with socio-economic indicators; average income per capita and population density. [Disclaimer: Abstract text might vary slightly from what is displayed in the e-poster]