Abstract
IntroductionThe unprecedented COVID-19 pandemic has greatly affected human health and socioeconomic backgrounds. This study examined the spatiotemporal spread pattern of the COVID-19 pandemic in Malaysia from the index case to 291,774 cases in 13 months, emphasizing on the spatial autocorrelation of the high-risk cluster events and the spatial scan clustering pattern of transmission.MethodologyWe obtained the confirmed cases and deaths of COVID-19 in Malaysia from the official GitHub repository of Malaysia's Ministry of Health from January 25, 2020 to February 24, 2021, 1 day before the national vaccination program was initiated. All analyses were based on the daily cumulated cases, which are derived from the sum of retrospective 7 days and the current day for smoothing purposes. We examined the daily global, local spatial autocorrelation and scan statistics of COVID-19 cases at district level using Moran's I and SaTScan™.ResultsAt the initial stage of the outbreak, Moran's I index > 0.5 (p < 0.05) was observed. Local Moran's I depicted the high-high cluster risk expanded from west to east of Malaysia. The cases surged exponentially after September 2020, with the high-high cluster in Sabah, from Kinabatangan on September 1 (cumulative cases = 9,354; Moran's I = 0.34; p < 0.05), to 11 districts on October 19 (cumulative cases = 21,363, Moran's I = 0.52, p < 0.05). The most likely cluster identified from space-time scanning was centered in Jasin, Melaka (RR = 11.93; p < 0.001) which encompassed 36 districts with a radius of 178.8 km, from November 24, 2020 to February 24, 2021, followed by the Sabah cluster.Discussion and ConclusionBoth analyses complemented each other in depicting underlying spatiotemporal clustering risk, giving detailed space-time spread information at district level. This daily analysis could be valuable insight into real-time reporting of transmission intensity, and alert for the public to avoid visiting the high-risk areas during the pandemic. The spatiotemporal transmission risk pattern could be used to monitor the spread of the pandemic.
Highlights
The unprecedented COVID-19 pandemic has greatly affected human health and socioeconomic backgrounds
We investigated the spatiotemporal clustering pattern of COVID-19 cases in Malaysia the district-level daily spatial autocorrelation of COVID-19 cases and identified spatiotemporal clusters of COVID-19 in Malaysia
A total of 291,774 confirmed COVID-19 cases and 1,093 COVID-19 deaths were reported from January 25, 2020 to February 24, 2021
Summary
The unprecedented COVID-19 pandemic has greatly affected human health and socioeconomic backgrounds. Coronavirus disease 2019 (COVID-19) which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first detected in Wuhan, China in December 2019. Until 4 November 2021, the pandemic COVID-19 has surpassed 248 million cases and 5 million deaths worldwide [1] with an estimated reproduction number or R0 value of 1.70 (SD = 0.57) [2]. The total deaths due to COVID-19 have surpassed those of the Middle East respiratory syndrome (MERS) and severe acute respiratory syndrome (SARS), and the majority of the dead were elderly with history of comorbidities such as hypertension, diabetic, obese, and heart disease [3]. The second wave of the pandemic from February 27 till end of August resulted 9,340 confirmed cases and 127 deaths [12], which were mainly due to a religious mass gathering of an estimated 14,500 local and 1,500 overseas attendees in Sri Petaling, Selangor from February 27 to March 3, 2020 [10, 13, 14]. Malaysia experienced zero cases during the period of July 1, 2020 [15]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
