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Exploratory spatial data analysis (Esda) on covid-19 cases in malaysia
Jurnal Teknologi ; 83(6):83-94, 2021.
Article in English | Scopus | ID: covidwho-1575993
ABSTRACT
The Malaysian government implemented The Movement Control Order (MCO) on 18 March 2020 to control the spread of the COVID-19 outbreak. However, the third wave that started in September 2020 during the Recovery Movement Control Order (RMCO) phase saw a continuous increase in the number of cases. In this study, the exploratory spatial data analysis (ESDA) was used to analyse the existence of COVID-19 spatial clusters. Moran's index was used to map the spatial autocorrelation (cluster) to showcase the spreading patterns of the COVID-19 pandemic in Malaysia. The study results indicated significant changes in the COVID-19 hotspots over time. At the beginning of 2020, the state of Selangor and Sarawak were the first locality to become a significant COVID-19 hotspot. Furthermore, this research showed all affected areas during the study period. Overall, a non-random distribution of COVID-19 occurrences was detected, thus suggesting a positive spatial autocorrelation. Many parties are affected by the COVID-19 pandemic, especially those involved in healthcare provision, financial assistance allocation, and law enforcement. Other sectors such as the economy, education, and religion are also affected. Therefore, the findings from this study will provide useful information to all the related governmental and private agencies, as well as policymakers and researchers. © 2021 Penerbit UTM Press. All rights reserved.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Jurnal Teknologi Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Jurnal Teknologi Year: 2021 Document Type: Article