CORONAVIRUS SPATIAL BIG DATA PREDICTIVE ANALYSIS FOR THE SOUTHEAST ASIAN REGION

Abstract

The outbreak of the 2019 novel coronavirus disease (COVID-19) spread geospatially to more than 200 countries across the globe causing more than 12.39 mil people of the global population to be infected and 0.55 mil deaths (as of 10 July 2020), which is exponentially increasing and spreading in a spatiotemporal way to new geographical locations. This has led to a serious threat to human health and life, posing challenges to control the severity of the coronavirus spectrum. In the southeast Asian region, the outbreak of COVID-19 first arrived in Thailand on 13 January 2020, followed by South Korea on 20 January 2020, Vietnam and Taiwan on 22 January 2020, Hong Kong and Singapore on 23 January 2020, Malaysia on 25 January 2020, and Philippines on 30 January 2020, before reaching India on 31 January 2020. This has resulted in the imposition of national lockdowns / recommendations to control the outbreak of the coronavirus spectrum. The global spread of the coronavirus spectrum has highlighted the need for big data analysis to help decision makers in the design of lockdown measures. In this paper, coronavirus spatial big data predictive analysis has been carried out for the southeast Asian region along with countries located in different latitudes with varying populations from 4 to 150 mil where coronavirus
first reached 100, 1,000 and 5,000 reported cases. The coronavirus predictive models have been developed for different stages of the outbreak based on big data analysis of 5-day averaging of daily new coronavirus spectrum for these countries, which acts as knowledge classifier for predicting the trend of coronavirus spectrum for new geographical locations. In this paper, the impacts of latitude on mortality
(death per 1 mil populations) from coronavirus have also been discussed based on big data analysis to understand the alarming phase of the outbreak.
Keywords: 2019 novel coronavirus disease (COVID-19); spatial big data; southeast Asian region; predictive analysis; coronavirus spectrum model.

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