VSHR: A Mathematical Model for the Prediction of Second-Wave COVID-19 Epidemics in Malaysia
Author(s) -
Xiang Yu,
Lihua Lü,
Jiangfan Guo,
Haihuan Qin,
Chunlei Ji
Publication year - 2022
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2022/4168619
Subject(s) - covid-19 , pandemic , geography , computer science , econometrics , virology , outbreak , medicine , mathematics , infectious disease (medical specialty) , disease , pathology
Since December 2019, a novel coronavirus (COVID-19) has spread all over the world, causing unpredictable economic losses and public fear. Although vaccines against this virus have been developed and administered for months, many countries still suffer from secondary COVID-19 infections, including the United Kingdom, France, and Malaysia. Observations of COVID-19 infections in the United Kingdom and France and their governance measures showed a certain number of similarities. A further investigation of these countries’ COVID-19 transmission patterns suggested that when a turning point appeared, the values of their stringency indices per population density (PSI) were nearly proportional to their absolute infection rate (AIR). To justify our assumptions, we developed a mathematical model named VSHR to predict the COVID-19 turning point for Malaysia. VSHR was first trained on 30-day infection records prior to the United Kingdom, Germany, France, and Belgium’s known turning points. It was then transferred to Malaysian COVID-19 data to predict this nation’s turning point. Given the estimated AIR parameter values in 5 days, we were now able to locate the turning point’s appearance on June 2nd, 2021. VSHR offered two improvements: (1) gathered countries into groups based on their SI patterns and (2) generated a model to identify the turning point for a target country within 5 days with 90% CI. Our research on COVID-19’s turning point for a country is beneficial for governments and clinical systems against future COVID-19 infections.
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