tetano
Editor, Senior Moderator
Comput Math Methods Med
. 2022 Jan 18;2022:4168619.
doi: 10.1155/2022/4168619. eCollection 2022.
VSHR: A Mathematical Model for the Prediction of Second-Wave COVID-19 Epidemics in Malaysia
Xiang Yu[SUP] 1 [/SUP], Lihua Lu[SUP] 1 [/SUP], Jiangfan Guo[SUP] 1 [/SUP], Haihuan Qin[SUP] 1 [/SUP], Chunlei Ji[SUP] 1 [/SUP]
Affiliations
Abstract
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 2[SUP]nd[/SUP], 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.
. 2022 Jan 18;2022:4168619.
doi: 10.1155/2022/4168619. eCollection 2022.
VSHR: A Mathematical Model for the Prediction of Second-Wave COVID-19 Epidemics in Malaysia
Xiang Yu[SUP] 1 [/SUP], Lihua Lu[SUP] 1 [/SUP], Jiangfan Guo[SUP] 1 [/SUP], Haihuan Qin[SUP] 1 [/SUP], Chunlei Ji[SUP] 1 [/SUP]
Affiliations
- PMID: 35087601
- PMCID: PMC8789418
- DOI: 10.1155/2022/4168619
Abstract
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 2[SUP]nd[/SUP], 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.