VSHR: A Mathematical Model for the Prediction of Second-Wave COVID-19 Epidemics in Malaysia
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 th...
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description | 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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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.</description><identifier>ISSN: 1748-670X</identifier><identifier>EISSN: 1748-6718</identifier><identifier>DOI: 10.1155/2022/4168619</identifier><identifier>PMID: 35087601</identifier><language>eng</language><publisher>United States: Hindawi</publisher><subject>Algorithms ; Belgium - epidemiology ; Computational Biology ; Computer Simulation ; COVID-19 - epidemiology ; COVID-19 - transmission ; Epidemics - statistics & numerical data ; Epidemiological Models ; France - epidemiology ; Germany - epidemiology ; Humans ; Malaysia - epidemiology ; SARS-CoV-2 ; United Kingdom - epidemiology</subject><ispartof>Computational and mathematical methods in medicine, 2022-01, Vol.2022, p.4168619-9</ispartof><rights>Copyright © 2022 Xiang Yu et al.</rights><rights>Copyright © 2022 Xiang Yu et al. 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c420t-fd6f5732220f43dfd8b5663a270539ab9f716eb06b6c4de6bddc0a11f7dbd6413</citedby><cites>FETCH-LOGICAL-c420t-fd6f5732220f43dfd8b5663a270539ab9f716eb06b6c4de6bddc0a11f7dbd6413</cites><orcidid>0000-0001-7120-1668 ; 0000-0002-4826-9872 ; 0000-0002-7592-9100 ; 0000-0001-6509-5301</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789418/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8789418/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35087601$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Khalaf, Osamah Ibrahim</contributor><creatorcontrib>Yu, Xiang</creatorcontrib><creatorcontrib>Lu, Lihua</creatorcontrib><creatorcontrib>Guo, Jiangfan</creatorcontrib><creatorcontrib>Qin, Haihuan</creatorcontrib><creatorcontrib>Ji, Chunlei</creatorcontrib><title>VSHR: A Mathematical Model for the Prediction of Second-Wave COVID-19 Epidemics in Malaysia</title><title>Computational and mathematical methods in medicine</title><addtitle>Comput Math Methods Med</addtitle><description>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. 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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.</abstract><cop>United States</cop><pub>Hindawi</pub><pmid>35087601</pmid><doi>10.1155/2022/4168619</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0001-7120-1668</orcidid><orcidid>https://orcid.org/0000-0002-4826-9872</orcidid><orcidid>https://orcid.org/0000-0002-7592-9100</orcidid><orcidid>https://orcid.org/0000-0001-6509-5301</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Belgium - epidemiology Computational Biology Computer Simulation COVID-19 - epidemiology COVID-19 - transmission Epidemics - statistics & numerical data Epidemiological Models France - epidemiology Germany - epidemiology Humans Malaysia - epidemiology SARS-CoV-2 United Kingdom - epidemiology |
title | VSHR: A Mathematical Model for the Prediction of Second-Wave COVID-19 Epidemics in Malaysia |
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