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The values and limitations of mathematical modelling to COVID-19 in the world: a follow up report

dc.contributor.authorTang, Yuanji
dc.contributor.authorTang, Sherry
dc.contributor.authorWang, Shixia
dc.date2022-08-11T08:08:09.000
dc.date.accessioned2022-08-23T15:44:37Z
dc.date.available2022-08-23T15:44:37Z
dc.date.issued2020-12-01
dc.date.submitted2020-11-25
dc.identifier.citation<p>Tang Y, Tang S, Wang S. The values and limitations of mathematical modelling to COVID-19 in the world: a follow up report. Emerg Microbes Infect. 2020 Dec;9(1):2465-2473. doi: 10.1080/22221751.2020.1843973. PMID: 33121387; PMCID: PMC7671649. <a href="https://doi.org/10.1080/22221751.2020.1843973">Link to article on publisher's site</a></p>
dc.identifier.issn2222-1751 (Linking)
dc.identifier.doi10.1080/22221751.2020.1843973
dc.identifier.pmid33121387
dc.identifier.urihttp://hdl.handle.net/20.500.14038/27354
dc.description.abstractWe previously described a mathematical model to simulate the course of the COVID-19 pandemic and try to predict how this outbreak might evolve in the following two months when the pandemic cases will drop significantly. Our original paper prepared in March 2020 analyzed the outbreaks of COVID-19 in the US and its selected states to identify the rise, peak, and decrease of cases within a given geographic population, as well as a rough calculation of accumulated total cases in this population from the beginning to the end of June 2020. The current report will describe how well the later actual trend from March to June fit our model and prediction. Similar analyses are also conducted to include countries other than the US. From such a wide global data analysis, our results demonstrated that different US states and countries showed dramatically different patterns of pandemic trend. The values and limitations of our modelling are discussed.
dc.language.isoen_US
dc.relation<p><a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=33121387&dopt=Abstract">Link to Article in PubMed</a></p>
dc.rights© 2020 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectCOVID-19
dc.subjectSARS-CoV-2
dc.subjectepidemiology
dc.subjectmodelling
dc.subjectpandemic
dc.subjectDisease Modeling
dc.subjectEpidemiology
dc.subjectImmunology and Infectious Disease
dc.subjectInfectious Disease
dc.subjectMathematics
dc.subjectMicrobiology
dc.subjectVirus Diseases
dc.titleThe values and limitations of mathematical modelling to COVID-19 in the world: a follow up report
dc.typeJournal Article
dc.source.journaltitleEmerging microbes and infections
dc.source.volume9
dc.source.issue1
dc.identifier.legacyfulltexthttps://escholarship.umassmed.edu/cgi/viewcontent.cgi?article=1151&amp;context=covid19&amp;unstamped=1
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/covid19/148
dc.identifier.contextkey20304133
refterms.dateFOA2022-08-23T15:44:37Z
html.description.abstract<p>We previously described a mathematical model to simulate the course of the COVID-19 pandemic and try to predict how this outbreak might evolve in the following two months when the pandemic cases will drop significantly. Our original paper prepared in March 2020 analyzed the outbreaks of COVID-19 in the US and its selected states to identify the rise, peak, and decrease of cases within a given geographic population, as well as a rough calculation of accumulated total cases in this population from the beginning to the end of June 2020. The current report will describe how well the later actual trend from March to June fit our model and prediction. Similar analyses are also conducted to include countries other than the US. From such a wide global data analysis, our results demonstrated that different US states and countries showed dramatically different patterns of pandemic trend. The values and limitations of our modelling are discussed.</p>
dc.identifier.submissionpathcovid19/148
dc.contributor.departmentDepartment of Medicine
dc.source.pages2465-2473


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© 2020 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Except where otherwise noted, this item's license is described as © 2020 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.