A novel compartmental model to capture the nonlinear trend of COVID-19
The COVID-19 pandemic took the world by surprise and surpassed the expectations of epidemiologists, governments, medical experts, and the scientific community as a whole. The majority of epidemiological models failed to capture the non-linear trend of the susceptible compartment and were unable to m...
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| Veröffentlicht in: | Computers in biology and medicine 2021-07, Vol.134, p.104421-104421, Article 104421 |
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| creator | Ramezani, Somayeh Bakhtiari Amirlatifi, Amin Rahimi, Shahram |
| description | The COVID-19 pandemic took the world by surprise and surpassed the expectations of epidemiologists, governments, medical experts, and the scientific community as a whole. The majority of epidemiological models failed to capture the non-linear trend of the susceptible compartment and were unable to model this pandemic accurately. This study presents a variant of the well-known SEIRD model to account for social awareness measures, variable death rate, and the presence of asymptomatic infected individuals. The proposed SEAIRDQ model accounts for the transition of individuals between the susceptible and social awareness compartments. We tested our model against the reported cumulative infection and death data for different states in the US and observed over 98.8% accuracy. Results of this study give new insights into the prevailing reproduction number and herd immunity across the US.
•A new compartmental model that captures the nonlinear behavior of the COVID-19 pandemic.•Findings on several key factors in explaining the behavior of COVID-19.•Determination of the reproduction number and the herd immunity percentage for the US.•Facilitating decision making and better explaining the behavior of the COVID-19 pandemic. |
| doi_str_mv | 10.1016/j.compbiomed.2021.104421 |
| format | Article |
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•A new compartmental model that captures the nonlinear behavior of the COVID-19 pandemic.•Findings on several key factors in explaining the behavior of COVID-19.•Determination of the reproduction number and the herd immunity percentage for the US.•Facilitating decision making and better explaining the behavior of the COVID-19 pandemic.</description><identifier>ISSN: 0010-4825</identifier><identifier>EISSN: 1879-0534</identifier><identifier>DOI: 10.1016/j.compbiomed.2021.104421</identifier><identifier>PMID: 33964736</identifier><language>eng</language><publisher>United States: Elsevier Ltd</publisher><subject>Asymptomatic ; Compartmental modeling ; Coronaviruses ; COVID-19 ; Disease transmission ; Epidemic models ; Epidemics ; Epidemiology ; Herd immunity ; Hospitalization ; Infections ; Infectious diseases ; Mathematical functions ; Model testing ; Nonlinear trend ; Ordinary differential equations ; Pandemics ; Population ; Quarantine ; Reproduction Number,s SEIRD ; Severe acute respiratory syndrome coronavirus 2 ; Social awareness</subject><ispartof>Computers in biology and medicine, 2021-07, Vol.134, p.104421-104421, Article 104421</ispartof><rights>2021 Elsevier Ltd</rights><rights>Copyright © 2021 Elsevier Ltd. All rights reserved.</rights><rights>2021. Elsevier Ltd</rights><rights>2021 Elsevier Ltd. All rights reserved. 2021 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c507t-3b5c40e8fe9fb55e3018a3ad3e13670e560957cafce6f6bdc649283ea5b2f8c43</citedby><cites>FETCH-LOGICAL-c507t-3b5c40e8fe9fb55e3018a3ad3e13670e560957cafce6f6bdc649283ea5b2f8c43</cites><orcidid>0000-0002-5230-8723 ; 0000-0002-2225-2087</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0010482521002158$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33964736$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ramezani, Somayeh Bakhtiari</creatorcontrib><creatorcontrib>Amirlatifi, Amin</creatorcontrib><creatorcontrib>Rahimi, Shahram</creatorcontrib><title>A novel compartmental model to capture the nonlinear trend of COVID-19</title><title>Computers in biology and medicine</title><addtitle>Comput Biol Med</addtitle><description>The COVID-19 pandemic took the world by surprise and surpassed the expectations of epidemiologists, governments, medical experts, and the scientific community as a whole. The majority of epidemiological models failed to capture the non-linear trend of the susceptible compartment and were unable to model this pandemic accurately. This study presents a variant of the well-known SEIRD model to account for social awareness measures, variable death rate, and the presence of asymptomatic infected individuals. The proposed SEAIRDQ model accounts for the transition of individuals between the susceptible and social awareness compartments. We tested our model against the reported cumulative infection and death data for different states in the US and observed over 98.8% accuracy. Results of this study give new insights into the prevailing reproduction number and herd immunity across the US.
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•A new compartmental model that captures the nonlinear behavior of the COVID-19 pandemic.•Findings on several key factors in explaining the behavior of COVID-19.•Determination of the reproduction number and the herd immunity percentage for the US.•Facilitating decision making and better explaining the behavior of the COVID-19 pandemic.</abstract><cop>United States</cop><pub>Elsevier Ltd</pub><pmid>33964736</pmid><doi>10.1016/j.compbiomed.2021.104421</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-5230-8723</orcidid><orcidid>https://orcid.org/0000-0002-2225-2087</orcidid><oa>free_for_read</oa></addata></record> |
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| ispartof | Computers in biology and medicine, 2021-07, Vol.134, p.104421-104421, Article 104421 |
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| source | Elsevier ScienceDirect Journals |
| subjects | Asymptomatic Compartmental modeling Coronaviruses COVID-19 Disease transmission Epidemic models Epidemics Epidemiology Herd immunity Hospitalization Infections Infectious diseases Mathematical functions Model testing Nonlinear trend Ordinary differential equations Pandemics Population Quarantine Reproduction Number,s SEIRD Severe acute respiratory syndrome coronavirus 2 Social awareness |
| title | A novel compartmental model to capture the nonlinear trend of COVID-19 |
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