Data-driven study of the COVID-19 pandemic via age-structured modelling and prediction of the health system failure in Brazil amid diverse intervention strategies
In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities, social distancing of people above sixty years old and voluntary home quarantine...
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| Veröffentlicht in: | PloS one 2020-07, Vol.15 (7), p.e0236310-e0236310 |
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| creator | Canabarro, Askery Tenório, Elayne Martins, Renato Martins, Laís Brito, Samuraí Chaves, Rafael |
| description | In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities, social distancing of people above sixty years old and voluntary home quarantine to show that it is still not enough to protect the health system by explicitly computing the demand for hospital intensive care units. We also show that an urgent intense quarantine might be the only solution to avoid the collapse of the health system and, consequently, to minimize the quantity of deaths. On the other hand, we demonstrate that the relaxation of the already imposed control measures in the next days would be catastrophic. |
| doi_str_mv | 10.1371/journal.pone.0236310 |
| format | Article |
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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Canabarro, Askery</au><au>Tenório, Elayne</au><au>Martins, Renato</au><au>Martins, Laís</au><au>Brito, Samuraí</au><au>Chaves, Rafael</au><au>Braunstein, Lidia Adriana</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Data-driven study of the COVID-19 pandemic via age-structured modelling and prediction of the health system failure in Brazil amid diverse intervention strategies</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2020-07-30</date><risdate>2020</risdate><volume>15</volume><issue>7</issue><spage>e0236310</spage><epage>e0236310</epage><pages>e0236310-e0236310</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. 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| subjects | Adolescent Adult Age Age Distribution Aged Aged, 80 and over Betacoronavirus Brazil - epidemiology Catastrophic failure analysis Child Child, Preschool Coronavirus Infections - epidemiology Coronavirus Infections - mortality Coronavirus Infections - prevention & control Coronavirus Infections - virology Coronaviruses COVID-19 Disease control Disease transmission Disease Transmission, Infectious - prevention & control Epidemic models Epidemics Epidemiology Female Forecasting Hospitals Humans Infant Infant, Newborn Infections Intensive care units Investigations Male Medicine and Health Sciences Middle Aged Models, Theoretical Ordinary differential equations Pandemics Pandemics - prevention & control People and places Physics Pneumonia, Viral - epidemiology Pneumonia, Viral - mortality Pneumonia, Viral - prevention & control Pneumonia, Viral - virology Population Prognosis Public health Quarantine Quarantine - methods SARS-CoV-2 Schools Severe acute respiratory syndrome coronavirus 2 Social distancing Social Sciences Vaccines Young Adult |
| title | Data-driven study of the COVID-19 pandemic via age-structured modelling and prediction of the health system failure in Brazil amid diverse intervention strategies |
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