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.
Identifieur interne : 000921 ( Main/Curation ); précédent : 000920; suivant : 000922Data-driven study of the COVID-19 pandemic via age-structured modelling and prediction of the health system failure in Brazil amid diverse intervention strategies.
Auteurs : Askery Canabarro [Brésil] ; Elayne Ten Rio [Brésil] ; Renato Martins [Brésil] ; Laís Martins [Brésil] ; Samuraí Brito [Brésil] ; Rafael Chaves [Brésil]Source :
- PloS one [ 1932-6203 ] ; 2020.
Descripteurs français
- KwdFr :
- Adolescent (MeSH), Adulte (MeSH), Adulte d'âge moyen (MeSH), Betacoronavirus (MeSH), Brésil (épidémiologie), Enfant (MeSH), Enfant d'âge préscolaire (MeSH), Femelle (MeSH), Humains (MeSH), Infections à coronavirus (mortalité), Infections à coronavirus (prévention et contrôle), Infections à coronavirus (virologie), Infections à coronavirus (épidémiologie), Jeune adulte (MeSH), Modèles théoriques (MeSH), Mâle (MeSH), Nourrisson (MeSH), Nouveau-né (MeSH), Pandémies (prévention et contrôle), Pneumopathie virale (mortalité), Pneumopathie virale (prévention et contrôle), Pneumopathie virale (virologie), Pneumopathie virale (épidémiologie), Pronostic (MeSH), Prévision (MeSH), Quarantaine (méthodes), Répartition par âge (MeSH), Sujet âgé (MeSH), Sujet âgé de 80 ans ou plus (MeSH), Transmission de maladie infectieuse (prévention et contrôle).
- MESH :
- mortalité : Infections à coronavirus, Pneumopathie virale.
- méthodes : Quarantaine.
- prévention et contrôle : Infections à coronavirus, Pandémies, Pneumopathie virale, Transmission de maladie infectieuse.
- virologie : Infections à coronavirus, Pneumopathie virale.
- épidémiologie : Brésil, Infections à coronavirus, Pneumopathie virale.
- Adolescent, Adulte, Adulte d'âge moyen, Betacoronavirus, Enfant, Enfant d'âge préscolaire, Femelle, Humains, Jeune adulte, Modèles théoriques, Mâle, Nourrisson, Nouveau-né, Pronostic, Prévision, Répartition par âge, Sujet âgé, Sujet âgé de 80 ans ou plus.
- Wicri :
- geographic : Brésil.
English descriptors
- KwdEn :
- Adolescent (MeSH), Adult (MeSH), Age Distribution (MeSH), Aged (MeSH), Aged, 80 and over (MeSH), Betacoronavirus (MeSH), Brazil (epidemiology), Child (MeSH), Child, Preschool (MeSH), Coronavirus Infections (epidemiology), Coronavirus Infections (mortality), Coronavirus Infections (prevention & control), Coronavirus Infections (virology), Disease Transmission, Infectious (prevention & control), Female (MeSH), Forecasting (MeSH), Humans (MeSH), Infant (MeSH), Infant, Newborn (MeSH), Male (MeSH), Middle Aged (MeSH), Models, Theoretical (MeSH), Pandemics (prevention & control), Pneumonia, Viral (epidemiology), Pneumonia, Viral (mortality), Pneumonia, Viral (prevention & control), Pneumonia, Viral (virology), Prognosis (MeSH), Quarantine (methods), Young Adult (MeSH).
- MESH :
- geographic , epidemiology : Brazil.
- epidemiology : Coronavirus Infections, Pneumonia, Viral.
- methods : Quarantine.
- mortality : Coronavirus Infections, Pneumonia, Viral.
- prevention & control : Coronavirus Infections, Disease Transmission, Infectious, Pandemics, Pneumonia, Viral.
- virology : Coronavirus Infections, Pneumonia, Viral.
- Adolescent, Adult, Age Distribution, Aged, Aged, 80 and over, Betacoronavirus, Child, Child, Preschool, Female, Forecasting, Humans, Infant, Infant, Newborn, Male, Middle Aged, Models, Theoretical, Prognosis, Young Adult.
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. 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: 10.1371/journal.pone.0236310
PubMed: 32730352
PubMed Central: PMC7392258
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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.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">32730352</PMID><DateCompleted><Year>2020</Year><Month>08</Month><Day>21</Day></DateCompleted><DateRevised><Year>2020</Year><Month>08</Month><Day>21</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Electronic">1932-6203</ISSN><JournalIssue CitedMedium="Internet"><Volume>15</Volume><Issue>7</Issue><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>PloS one</Title><ISOAbbreviation>PLoS One</ISOAbbreviation></Journal><ArticleTitle>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.</ArticleTitle><Pagination><MedlinePgn>e0236310</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1371/journal.pone.0236310</ELocationID><Abstract><AbstractText>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.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Canabarro</LastName><ForeName>Askery</ForeName><Initials>A</Initials><Identifier Source="ORCID">0000-0001-5048-2317</Identifier><AffiliationInfo><Affiliation>International Institute of Physics, Federal University of Rio Grande do Norte, Natal, RN, Brazil.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Grupo de Física da Matéria Condensada, Núcleo de Ciências Exatas-NCEx, Campus Arapiraca, Universidade Federal de Alagoas, Arapiraca, AL, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tenório</LastName><ForeName>Elayne</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>Hospital Santa Casa de Misericórdia de Maceió, Maceió, AL, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Martins</LastName><ForeName>Renato</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>HIV/AIDS Testing and Counseling Center, Itaberaba, BA, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Martins</LastName><ForeName>Laís</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Superior School of Health Science, Brasília, DF, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Brito</LastName><ForeName>Samuraí</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>International Institute of Physics, Federal University of Rio Grande do Norte, Natal, RN, Brazil.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Chaves</LastName><ForeName>Rafael</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>International Institute of Physics, Federal University of Rio Grande do Norte, Natal, RN, Brazil.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>School of Science and Technology, Federal University of Rio Grande do Norte, Natal, Brazil.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>07</Month><Day>30</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>PLoS One</MedlineTA><NlmUniqueID>101285081</NlmUniqueID><ISSNLinking>1932-6203</ISSNLinking></MedlineJournalInfo><SupplMeshList><SupplMeshName Type="Disease" UI="C000657245">COVID-19</SupplMeshName><SupplMeshName Type="Organism" UI="C000656484">severe acute respiratory syndrome coronavirus 2</SupplMeshName></SupplMeshList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000293" MajorTopicYN="N">Adolescent</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017677" MajorTopicYN="N">Age Distribution</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000369" MajorTopicYN="N">Aged, 80 and over</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D000073640" MajorTopicYN="Y">Betacoronavirus</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D001938" MajorTopicYN="N" Type="Geographic">Brazil</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="N">epidemiology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D002648" MajorTopicYN="N">Child</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002675" MajorTopicYN="N">Child, Preschool</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D018352" 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MajorTopicYN="N">Infant, Newborn</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008962" MajorTopicYN="Y">Models, Theoretical</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D058873" MajorTopicYN="N">Pandemics</DescriptorName><QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011024" MajorTopicYN="N">Pneumonia, Viral</DescriptorName><QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName><QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName><QualifierName UI="Q000517" MajorTopicYN="Y">prevention & control</QualifierName><QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011379" MajorTopicYN="N">Prognosis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D011790" MajorTopicYN="N">Quarantine</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName></MeshHeading></MeshHeadingList><CoiStatement>The authors have declared that no competing interests exist.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>04</Month><Day>07</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>07</Month><Day>04</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>7</Month><Day>31</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>7</Month><Day>31</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>8</Month><Day>22</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32730352</ArticleId><ArticleId IdType="doi">10.1371/journal.pone.0236310</ArticleId><ArticleId IdType="pii">PONE-D-20-09888</ArticleId><ArticleId IdType="pmc">PMC7392258</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Intensive Care Med. 2012 Oct;38(10):1647-53</Citation><ArticleIdList><ArticleId IdType="pubmed">22777516</ArticleId></ArticleIdList></Reference><Reference><Citation>PLoS Comput Biol. 2017 Sep 12;13(9):e1005697</Citation><ArticleIdList><ArticleId IdType="pubmed">28898249</ArticleId></ArticleIdList></Reference><Reference><Citation>Lancet. 2020 Mar 21;395(10228):931-934</Citation><ArticleIdList><ArticleId IdType="pubmed">32164834</ArticleId></ArticleIdList></Reference><Reference><Citation>PLoS One. 2020 Mar 31;15(3):e0230405</Citation><ArticleIdList><ArticleId IdType="pubmed">32231374</ArticleId></ArticleIdList></Reference><Reference><Citation>Ann Intern Med. 2020 May 5;172(9):577-582</Citation><ArticleIdList><ArticleId IdType="pubmed">32150748</ArticleId></ArticleIdList></Reference><Reference><Citation>JAMA. 2020 Feb 24;:</Citation><ArticleIdList><ArticleId IdType="pubmed">32091533</ArticleId></ArticleIdList></Reference><Reference><Citation>Phys Rev Lett. 2020 Feb 14;124(6):068301</Citation><ArticleIdList><ArticleId IdType="pubmed">32109112</ArticleId></ArticleIdList></Reference><Reference><Citation>Lancet. 2020 Feb 15;395(10223):497-506</Citation><ArticleIdList><ArticleId IdType="pubmed">31986264</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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