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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pubmed:32730352Le document en format XML
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<front><div type="abstract" xml:lang="en">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.</div>
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<QualifierName UI="Q000453" MajorTopicYN="Y">epidemiology</QualifierName>
<QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName>
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</MeshHeading>
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<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
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<QualifierName UI="Q000401" MajorTopicYN="N">mortality</QualifierName>
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<QualifierName UI="Q000821" MajorTopicYN="N">virology</QualifierName>
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<MeshHeading><DescriptorName UI="D011379" MajorTopicYN="N">Prognosis</DescriptorName>
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<CoiStatement>The authors have declared that no competing interests exist.</CoiStatement>
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<Month>04</Month>
<Day>07</Day>
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<PubMedPubDate PubStatus="accepted"><Year>2020</Year>
<Month>07</Month>
<Day>04</Day>
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