Percolation across households in mechanistic models of non-pharmaceutical interventions in SARS-CoV-2 disease dynamics

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniversity of Oxford-
Autor(es): dc.contributorObservatório COVID-19 BR-
Autor(es): dc.contributorUniversity of Lausanne-
Autor(es): dc.contributorUniversidade de São Paulo (USP)-
Autor(es): dc.contributorCentre for Tropical Medicine and Global Health-
Autor(es): dc.contributorUniversidade Federal do ABC (UFABC)-
Autor(es): dc.creatorFranco, Caroline-
Autor(es): dc.creatorFerreira, Leonardo Souto-
Autor(es): dc.creatorSudbrack, Vítor-
Autor(es): dc.creatorBorges, Marcelo Eduardo-
Autor(es): dc.creatorPoloni, Silas-
Autor(es): dc.creatorPrado, Paulo Inácio-
Autor(es): dc.creatorWhite, Lisa J.-
Autor(es): dc.creatorÁguas, Ricardo-
Autor(es): dc.creatorKraenkel, Roberto André-
Autor(es): dc.creatorCoutinho, Renato Mendes-
Data de aceite: dc.date.accessioned2025-08-21T17:52:07Z-
Data de disponibilização: dc.date.available2025-08-21T17:52:07Z-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-04-29-
Data de envio: dc.date.issued2022-06-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1016/j.epidem.2022.100551-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/230597-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/230597-
Descrição: dc.descriptionSince the emergence of the novel coronavirus disease 2019 (COVID-19), mathematical modelling has become an important tool for planning strategies to combat the pandemic by supporting decision-making and public policies, as well as allowing an assessment of the effect of different intervention scenarios. A proliferation of compartmental models were developed by the mathematical modelling community in order to understand and make predictions about the spread of COVID-19. While compartmental models are suitable for simulating large populations, the underlying assumption of a well-mixed population might be problematic when considering non-pharmaceutical interventions (NPIs) which have a major impact on the connectivity between individuals in a population. Here we propose a modification to an extended age-structured SEIR (susceptible–exposed–infected–recovered) framework, with dynamic transmission modelled using contact matrices for various settings in Brazil. By assuming that the mitigation strategies for COVID-19 affect the connections among different households, network percolation theory predicts that the connectivity among all households decreases drastically above a certain threshold of removed connections. We incorporated this emergent effect at population level by modulating home contact matrices through a percolation correction function, with the few additional parameters fitted to hospitalisation and mortality data from the city of São Paulo. Our model with percolation effects was better supported by the data than the same model without such effects. By allowing a more reliable assessment of the impact of NPIs, our improved model provides a better description of the epidemiological dynamics and, consequently, better policy recommendations.-
Descrição: dc.descriptionLi Ka Shing Foundation-
Descrição: dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionBill and Melinda Gates Foundation-
Descrição: dc.descriptionInstitute of Theoretical Physics São Paulo State University-
Descrição: dc.descriptionBig Data Institute Li Ka Shing Centre for Health Information and Discovery Nuffield Department of Medicine University of Oxford-
Descrição: dc.descriptionObservatório COVID-19 BR-
Descrição: dc.descriptionDepartment of Ecology and Evolution University of Lausanne-
Descrição: dc.descriptionInstituto de Biociências Universidade de São Paulo-
Descrição: dc.descriptionNuffield Department of Medicine University of Oxford Centre for Tropical Medicine and Global Health-
Descrição: dc.descriptionCentro de Matemática Computação e Cognição - Universidade Federal do ABC-
Descrição: dc.descriptionInstitute of Theoretical Physics São Paulo State University-
Descrição: dc.descriptionCAPES: 001-
Descrição: dc.descriptionFAPESP: 2016/01343-7-
Descrição: dc.descriptionFAPESP: 2017/26770-8-
Descrição: dc.descriptionFAPESP: 2018/23984-0-
Descrição: dc.descriptionFAPESP: 2018/24037-4-
Descrição: dc.descriptionFAPESP: 2019/26310-2-
Descrição: dc.descriptionCNPq: 311832/2017-2-
Descrição: dc.descriptionCNPq: 313055/2020-3-
Descrição: dc.descriptionCNPq: 315854/2020-0-
Descrição: dc.descriptionBill and Melinda Gates Foundation: OPP1193472-
Idioma: dc.languageen-
Relação: dc.relationEpidemics-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectCompartmental model-
Palavras-chave: dc.subjectCOVID-19-
Palavras-chave: dc.subjectPercolation-
Palavras-chave: dc.subjectSEIR-
Título: dc.titlePercolation across households in mechanistic models of non-pharmaceutical interventions in SARS-CoV-2 disease dynamics-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

Não existem arquivos associados a este item.