Tracking Epidemics With Google Flu Trends Data and a State-Space SEIR Model

Página do item simplificado
dc.contributor.authorDukic, Vanja
dc.contributor.authorHEDIBERT FREITAS LOPES
dc.contributor.authorPolson, Nicholas G.
dc.coverage.cidadeNão informadopt_BR
dc.coverage.paisNão Informadopt_BR
dc.creatorDukic, Vanja
dc.creatorPolson, Nicholas G.
dc.date.accessioned2022-08-19T21:17:20Z
dc.date.available2022-08-19T21:17:20Z
dc.date.issued2012
dc.description.otherIn this article, we use Google Flu Trends data together with a sequential surveillance model based on state-space methodology to track the evolution of an epidemic process over time. We embed a classical mathematical epidemiology model [a susceptible-exposed-infected-recovered (SEIR) model] within the state-space framework, thereby extending the SEIR dynamics to allow changes through time. The implementation of this model is based on a particle filtering algorithm, which learns about the epidemic process sequentially through time and provides updated estimated odds of a pandemic with each new surveillance data point. We show how our approach, in combination with sequential Bayes factors, can serve as an online diagnostic tool for influenza pandemic. We take a close look at the Google Flu Trends data describing the spread of flu in the United States during 2003—2009 and in nine separate U.S. states chosen to represent a wide range of health care and emergency system strengths and weaknesses. This article has online supplementary materials.pt_BR
dc.format.extentp. 1410-1426pt_BR
dc.format.mediumDigitalpt_BR
dc.identifier.issue500pt_BR
dc.identifier.urihttps://repositorio.insper.edu.br/handle/11224/4061
dc.identifier.volume107pt_BR
dc.language.isoInglêspt_BR
dc.publisherAmerican Statistical Associationpt_BR
dc.relation.ispartofJournal of the American Statistical Associationpt_BR
dc.rights.licenseO INSPER E ESTE REPOSITÓRIO NÃO DETÊM OS DIREITOS DE USO E REPRODUÇÃO DOS CONTEÚDOS AQUI REGISTRADOS. É RESPONSABILIDADE DOS USUÁRIOS INDIVIDUAIS VERIFICAR OS USOS PERMITIDOS NA FONTE ORIGINAL, RESPEITANDO-SE OS DIREITOS DE AUTOR OU EDITOR.pt_BR
dc.subject.keywordsFlupt_BR
dc.subject.keywordsGoogle correlatept_BR
dc.subject.keywordsGoogle searchespt_BR
dc.subject.keywordsGoogle trendspt_BR
dc.subject.keywordsH1N1pt_BR
dc.subject.keywordsInfectious Diseasespt_BR
dc.subject.keywordsInfluenzapt_BR
dc.subject.keywordsIP surveilancept_BR
dc.subject.keywordsNowcastingpt_BR
dc.subject.keywordsOnline surveillancept_BR
dc.subject.keywordsParticle filteringpt_BR
dc.titleTracking Epidemics With Google Flu Trends Data and a State-Space SEIR Modelpt_BR
dc.typejournal article
dspace.entity.typePublication
local.identifier.sourceUrihttps://www.jstor.org/stable/23427343
local.subject.cnpqCiências Sociais Aplicadaspt_BR
local.typeArtigo Científicopt_BR
relation.isAuthorOfPublication41f844cb-0e5a-4ef1-bb19-5ab1cec8e2ca
relation.isAuthorOfPublication.latestForDiscovery41f844cb-0e5a-4ef1-bb19-5ab1cec8e2ca
Arquivos
Pacote Original
Agora exibindo 1 - 2 de 2
N/D
Nome:
R_Artigo_2012_Tracking Epidemics With Google_TC.pdf
Tamanho:
3.72 MB
Formato:
Adobe Portable Document Format
Descrição:
R_Artigo_2012_Tracking Epidemics With Google_TC
Baixar
Imagem de Miniatura
Nome:
Acesso_Primeira Pagina_Tracking Epidemics With Google Flu Trends Data and a State-Space SEIR Model.pdf
Tamanho:
118.54 KB
Formato:
Adobe Portable Document Format
Baixar
Licença do Pacote
Agora exibindo 1 - 1 de 1
N/D
Nome:
license.txt
Tamanho:
282 B
Formato:
Item-specific license agreed upon to submission
Descrição:
Baixar
Coleções
Coleção de Artigos Acadêmicos