Correlations between web searches and covid-19 epidemiological indicators in Brazil

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dc.creatorMarcelo Sartori Locatelli
dc.creatorAnne Isabelle Rodrigues de Carvalho
dc.creatorLeandro M. V. Souza
dc.creatorGabriela P. F. Paixão
dc.creatorElisa França Chaves
dc.creatorGuilherme Bezerra Dos Santos
dc.creatorRafael Vinícius dos Santos
dc.creatorAmanda Cupertino de Freitas
dc.creatorMatheus G. Flores
dc.creatorRachel F. Biezuner
dc.creatorRodolfo Lins Cardoso
dc.creatorEvandro Landulfo Teixeira Paradela Cunha
dc.creatorRodrigo Machado Fonseca
dc.creatorAna Paula Couto da Silva
dc.creatorWagner Meira Jr
dc.creatorJanaína Guiginski
dc.creatorRamon A. S. Franco
dc.creatorTereza Bernardes
dc.creatorPedro Loures Alzamora
dc.creatorDaniel Victor F. da Silva
dc.creatorMarcelo Augusto s Ganem
dc.creatorThiago H. M. Santos
dc.date.accessioned2024-05-10T20:54:04Z
dc.date.accessioned2025-09-08T23:47:03Z
dc.date.available2024-05-10T20:54:04Z
dc.date.issued2022
dc.identifier.doi10.1590/1678-4324-2022210648
dc.identifier.issn1678-4324
dc.identifier.urihttps://hdl.handle.net/1843/68191
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofBrazilian Archives of Biology and Technology
dc.rightsAcesso Aberto
dc.subjectSaúde - Indicadores
dc.subject.otherGoogle Trends
dc.subject.otherInfodemiology
dc.subject.otherEpidemiological predictions
dc.subject.otherDigital health
dc.titleCorrelations between web searches and covid-19 epidemiological indicators in Brazil
dc.typeArtigo de periódico
local.citation.epage10
local.citation.spage1
local.citation.volume65
local.description.resumoCOVID-19 rapidly spread across the world in an unprecedented outbreak with a massive number of infected and fatalities. The pandemic was heavily discussed and searched on the internet, which generated big amounts of data related to it. This led to the possibility of attempting to forecast coronavirus indicators using the internet data. For this study, Google Trends statistics for 124 selected search terms related to pandemic were used in an attempt to find which keywords had the best Spearman correlations with a lag, as well as a forecasting model. It was found that keywords related to coronavirus testing among some others, such as “I have contracted covid”, had high correlations (≥0.7) with few weeks of lag (≤4 weeks). Besides that, the ARIMAX model using those keywords had promising results in predicting the increase or decrease of epidemiological indicators, although it was not able to predict their exact values. Thus, we found that Google Trends data may be useful for predicting outbreaks of coronavirus a few weeks before they happen, and may be used as an auxiliary tool in monitoring and forecasting the disease in Brazil.
local.identifier.orcidhttps://orcid.org/0000-0002-0893-1446
local.identifier.orcidhttps://orcid.org/0000-0002-6533-5229
local.identifier.orcidhttps://orcid.org/0000-0002-1150-2546
local.identifier.orcidhttps://orcid.org/0000-0003-1821-3912
local.identifier.orcidhttps://orcid.org/0000-0002-8176-586X
local.identifier.orcidhttps://orcid.org/0000-0002-1979-1522
local.identifier.orcidhttps://orcid.org/0000-0002-6534-5785
local.identifier.orcidhttps://orcid.org/0000-0001-8600-4077
local.identifier.orcidhttps://orcid.org/0000-0002-1654-5852
local.identifier.orcidhttps://orcid.org/0000-0002-9542-090X
local.identifier.orcidhttps://orcid.org/0000-0002-0139-107X
local.identifier.orcidhttps://orcid.org/0000-0002-5302-2946
local.identifier.orcidhttps://orcid.org/0000-0001-6125-642X
local.identifier.orcidhttps://orcid.org/0000-0001-5951-3562
local.identifier.orcidhttps://orcid.org/0000-0002-2614-2723
local.identifier.orcidhttps://orcid.org/0000-0003-0590-4538
local.identifier.orcidhttps://orcid.org/0000-0002-2653-9835
local.identifier.orcidhttps://orcid.org/0000-0001-7199-3888
local.identifier.orcidhttps://orcid.org/0000-0001-9599-0198
local.identifier.orcidhttps://orcid.org/0000-0001-7662-6737
local.identifier.orcidhttps://orcid.org/0000-0003-0842-4732
local.identifier.orcidhttps://orcid.org/0000-0001-6784-0002
local.publisher.countryBrasil
local.publisher.departmentFALE - FACULDADE DE LETRAS
local.publisher.initialsUFMG
local.url.externahttp://www.scielo.br/j/babt/a/FN9Rwk4DpGDCRmPg8V9tkgL/?lang=endoi:10.1590/1678-4324-2022210648

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