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ResiliScence 4 COVID-19: social sensing & intelligence for forecasting human response in future COVID-19 scenarios, towards social systems resilience

2021-03Report Open access
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dc.contributor.authorGaspar, Rui
dc.contributor.authorRodrigues, Ana Paula
dc.contributor.authorRaposo, Beatriz
dc.contributor.authorGodinho, Cristina
dc.contributor.authorBoavida, Fernando
dc.contributor.authorLeiras, Gisela
dc.contributor.authorToscano, Hugo
dc.contributor.authorFilipe, Jessica
dc.contributor.authorSilva, Jorge Sá
dc.contributor.authorFernandes, Marcelo
dc.contributor.authorArriaga, Miguel
dc.contributor.authorFrancisco, Rita
dc.contributor.authorDomingos, Samuel
dc.contributor.authorSilva, Susana
dc.contributor.authorEspassandim, Teresa
dc.date.accessioned2021-09-13T09:09:32Z
dc.date.available2021-09-13T09:09:32Z
dc.date.issued2021-03
dc.description.abstractUm cenário amplamente discutido face à atual pandemia, prevê a criação de vacinas para a COVID-19. Mas como responderão os cidadãos noutros cenários, e.g. se não existir vacina? Ou se não existir terapêutica adequada ou imunidade de grupo? Sendo o comportamento humano o mais eficaz mecanismo de controlo social da pandemia na ausência de vacina ou outras medidas de controlo, conseguir prevê-lo permitirá intervir proactivamente, reduzindo a sobrecarga e aumentando a resiliência do Sistema Nacional de Saúde. Com esse fim, foram criados modelos teóricos de gestão e comunicação de crise e modelos preditivos de comportamentos de prevenção do risco por contágio de SARS-CoV-2. Estes foram sustentados em dados de sensores humanos, tendo por base a análise de dados extraídos de redes sociais, inquéritos longitudinais e dados "inteligentes" (recolhidos por smartphone). A partir dos resultados, foram elaboradas recomendações emitidas para a Direção-Geral da Saúde, com vista ao desenvolvimento de estratégias e recursos promotores de mobilização e resiliência social, customizadas às diferentes fases de crise e futuros cenários de pandemia.pt_PT
dc.description.abstractA widely discussed scenario in the current pandemic, refers to the creation of a vaccine for COVID-19. But how will citizens respond in other scenarios, e.g. if there is no vaccine? Or if there is no effective therapy or group immunity? Because human behaviour is the most effective mechanism for social control of the pandemic in the absence of a vaccine or other control measures, being able to predict it will allow to intervene proactively, reducing the burden on the National Health System and increasing its resilience. To do so, theoretical models of crisis management and crisis communication and predictive models of SARS-CoV-2 contagion risk prevention behaviours were created based on data from human sensors. This was grounded on data collected from social media, longitudinal surveys and "smart" data (collected through smartphones/smartwatches). Based on the results, proposals were shared with the Directorate-General for Health, focused on the development of strategies and resources to promote social mobilization and resilience, customized to different crisis stages and future pandemic scenarios.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.34632/9789895471959
dc.identifier.isbn9789895471959
dc.identifier.urihttp://hdl.handle.net/10400.14/34759
dc.language.isoporpt_PT
dc.peerreviewednopt_PT
dc.publisherUniversidade Católica Portuguesapt_PT
dc.titleResiliScence 4 COVID-19: social sensing & intelligence for forecasting human response in future COVID-19 scenarios, towards social systems resiliencept_PT
dc.typereport
dspace.entity.typePublication
oaire.citation.conferencePlaceLisboapt_PT
oaire.citation.titleResiliScence 4 COVID-19: social sensing & intelligence for forecasting human response in future COVID-19 scenarios, towards social systems resiliencept_PT
person.familyNameGaspar de Carvalho
person.familyNameGodinho
person.familyNameArriaga
person.familyNameFrancisco
person.givenNameRui
person.givenNameCristina
person.givenNameMiguel
person.givenNameRita
person.identifier591157
person.identifier.ciencia-id5813-697B-5A73
person.identifier.ciencia-id4410-1ADE-E90A
person.identifier.ciencia-id2F1A-573B-13BC
person.identifier.ciencia-idC516-CF2A-C93E
person.identifier.orcid0000-0002-0943-6658
person.identifier.orcid0000-0002-2293-7190
person.identifier.orcid0000-0002-9183-9121
person.identifier.orcid0000-0001-9101-523X
person.identifier.ridI-2067-2015
person.identifier.scopus-author-id50161487500
person.identifier.scopus-author-id55948709100
person.identifier.scopus-author-id54988743400
rcaap.rightsopenAccesspt_PT
rcaap.typereportpt_PT
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relation.isAuthorOfPublication.latestForDiscovery17fd1bc6-6d4e-4c58-b429-99fd86953353

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