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

Rui Gaspar, Ana Paula Rodrigues, Beatriz Raposo, Cristina Godinho, Fernando Boavida, Gisela Leiras, Hugo Toscano, Jessica Filipe, Jorge Sá Silva, Marcelo Fernandes, Miguel Arriaga, Rita Francisco, Samuel Domingos, Susana Silva, Teresa Espassandim

Research output: Book/ReportCommissioned report

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Abstract

A 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.
Original languagePortuguese
Place of PublicationLisboa
PublisherUniversidade Católica Portuguesa
Number of pages17
ISBN (Electronic)9789895471959
DOIs
Publication statusPublished - Mar 2021

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