publication . Article . Preprint . 2021

Adaptive Time-Dependent Priors and Bayesian Inference to Evaluate SARS-CoV-2 Public Health Measures Validated on 31 Countries

Hugues Turbé; Hugues Turbé; Mina Bjelogrlic; Mina Bjelogrlic; Arnaud Robert; Arnaud Robert; Christophe Gaudet-Blavignac; Christophe Gaudet-Blavignac; Jean-Philippe Goldman; Jean-Philippe Goldman; ...
Open Access English
  • Published: 21 Jan 2021 Journal: Frontiers in Public Health, volume 8 (issn: 2296-2565, Copyright policy)
  • Publisher: Frontiers Media SA
  • Country: Switzerland
<jats:p>With the rapid spread of the SARS-CoV-2 virus since the end of 2019, public health confinement measures to contain the propagation of the pandemic have been implemented. Our method to estimate the reproduction number using Bayesian inference with time-dependent priors enhances previous approaches by considering a dynamic prior continuously updated as restrictive measures and comportments within the society evolve. In addition, to allow direct comparison between reproduction number and introduction of public health measures in a specific country, the infection dates are inferred from daily confirmed cases and confirmed death. The evolution of this reprodu...
free text keywords: Public Health, Environmental and Occupational Health, Basic Reproduction Number, Bayes Theorem, COVID-19/epidemiology/mortality, Europe, Humans, Longitudinal Studies, Public Health, SARS-CoV-2/isolation & purification, infectious diseases, reproductive number estimation, non-pharmaceutical interventions, Bayesian inference (BI), health sciences, epidemiology, Public Health, Original Research, SARS -CoV-2, ddc:616.0757, Public health, medicine.medical_specialty, medicine, Coronavirus disease 2019 (COVID-19), Bayesian inference, Econometrics, Computer science, Median time, Prior probability, Pandemic, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 2019-20 coronavirus outbreak, Geography, Data-driven, Psychological intervention, lcsh:Public aspects of medicine, lcsh:RA1-1270
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