SOCRATES-CoMix: a platform for timely and open-source contact mixing data during and in between COVID-19 surges and interventions in over 20 European countries
Frederik Verelst,
Lisa Hermans,
Sarah Vercruysse,
Amy Gimma,
Pietro Coletti,
Jantien A. Backer,
Kerry L. M. Wong,
James Wambua,
Kevin van Zandvoort,
Lander Willem,
Laurens Bogaardt,
Christel Faes,
Christopher I. Jarvis,
Jacco Wallinga,
W. John Edmunds,
Philippe Beutels,
Niel Hens
Affiliations
Frederik Verelst
Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp
Lisa Hermans
Data Science Institute and I-BioStat, Hasselt University
Sarah Vercruysse
Data Science Institute and I-BioStat, Hasselt University
Amy Gimma
London School of Hygiene and Tropical Medicine
Pietro Coletti
Data Science Institute and I-BioStat, Hasselt University
Jantien A. Backer
Centre for Infectious Disease Control, National Institute for Public Health and the Environment
Kerry L. M. Wong
London School of Hygiene and Tropical Medicine
James Wambua
Data Science Institute and I-BioStat, Hasselt University
Kevin van Zandvoort
London School of Hygiene and Tropical Medicine
Lander Willem
Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp
Laurens Bogaardt
Centre for Infectious Disease Control, National Institute for Public Health and the Environment
Christel Faes
Data Science Institute and I-BioStat, Hasselt University
Christopher I. Jarvis
London School of Hygiene and Tropical Medicine
Jacco Wallinga
Centre for Infectious Disease Control, National Institute for Public Health and the Environment
W. John Edmunds
London School of Hygiene and Tropical Medicine
Philippe Beutels
Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp
Niel Hens
Centre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp
Abstract Background SARS-CoV-2 dynamics are driven by human behaviour. Social contact data are of utmost importance in the context of transmission models of close-contact infections. Methods Using online representative panels of adults reporting on their own behaviour as well as parents reporting on the behaviour of one of their children, we collect contact mixing (CoMix) behaviour in various phases of the COVID-19 pandemic in over 20 European countries. We provide these timely, repeated observations using an online platform: SOCRATES-CoMix. In addition to providing cleaned datasets to researchers, the platform allows users to extract contact matrices that can be stratified by age, type of day, intensity of the contact and gender. These observations provide insights on the relative impact of recommended or imposed social distance measures on contacts and can inform mathematical models on epidemic spread. Conclusion These data provide essential information for policymakers to balance non-pharmaceutical interventions, economic activity, mental health and wellbeing, during vaccine rollout.
