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Title: | 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 | Authors: | Verelst, Frederik HERMANS, Lisa VERCRUYSSE, Sarah Gimma, Amy COLETTI, Pietro Backer, Jantien A. Wong, Kerry L. M. WAMBUA, James van Zandvoort, Kevin WILLEM, Lander Bogaardt, Laurens FAES, Christel Jarvis, Christopher, I Wallinga, Jacco Edmunds, W. John Beutels, Philippe HENS, Niel |
Issue Date: | 2021 | Publisher: | BMC | Source: | BMC MEDICINE, 19 (1) (Art N° 254) | 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. | Notes: | Hermans, L (corresponding author), Hasselt Univ, Data Sci Inst, Hasselt, Belgium.; Hermans, L (corresponding author), Hasselt Univ, I BioStat, Hasselt, Belgium. lisa.hermans@uhasselt.be |
Keywords: | Social contact behaviour;Mixing patterns;Contact data;Mathematical modelling;SARS-CoV-2;COVID-19;Europe | Document URI: | http://hdl.handle.net/1942/35767 | ISSN: | 1741-7015 | e-ISSN: | 1741-7015 | DOI: | 10.1186/s12916-021-02133-y | ISI #: | WOS:000701053600002 | Rights: | The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. | Category: | A1 | Type: | Journal Contribution | Validations: | ecoom 2022 |
Appears in Collections: | Research publications |
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s12916-021-02133-y.pdf | Published version | 2.46 MB | Adobe PDF | View/Open |
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