Modelling practices, data provisioning, sharing and dissemination needs for pandemic decision-making: a European survey-based modellers’ perspective, 2020 to 2022

BACKGROUNDAdvanced outbreak analytics were instrumental in informing governmental decision-making during the COVID-19 pandemic. However, systematic evaluations of how modelling practices, data use and science-policy interactions evolved during this and previous emergencies remain scarce.AIMThis study assessed the evolution of modelling practices, data usage, gaps, and engagement between modellers and decision-makers to inform future global epidemic intelligence.METHODSWe conducted a two-stage semiquantitative survey among modellers in a large European epidemic intelligence consortium. Responses were analysed descriptively across early, mid- and late-pandemic phases. We used policy citations in Overton to assess policy impact.RESULTSOur sample included 66 modelling contributions from 11 institutions in four European countries. COVID-19 modelling initially prioritised understanding epidemic dynamics; evaluating non-pharmaceutical interventions and vaccination impacts later became equally important. Traditional surveillance data (e.g. case line lists) were widely available in near-real time. Conversely, real-time non-traditional data (notably social contact and behavioural surveys) and serological data were frequently reported as lacking. Gaps included poor stratification and incomplete geographical coverage. Frequent bidirectional engagement with decision-makers shaped modelling scope and recommendations. However, fewer than half of the studies shared open-access code.CONCLUSIONSWe highlight the evolving use and needs of modelling during public health crises. Persistent gaps in the availability of non-traditional data underscore the need to rethink sustainable data collection and sharing practices, including from for-profit providers. Future preparedness should focus on strengthening collaborative platforms, research consortia and modelling networks to foster data and code sharing and effective collaboration between academia, decision-makers and data providers.

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Publication Details

Journal
Eurosurveillance
Published
2025-10-23
DOI
https://doi.org/10.2807/1560-7917.es.2025.30.42.2500216
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
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article

Modelling practices, data provisioning, sharing and dissemination needs for pandemic decision-making: a European survey-based modellers’ perspective, 2020 to 2022

Wim Van Bortel, Luca Busani, Annapaola Rizzoli, Vittoria Colizza et al.
Eurosurveillance
COVID-19 epidemiological studies
article

Modelling practices, data provisioning, sharing and dissemination needs for pandemic decision-making: a European survey-based modellers’ perspective, 2020 to 2022

Wim Van Bortel, Luca Busani, Annapaola Rizzoli, Vittoria Colizza, Andrew J. Tatem, Sabine van Elsland, Philippe Lemey, Shengjie Lai, Zoran Milosavljević, Elena Arsevska, Marius Gilbert, Chiara Poletto, Moritz U. G. Kraemer, Laura Di Domenico, Esther van Kleef, William Wint, Simon Dellicour, Maguelonne Teisseire, Danijela Simić, Stefano Merler
article en

Abstract

BACKGROUNDAdvanced outbreak analytics were instrumental in informing governmental decision-making during the COVID-19 pandemic. However, systematic evaluations of how modelling practices, data use and science-policy interactions evolved during this and previous emergencies remain scarce.AIMThis study assessed the evolution of modelling practices, data usage, gaps, and engagement between modellers and decision-makers to inform future global epidemic intelligence.METHODSWe conducted a two-stage semiquantitative survey among modellers in a large European epidemic intelligence consortium. Responses were analysed descriptively across early, mid- and late-pandemic phases. We used policy citations in Overton to assess policy impact.RESULTSOur sample included 66 modelling contributions from 11 institutions in four European countries. COVID-19 modelling initially prioritised understanding epidemic dynamics; evaluating non-pharmaceutical interventions and vaccination impacts later became equally important. Traditional surveillance data (e.g. case line lists) were widely available in near-real time. Conversely, real-time non-traditional data (notably social contact and behavioural surveys) and serological data were frequently reported as lacking. Gaps included poor stratification and incomplete geographical coverage. Frequent bidirectional engagement with decision-makers shaped modelling scope and recommendations. However, fewer than half of the studies shared open-access code.CONCLUSIONSWe highlight the evolving use and needs of modelling during public health crises. Persistent gaps in the availability of non-traditional data underscore the need to rethink sustainable data collection and sharing practices, including from for-profit providers. Future preparedness should focus on strengthening collaborative platforms, research consortia and modelling networks to foster data and code sharing and effective collaboration between academia, decision-makers and data providers.

EurosurveillanceVol. 30(42)
Fondazione Edmund Mach (IT), University of Bern (CH), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (FR), Université Libre de Bruxelles (BE), Vrije Universiteit Brussel (BE), University of Padua (IT), Inserm (FR), Utrecht University (NL), Fondazione Bruno Kessler (IT), Rega Institute for Medical Research (BE), Istituto Superiore di Sanità (IT), Oxford Research Group (GB), University Medical Center Utrecht (NL), Sorbonne Université (FR), University of Oxford (GB), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Animal, Santé, Territoires, Risques et Ecosystèmes (FR), Institut Pierre Louis d‘Épidémiologie et de Santé Publique (FR), Institute of Social and Preventive Medicine (CH), Institute of Public Health of Serbia (RS), Science Oxford (GB), University of Southampton (GB), Territoires, Environnement, Télédétection et Information Spatiale (FR), Imperial College London (GB), Instituut voor Tropische Geneeskunde (BE), KU Leuven (BE)
Bill and Melinda Gates Foundation, Rockefeller Foundation, Wellcome Trust, European Commission, Agence Nationale de la Recherche, Fonds De La Recherche Scientifique - FNRS, Fonds Wetenschappelijk Onderzoek, Novo Nordisk, Novo Nordisk Fonden, Vlaamse regering, Horizon 2020 Framework Programme, HORIZON EUROPE Framework Programme, Medical Research Council, Departement Economie, Wetenschap en Innovatie, European and Developing Countries Clinical Trials Partnership
Openalex Percentile: Top 66%
COVID-19 epidemiological studies
DOIOpen Access PDFOpenAlex
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