Print Email Facebook Twitter Computational Models That Matter During a Global Pandemic Outbreak Title Computational Models That Matter During a Global Pandemic Outbreak: A Call to Action Author Squazzoni, Flaminio (University of Milan) Polhillb, J. Gareth (The James Hutton Institute) Edmonds, Bruce (Manchester Metropolitan University) Ahrweiler, Petra (Johannes Gutenberg-University Mainz) Antosz, Patrycja (Rijksuniversiteit Groningen) Scholz, G. (University of Osnabrück) Chappin, E.J.L. (TU Delft Energie and Industrie) Borit, Melania (The Arctic University of Norway) Verhagen, Harko (Stockholm University) Giardini, Francesca (Rijksuniversiteit Groningen) Gilbert, Nigel (University of Surrey) Date 2020 Abstract The COVID-19 pandemic is causing a dramatic loss of lives worldwide, challenging the sustainability of our health care systems, threatening economic meltdown, and putting pressure on the mental health of individuals (due to social distancing and lock-down measures). The pandemic is also posing severe challenges to the scientific community, with scholars under pressure to respond to policymakers’ demands for advice despite the absence of adequate, trusted data. Understanding the pandemic requires fine-grained data representing specific local conditions and the social reactions of individuals. While experts have built simulation models to estimate disease trajectories that may be enough to guide decision-makers to formulate policy measures to limit the epidemic, they do not cover the full behavioural and social complexity of societies under pandemic crisis. Modelling that has such a large potential impact upon people’s lives is a great responsibility. This paper calls on the scientific community to improve the transparency, access, and rigour of their models. It also calls on stakeholders to improve the rapidity with which data from trusted sources are released to the community (in a fully responsible manner). Responding to the pandemic is a stress test of our collaborative capacity and the social/economic value of research. Subject Agent-Based ModelsCOVID-19DataModellingPandemic DiseasePolicy To reference this document use: http://resolver.tudelft.nl/uuid:4b766f1f-297c-43d8-877d-4ec371b7ceef DOI https://doi.org/10.18564/jasss.4298 ISSN 1460-7425 Source Journal of Artificial Societies and Social Simulation, 23 (2) Part of collection Institutional Repository Document type journal article Rights © 2020 Flaminio Squazzoni, J. Gareth Polhillb, Bruce Edmonds, Petra Ahrweiler, Patrycja Antosz, G. Scholz, E.J.L. Chappin, Melania Borit, Harko Verhagen, Francesca Giardini, Nigel Gilbert Files PDF Computational_Models_That ... tbreak.pdf 357.65 KB Close viewer /islandora/object/uuid:4b766f1f-297c-43d8-877d-4ec371b7ceef/datastream/OBJ/view