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Computational Models That Matter During a Global Pandemic Outbreak: A Call to Action

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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.

Suggested Citation

  • Flaminio Squazzoni & J. Gareth Polhill & Bruce Edmonds & Petra Ahrweiler & Patrycja Antosz & Geeske Scholz & Emile Chappin & Melania Borit & Harko Verhagen & Francesca Giardini & Nigel Gilbert, 2020. "Computational Models That Matter During a Global Pandemic Outbreak: A Call to Action," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(2), pages 1-10.
  • Handle: RePEc:jas:jasssj:2020-44-1
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    3. Davids, Allan & du Rand, Gideon & Georg, Co-Pierre & Koziol, Tina & Schasfoort, Joeri, 2023. "Social learning in a network model of Covid-19," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 271-304.
    4. Mitja Steinbacher & Matthias Raddant & Fariba Karimi & Eva Camacho Cuena & Simone Alfarano & Giulia Iori & Thomas Lux, 2021. "Advances in the agent-based modeling of economic and social behavior," SN Business & Economics, Springer, vol. 1(7), pages 1-24, July.
    5. Farouk Daghistani, 2023. "Public Behavior in Urban Parks during Pandemics as a Foundation for Risk Assessment by Park Managers: A Case Study in Saudi Arabia," Sustainability, MDPI, vol. 15(2), pages 1-22, January.
    6. Stephan Leitner, 2021. "On the dynamics emerging from pandemics and infodemics," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 20(1), pages 135-141, June.
    7. Stefano Guarino & Enrico Mastrostefano & Massimo Bernaschi & Alessandro Celestini & Marco Cianfriglia & Davide Torre & Lena Rebecca Zastrow, 2021. "Inferring Urban Social Networks from Publicly Available Data," Future Internet, MDPI, vol. 13(5), pages 1-45, April.
    8. Andreas Tolk & Jennifer A. Richkus & F. LeRon Shults & Wesley J. Wildman, 2023. "Computational Decision Support for Socio-Technical Awareness of Land-Use Planning under Complexity—A Dam Resilience Planning Case Study," Land, MDPI, vol. 12(5), pages 1-20, April.
    9. Svitlana Kolosok & Yuriy Bilan & Tetiana Vasylieva & Adam Wojciechowski & Michał Morawski, 2021. "A Scoping Review of Renewable Energy, Sustainability and the Environment," Energies, MDPI, vol. 14(15), pages 1-19, July.
    10. Moritz Kersting & Andreas Bossert & Leif Sörensen & Benjamin Wacker & Jan Chr. Schlüter, 2021. "Predicting effectiveness of countermeasures during the COVID-19 outbreak in South Africa using agent-based simulation," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-15, December.
    11. Stephan Leitner & Bartosz Gula & Dietmar Jannach & Ulrike Krieg-Holz & Friederike Wall, 2021. "Understanding the dynamics emerging from infodemics: a call to action for interdisciplinary research," SN Business & Economics, Springer, vol. 1(1), pages 1-18, January.
    12. F. LeRon Shults & Wesley J. Wildman, 2020. "Human Simulation and Sustainability: Ontological, Epistemological, and Ethical Reflections," Sustainability, MDPI, vol. 12(23), pages 1-16, December.
    13. Talal Daghriri & Michael Proctor & Sarah Matthews, 2022. "Evolution of Select Epidemiological Modeling and the Rise of Population Sentiment Analysis: A Literature Review and COVID-19 Sentiment Illustration," IJERPH, MDPI, vol. 19(6), pages 1-20, March.
    14. Friederike Wall, 2021. "Compliance to “Unpleasant” actions of crisis management: some remarks from a management control perspective," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 20(1), pages 159-164, June.
    15. Zengqing Wu & Run Peng & Xu Han & Shuyuan Zheng & Yixin Zhang & Chuan Xiao, 2023. "Smart Agent-Based Modeling: On the Use of Large Language Models in Computer Simulations," Papers 2311.06330, arXiv.org, revised Dec 2023.

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