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

大流行 爆发 行动号召 动作(物理) 2019年冠状病毒病(COVID-19) 2019-20冠状病毒爆发 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 病毒学 计算机科学 生物 医学 业务 传染病(医学专业) 疾病 物理 营销 病理 量子力学
作者
Flaminio Squazzoni,Gary Polhill,Bruce Edmonds,Petra Ahrweiler,Patrycja Antosz,Geeske Scholz,E.J.L. Chappin,Melania Borit,Harko Verhagen,Francesca Giardini,Nigel Gilbert
出处
期刊:Journal of Artificial Societies and Social Simulation [University of Surrey]
卷期号:23 (2) 被引量:90
标识
DOI:10.18564/jasss.4298
摘要

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.

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