TY - JOUR

T1 - Computational Models That Matter During a Global Pandemic Outbreak

T2 - A Call to Action

AU - Squazzoni, Flaminio

AU - Polhill, J. Gareth

AU - Edmonds, Bruce

AU - Ahrweiler, Petra

AU - Antosz, Patrycja

AU - Scholz, Geeske

AU - Chappin, Emile

AU - Borit, Melania

AU - Verhagen, Harko

AU - Giardini, Francesca

AU - Gilbert, Nigel

PY - 2020/3/31

Y1 - 2020/3/31

N2 - 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.

AB - 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.

KW - COVID-19

KW - Pandemic disease

KW - Agent-based model

KW - Modelling

KW - Policy

KW - Data

KW - SOCIAL-SCIENCES

KW - DYNAMICS

KW - IMPACT

KW - Agent-Based Models

KW - Pandemic Disease

U2 - 10.18564/jasss.4298

DO - 10.18564/jasss.4298

M3 - Article

VL - 23

JO - Journal of Artificial Societies and Social Simulation

JF - Journal of Artificial Societies and Social Simulation

SN - 1460-7425

IS - 2

M1 - 10

ER -