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.
Highlights
Industries, companies, small businesses, and shops have been shut if they are not essential. This will have longterm economic consequences, such as the failure of many small businesses and a decline in private investment — consequences related to the severity of policy measures which, at the moment, do not have a defined expiry date
Considering its impact and relevance, the Imperial College model has been criticized for various reasons: (a) it does not enable the consideration of other policy options, (b) it does not use su icient data across di erent contexts, while claiming general findings, (c) it does not help to understand social conditions and consequences of measures
In response to the lack of behavioural realism in many of the currently used in the public debate, there has been a proliferation of examples of open source agent-based implementations, though authors admitted that they are probably illustrations. While this tells more about the academic e ervescence and selective attention that typically characterise emergencies and outbreaks, the competitive advantage of the Imperial College model and similar models, which at the present stage cannot be seriously tested by the community, makes these e orts of uncertain value for immediate responses, whereas they could be relevant for understanding long-term socio-economic consequences of policy measures
Summary
. Considering its impact and relevance, the Imperial College model has been criticized for various reasons: (a) it does not enable the consideration of other policy options, (b) it does not use su icient data across di erent contexts, while claiming general findings, (c) it does not help to understand social conditions and consequences of measures.
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