4.7 Article

Changing readiness to mitigate SARS-CoV-2 steered long-term epidemic and social trajectories

Journal

SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-021-93248-y

Keywords

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Funding

  1. Helmholtz society

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This study examines the impact of societal responses on pandemics and the predictability of these responses. It suggests that mitigation measures such as social distancing can minimize the conflicting objectives of disease-related mortality and the consequences of mitigation. The study finds that the dynamic changes in readiness H affect the implementation of mitigation measures and the development of epidemics.
Societal responses crucially shape the course of a pandemic, but are difficult to predict. Mitigation measures such as social distancing are here assumed to minimize a utility function that consists of two conflicting sub-targets, the disease related mortality and the multifaceted consequences of mitigation. The relative weight of the two sub-targets defines the mitigation readiness H, which entails the political, social, and psychological aspects of decision making. The dynamics of social and behavioral mitigation thus follows an adaptive rule, which in turn is mediated by a non-adaptive dynamics of H. This framework for social dynamics is integrated into an epidemiological model and applied to the ongoing SARS-CoV-2 pandemic. Unperturbed simulations accurately reproduce diverse epidemic and mitigation trajectories from 2020 to 2021, reported from 11 European countries, Iran, and 8 US states. High regional variability in the severity and duration of the spring lockdown and in peak mortality rates of the first SARS-CoV-2 wave can be explained by differences in the reconstructed readiness H. A ubiquitous temporal decrease of H has greatly intensified second and third waves and slowed down their decay. The unprecedented skill of the model suggests that the combination of an adaptive and a non-adaptive rule may constitute a more fundamental mode in social dynamics. Its implementation in an epidemic context can produce realistic long-term scenarios relevant for strategic planning, such as on the feasibility of a zero-infection target or on the evolutionary arms race between mutations of SARS-CoV-2 and social responses.

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