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Evolution, Medicine and Public Health
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How evolutionary behavioural sciences can help us understand behaviour in a pandemic

Authors: Megan Arnot; Eva Brandl; O L K Campbell; Yuan Chen; Juan Du; Mark Dyble; Emily H Emmott; +8 Authors

How evolutionary behavioural sciences can help us understand behaviour in a pandemic

Abstract

AbstractThe COVID-19 pandemic has brought science into the public eye and to the attention of governments more than ever before. Much of this attention is on work in epidemiology, virology and public health, with most behavioural advice in public health focusing squarely on ‘proximate’ determinants of behaviour. While epidemiological models are powerful tools to predict the spread of disease when human behaviour is stable, most do not incorporate behavioural change. The evolutionary basis of our preferences and the cultural evolutionary dynamics of our beliefs drive behavioural change, so understanding these evolutionary processes can help inform individual and government decision-making in the face of a pandemic.Lay summary: The COVID-19 pandemic has brought behavioural sciences into the public eye: Without vaccinations, stopping the spread of the virus must rely on behaviour change by limiting contact between people. On the face of it, “stop seeing people” sounds simple. In practice, this is hard. Here we outline how an evolutionary perspective on behaviour change can provide additional insights. Evolutionary theory postulates that our psychology and behaviour did not evolve to maximize our health or that of others. Instead, individuals are expected to act to maximise their inclusive fitness (i.e, spreading our genes) – which can lead to a conflict between behaviours that are in the best interests for the individual, and behaviours that stop the spread of the virus. By examining the ultimate explanations of behaviour related to pandemic-management (such as behavioural compliance and social distancing), we conclude that “good of the group” arguments and “one size fits all” policies are unlikely to encourage behaviour change over the long-term. Sustained behaviour change to keep pandemics at bay is much more likely to emerge from environmental change, so governments and policy makers may need to facilitate significant social change – such as improving life experiences for disadvantaged groups.

Country
France
Subjects by Vocabulary

Microsoft Academic Graph classification: Behavioural sciences Best interests Sociocultural evolution Evolutionary dynamics business.industry Social distance Social change Inclusive fitness Public relations Disadvantaged Psychology business

Keywords

Social distancing, Behavioural ecology, Health, Toxicology and Mutagenesis, Cultural evolution, COVID-19 ; behaviour change ; cultural evolution ; lockdown ; behavioural ecology ; social distancing, Medicine (miscellaneous), Review, Lockdown, AcademicSubjects/MED00860, Ecology, Evolution, Behavior and Systematics, AcademicSubjects/SCI01130, Behaviour change, COVID-19, [SHS.ECO]Humanities and Social Sciences/Economics and Finance

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  • citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    32
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
32
Top 1%
Top 10%
Top 1%
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