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1000 Titel
  • How evolutionary behavioural sciences can help us understand behaviour in a pandemic
1000 Autor/in
  1. Arnot, Megan |
  2. Brandl, Eva |
  3. Campbell, O L K |
  4. Chen, Yuan |
  5. Du, Juan |
  6. Dyble, Mark |
  7. Emmott, Emily H |
  8. Ge, Erhao |
  9. Kretschmer, Luke D W |
  10. Mace, Ruth |
  11. Micheletti, Alberto J C |
  12. Nila, Sarah |
  13. Peacey, Sarah |
  14. Salali, Gul Deniz |
  15. Zhang, Hanzhi |
1000 Erscheinungsjahr 2020
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2020-10-24
1000 Erschienen in
1000 Quellenangabe
  • 2020(1):264-278
1000 Copyrightjahr
  • 2020
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1093/emph/eoaa038 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665496/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • The 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.
1000 Sacherschließung
gnd 1206347392 COVID-19
lokal behaviour change
lokal cultural evolution
lokal lockdown
lokal behavioural ecology
lokal social distancing
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-6293-5202|https://frl.publisso.de/adhoc/uri/QnJhbmRsLCBFdmE=|https://frl.publisso.de/adhoc/uri/Q2FtcGJlbGwsIE8gTCBL|https://orcid.org/0000-0002-7069-1631|https://frl.publisso.de/adhoc/uri/RHUsIEp1YW4=|https://frl.publisso.de/adhoc/uri/RHlibGUsIE1hcms=|https://frl.publisso.de/adhoc/uri/RW1tb3R0LCBFbWlseSBI|https://frl.publisso.de/adhoc/uri/R2UsIEVyaGFv|https://frl.publisso.de/adhoc/uri/S3JldHNjaG1lciwgTHVrZSBEIFc=|https://frl.publisso.de/adhoc/uri/TWFjZSwgUnV0aA==|https://frl.publisso.de/adhoc/uri/TWljaGVsZXR0aSwgQWxiZXJ0byBKIEM=|https://frl.publisso.de/adhoc/uri/TmlsYSwgU2FyYWg=|https://frl.publisso.de/adhoc/uri/UGVhY2V5LCBTYXJhaA==|https://orcid.org/0000-0001-9538-3064|https://frl.publisso.de/adhoc/uri/WmhhbmcsIEhhbnpoaQ==
1000 Label
1000 Förderer
  1. Agence Nationale de la Recherche |
  2. British Academy Postdoctoral Research Fellowship |
  3. ESRC-BBSRC Soc-B Centre for Doctoral Training |
1000 Fördernummer
  1. ANR 17-EURE-0010
  2. SRG\171409
  3. ES/P000347/1
1000 Förderprogramm
  1. Investissement d’Avenir programme
  2. -
  3. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Agence Nationale de la Recherche |
    1000 Förderprogramm Investissement d’Avenir programme
    1000 Fördernummer ANR 17-EURE-0010
  2. 1000 joinedFunding-child
    1000 Förderer British Academy Postdoctoral Research Fellowship |
    1000 Förderprogramm -
    1000 Fördernummer SRG\171409
  3. 1000 joinedFunding-child
    1000 Förderer ESRC-BBSRC Soc-B Centre for Doctoral Training |
    1000 Förderprogramm -
    1000 Fördernummer ES/P000347/1
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6428267.rdf
1000 Erstellt am 2021-06-22T10:40:27.737+0200
1000 Erstellt von 218
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1000 Bearbeitet von 317
1000 Zuletzt bearbeitet Mon Aug 15 14:59:09 CEST 2022
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1000 Vgl. frl:6428267
1000 Oai Id
  1. oai:frl.publisso.de:frl:6428267 |
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