Social markers of a pandemic: modeling the association between cultural norms and COVID-19 spread data

Abstract While cross-national differences of the epidemic curves of COVID-19 become evident, social markers of such variability are still unexplored. In order to investigate how certain social norms may underlie the heterogeneity of the spread of infections, global social data (including cultural va...

Full description

Bibliographic Details
Main Authors: Máté Kapitány-Fövény, Mihály Sulyok
Format: Article
Language:English
Published: Springer Nature 2020-09-01
Series:Humanities & Social Sciences Communications
Online Access:https://doi.org/10.1057/s41599-020-00590-z
id doaj-0efadac995f34042a4688ee7e1758d72
record_format Article
spelling doaj-0efadac995f34042a4688ee7e1758d722021-09-19T11:40:03ZengSpringer NatureHumanities & Social Sciences Communications2662-99922020-09-01711910.1057/s41599-020-00590-zSocial markers of a pandemic: modeling the association between cultural norms and COVID-19 spread dataMáté Kapitány-Fövény0Mihály Sulyok1Faculty of Health Sciences, Semmelweis UniversityInstitute of Tropical Medicine, Eberhard Karls UniversityAbstract While cross-national differences of the epidemic curves of COVID-19 become evident, social markers of such variability are still unexplored. In order to investigate how certain social norms may underlie the heterogeneity of the spread of infections, global social data (including cultural values, indices of prosperity, and government effectiveness) and covariates (such as climate zone, economic indicator, and healthcare access and quality) of early transmission dynamics of COVID-19 were collected. Model-based clustering and random forest regression analysis were applied to identify distinct groups of societies and explore predictors of COVID-19 doubling time. Clustering revealed four groups: (1) reserved; (2) drifting; (3) assertive; and (4) compliant societies. Compliant societies from dry climate zones showed the highest doubling times in spite of increased population densities. Most relevant predictors of doubling time were population density, freedom of assembly and association, and agency, underlining the importance of social factors in the hetereogeneity of COVID-19 transmission rates. Our cluster typology might contribute to the explanation of cross-national variability in early transmission dynamics of highly infectious diseases.https://doi.org/10.1057/s41599-020-00590-z
collection DOAJ
language English
format Article
sources DOAJ
author Máté Kapitány-Fövény
Mihály Sulyok
spellingShingle Máté Kapitány-Fövény
Mihály Sulyok
Social markers of a pandemic: modeling the association between cultural norms and COVID-19 spread data
Humanities & Social Sciences Communications
author_facet Máté Kapitány-Fövény
Mihály Sulyok
author_sort Máté Kapitány-Fövény
title Social markers of a pandemic: modeling the association between cultural norms and COVID-19 spread data
title_short Social markers of a pandemic: modeling the association between cultural norms and COVID-19 spread data
title_full Social markers of a pandemic: modeling the association between cultural norms and COVID-19 spread data
title_fullStr Social markers of a pandemic: modeling the association between cultural norms and COVID-19 spread data
title_full_unstemmed Social markers of a pandemic: modeling the association between cultural norms and COVID-19 spread data
title_sort social markers of a pandemic: modeling the association between cultural norms and covid-19 spread data
publisher Springer Nature
series Humanities & Social Sciences Communications
issn 2662-9992
publishDate 2020-09-01
description Abstract While cross-national differences of the epidemic curves of COVID-19 become evident, social markers of such variability are still unexplored. In order to investigate how certain social norms may underlie the heterogeneity of the spread of infections, global social data (including cultural values, indices of prosperity, and government effectiveness) and covariates (such as climate zone, economic indicator, and healthcare access and quality) of early transmission dynamics of COVID-19 were collected. Model-based clustering and random forest regression analysis were applied to identify distinct groups of societies and explore predictors of COVID-19 doubling time. Clustering revealed four groups: (1) reserved; (2) drifting; (3) assertive; and (4) compliant societies. Compliant societies from dry climate zones showed the highest doubling times in spite of increased population densities. Most relevant predictors of doubling time were population density, freedom of assembly and association, and agency, underlining the importance of social factors in the hetereogeneity of COVID-19 transmission rates. Our cluster typology might contribute to the explanation of cross-national variability in early transmission dynamics of highly infectious diseases.
url https://doi.org/10.1057/s41599-020-00590-z
work_keys_str_mv AT matekapitanyfoveny socialmarkersofapandemicmodelingtheassociationbetweenculturalnormsandcovid19spreaddata
AT mihalysulyok socialmarkersofapandemicmodelingtheassociationbetweenculturalnormsandcovid19spreaddata
_version_ 1717375570062344192