TY - JOUR
T1 - A machine learning analysis of the relationship of demographics and social gathering attendance from 41 countries during pandemic
AU - Szaszi, Barnabas
AU - Hajdu, Nandor
AU - Szecsi, Peter
AU - Tipton, Elizabeth
AU - Aczel, Balazs
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Knowing who to target with certain messages is the prerequisite of efficient public health campaigns during pandemics. Using the COVID-19 pandemic situation, we explored which facets of the society—defined by age, gender, income, and education levels—are the most likely to visit social gatherings and aggravate the spread of a disease. Analyzing the reported behavior of 87,169 individuals from 41 countries, we found that in the majority of the countries, the proportion of social gathering-goers was higher in male than female, younger than older, lower-educated than higher educated, and low-income than high-income subgroups of the populations. However, the data showed noteworthy heterogeneity between the countries warranting against generalizing from one country to another. The analysis also revealed that relative to other demographic factors, income was the strongest predictor of avoidance of social gatherings followed by age, education, and gender. Although the observed strength of these associations was relatively small, we argue that incorporating demographic-based segmentation into public health campaigns can increase the efficiency of campaigns with an important caveat: the exploration of these associations needs to be done on a country level before using the information to target populations in behavior change interventions.
AB - Knowing who to target with certain messages is the prerequisite of efficient public health campaigns during pandemics. Using the COVID-19 pandemic situation, we explored which facets of the society—defined by age, gender, income, and education levels—are the most likely to visit social gatherings and aggravate the spread of a disease. Analyzing the reported behavior of 87,169 individuals from 41 countries, we found that in the majority of the countries, the proportion of social gathering-goers was higher in male than female, younger than older, lower-educated than higher educated, and low-income than high-income subgroups of the populations. However, the data showed noteworthy heterogeneity between the countries warranting against generalizing from one country to another. The analysis also revealed that relative to other demographic factors, income was the strongest predictor of avoidance of social gatherings followed by age, education, and gender. Although the observed strength of these associations was relatively small, we argue that incorporating demographic-based segmentation into public health campaigns can increase the efficiency of campaigns with an important caveat: the exploration of these associations needs to be done on a country level before using the information to target populations in behavior change interventions.
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U2 - 10.1038/s41598-021-04305-5
DO - 10.1038/s41598-021-04305-5
M3 - Article
C2 - 35031631
AN - SCOPUS:85123096254
SN - 2045-2322
VL - 12
JO - Scientific reports
JF - Scientific reports
IS - 1
M1 - 724
ER -