Abstract

This study investigates the potential impacts of different socio-economic-demographic (henceforth, SED) factors in COVID-19-related stay-at-home-tendencies (henceforth, COVID-19-SAHTs) in the US. This requires a state-level investigation rather than a country-level since the US states exhibit large SED differences from one another. To this aim, the K-Means Cluster analysis and the panel autoregressive distributed lag models are applied. The main empirical finding indicates that different SED factors in different US states matter in COVID-19-SAHTs. Additionally, people in the states which have more equal income distribution, higher rate of basic literacy, and less population density stay at their homes more during the COVID-19 pandemic. These findings may provide some vital pre-information to the state policymakers about how much the people from different SED statuses will tend to comply with future COVID-19 state restrictions such as stay-at-home orders and others. Until the scientists create a proven vaccine for the coronavirus, states will most likely continue to issue some COVID-19 restrictions to reduce the spread of this pandemic.

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Cite as

Ongan, S. & Gocer, I. 2023, 'Do different socio-economic-demographic factors matter in COVID-19 related stay-at-home-tendencies across the US States?', Journal of Health Management, 25(2), pp. 219-224. https://doi.org/10.1177/09720634231177341

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Last updated: 06 March 2024
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