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Abstract

Publishing Note: This article has been published in its peer-reviewed and accepted form as a post-print version. The fully formatted version of the article will be published on this record when it is available.


ABSTRACT

Background: As COVID-19 began to spread worldwide, local socioeconomic and health factors and nonpharmaceutical interventions may have affected epidemiological outcomes. To investigate the associations between public health orders, behavior, and population factors, and early epidemic dynamics, we investigated variation among counties in the U.S. state of Georgia. There, a large early outbreak occurred in March 2020 with varying levels of local nonpharmaceutical interventions prior to statewide orders, in addition to considerable socioeconomic disparities.

Methods: We conducted regressions to identify predictors of (1) local public health orders, (2) mobility as a proxy for behavioral responses to public health orders, and (3) epidemiological outcomes (i.e., cases and deaths). We used an event study to determine whether social distancing and shelter-in-place orders caused a behavioral change by using mobility as a proxy for social contacts.

Results: Counties at greater risk for early outbreaks (i.e., larger populations and earlier first reported cases) with a greater share of Democratic voters were more likely to introduce local public health orders. Social distancing orders gradually reduced mobility by 19% ten days after their introduction, and lower mobility was associated with fewer cases and deaths. Air pollution and population size were significant predictors of cases and deaths, while larger elderly or Black population were predictors of lower mobility and greater cases, suggesting self-protective behavior in vulnerable populations.

Conclusions: Early epidemiological outcomes reflected both responses to policy orders and existing health and socioeconomic disparities related to ability to socially distance and vulnerability to disease. Teasing apart the impact of behavior changes and population factors is difficult because the epidemic is embedded in a complex social system with multiple potential feedbacks: socioeconomic factors could affect both the implementation of policy orders and epidemic dynamics directly; policy orders may both respond to existing epidemic conditions and alter future epidemic trajectories.

Keywords: COVID-19, policy, mobility, socioeconomic, shelter-in-place, social distancing

First Page

21

Last Page

41

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Supplemental Files
GA Covid_Supplement_sub1.docx (276 kB)
Supplementary Material
ref_jgpha2021080204.pdf (75 kB)
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