Variation in COVID-19 Outbreaks at U.S. State and County Levels

Abstract

Objective

The COVID-19 pandemic poses an unprecedented threat to the health and economic prosperity of the world’s population. Yet, because not all regions are affected equally, this research aims to understand whether the relative growth rate of the initial outbreak in early 2020 varied significantly between U.S. states and counties.

Study design

Based on publicly available case data from across the U.S., the initial outbreak is statistically modeled as an exponential curve.

Methods

Regional differences are visually compared using geo maps and spaghetti lines. Additionally, they are statistically analyzed as an unconditional model (one-way random effects ANOVA estimated in HLM 7.03); the bias between state- and county-level models is evidenced with distribution tests and Bland-Altman plots (using SPSS 26).

Results

At the state level, the outbreak rate follows a normal distribution with an average relative growth rate of 0.197 (doubling time 3.518 days). But there is a low degree of reliability between state-wide and county-specific data reported (ICC = 0.169, p < 0.001), with a bias of 0.070 (standard deviation 0.062) as shown with a Bland-Altman plot. Hence, there is significant variation in the outbreak between U.S. states and counties.

Conclusions

The results emphasize the need for policy makers to look at the pandemic from the smallest population subdivision possible, so that countermeasures can be implemented, and critical resources provided effectively. Further research is needed to understand the reasons for these regional differences.

Graphical abstract

Highlights

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  The COVID-19 pandemic appears to affect some countries or regions in different ways.

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  Based on a statistical model, the research aims to understand whether the outbreak varies significantly between U.S. states and counties.

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  A low degree of reliability between state-wide and county-specific data is found.

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  Policy makers are advised to implement countermeasures and provide critical resources at the smallest population subdivision possible.