Abstract
On March 13, 2020, the World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) caused by the novel coronavirus SARS-CoV2 a pandemic. Since then the virus has infected over 9.1 million individuals and resulted in over 470,000 deaths worldwide (as of June 24, 2020). Here, we discuss the spatial correlation between county population health rankings and the incidence of COVID-19 cases and COVID-19 related deaths in the United States. We analyzed the spread of the disease based on multiple variables at the county level, using publicly available data on the numbers of confirmed cases and deaths, intensive care unit beds and socio-demographic, and healthcare resources in the U.S. Our results indicate substantial geographical variations in the distribution of COVID-19 cases and deaths across the US counties. There was significant positive global spatial correlation between the percentage of Black Americans and cases of COVID-19 (Moran I = 0.174 and 0.264, p < 0.0001). A similar result was found for the global spatial correlation between the percentage of Black American and deaths due to COVID-19 at the county level in the U.S. (Moran I = 0.264, p < 0.0001). There was no significant spatial correlation between the Hispanic population and COVID-19 cases and deaths; however, a higher percentage of non-Hispanic white was significantly negatively spatially correlated with cases (Moran I = –0.203, p < 0.0001) and deaths (Moran I = –0.137, p < 0.0001) from the disease. This study showed significant but weak spatial autocorrelation between the number of intensive care unit beds and COVID-19 cases (Moran I = 0.08, p < 0.0001) and deaths (Moran I = 0.15, p < 0.0001), respectively. These findings provide more detail into the interplay between the infectious disease and healthcare-related characteristics of the population. Only by understanding these relationships will it be possible to mitigate the rate of spread and severity of the disease.
Highlights
In December 2019, a cluster of pneumonia cases with unknown etiology were reported in Wuhan, China [1, 2]
We investigated the potential effects of county-level factors including the number of hospital beds, intensive care units (ICU) beds, number of primary care physicians (PCPs), adult obesity, number of uninsured, number of flu vaccinations, and race on the incidence of and deaths from COVID-19
We observed moderate and high significant global spatial autocorrelation based on Queen Contiguity spatial-lag of order 1 in the distribution of COVID-19 cases and deaths across US counties (Global univariate Moran’s I =0.228, p < 0.0001), and (Global univariate Moran’s I =0.477, p < 0.0001), respectively
Summary
In December 2019, a cluster of pneumonia cases with unknown etiology were reported in Wuhan, China [1, 2]. COVID-19 primarily spread via respiratory droplets and has an incubation period of up to 14 days, with symptom onset occurring by 11.5 days in ∼97.5% of cases [6]. Viral shedding occurs mainly from the upper respiratory tract even in asymptomatic patients; thereby, making it difficult to institute preventative measures that rely on symptomatology [7, 8]. This has led to different transmission rates from previous outbreaks, and while SARS was essentially under control within 8 months, the trajectory for COVID-19 appears to be significantly different.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
