Abstract
Background: Human mobility among geographic units is a possible cause of the widespread transmission of COVID-19 across regions. Due to the pressure of epidemic control and economic recovery, the states of the United States have adopted different policies for mobility limitations. Assessing the impact of these policies on the spatiotemporal interaction of COVID-19 transmission among counties in each state is critical to formulating the epidemic policies.Methods: The study utilized Moran’s I index and K-means clustering to investigate the time-varying spatial autocorrelation effect of 49 states (except the District of Colombia) with the daily new cases at the county level from Jan 22, 2020, to August 20, 2020. Based on the dynamic spatial lag model (SLM) and the SIR model with unreported infection rate (SIRu), the integrated SLM-SIRu model was constructed to estimate the inter-county spatiotemporal interaction coefficient of daily new cases in each state, which was further explored by Pearson correlation and stepwise OLS regression with socioeconomic factors.Results: The K-means clustering divided the time-varying spatial autocorrelation curves of 49 states into four types: continuous increasing, fluctuating increasing, weak positive, and weak negative. The Pearson correlation analysis showed that the spatiotemporal interaction coefficients in each state estimated by SLM-SIRu were significantly positively correlated with median age, population density, and the proportion of international immigrants and the highly educated population, but negatively correlated with the birth rate. The voting rate for Donald Trump in the 2016 U.S. presidential election showed a weak negative correlation. Further stepwise OLS regression retained only three positive correlated variables: poverty rate, population density, and the highly educated population proportion.Interpretation: This result suggests that various state policies in the U.S. have imposed different impacts on COVID-19 transmission among counties. All states should provide more protection and support for the low-income population, high-density populated states need to strengthen regional mobility restrictions, and the highly educated population should reduce unnecessary regional movement and strengthen self-protection.
Highlights
COVID-19 is still rampaging around the world[1, 2], showing obvious spatial differences in global geographic distribution[3]
Compared with the potential climate correlations implied by some studies [7, 8], more studies indicate that population density[9], health measures, and mobility restrictions[10]have a greater impact on the spread of COVID-19
This study provides an integrated model to capture the spatiotemporal interaction effect, which may help assess the impact of cross-regional mobility on epidemic transmission and assist the government in optimize COVID-19 control policy
Summary
COVID-19 is still rampaging around the world[1, 2], showing obvious spatial differences in global geographic distribution[3]. The United States, as the country with the most developed economy and the highest level of medical care, has the largest number of infections and shows geographic differences in COVID-19 transmission, which has become an important global health research issue for pandemic control. Based on the dynamic spatial lag model (SLM) and the SIR model with unreported infection rate (SIRu), the integrated SLM-SIRu model was constructed to estimate the inter-county spatiotemporal interaction coefficient of daily new cases in each state, which was further explored by Pearson correlation and stepwise OLS regression with socioeconomic factors. The Pearson correlation analysis showed that the spatiotemporal interaction coefficients in each state estimated by SLM-SIRu were significantly positively correlated with median age, population density, and the proportion of international immigrants and the highly educated population, but negatively correlated with the birth rate. All states should provide more protection and support for the low-income population, high-density populated states need to strengthen regional mobility restrictions, and the highly educated population should reduce unnecessary regional movement and strengthen self-protection
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
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 callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
