Exploring spatially heterogeneous associations between COVID-19 cases and the influencing factors in England

ABSTRACT

Coronavirus pandemic (COVID-19), caused by the SARS-CoV-2 virus, has spread expeditiously around the world since early 2020 and led to a tremendous number of deaths, severely impacting overall human well-being. The pandemic largely affected economic and social activities. The beneficial way to slow down or prevent the transmission is to be well informed about the disease and how the virus spreads. Therefore, analyzing factors that affect the COVID-19 transmission was of great importance in disease control and policy decisions. Socio-demographic factors show considerable impacts on the rate of COVID-19 infection, but the correlations would vary both temporally and spatially. Generally, the global correlation coefficients of all variables rocketed at the beginning of the COVID-19 outbreak and plateaued at a high level eventually. Then localized correlations were also calculated to map the spatial distribution of correlation coefficients. Results show that in the north of England, all socio-demographic factors are highly related to the COVID-19 cases with figures above 0.75, arising from the climatic, cultural and economic differences. As time flowed for both 55+ age structure and GDP, the southern part experienced sustainable increases in correlation values, which eventually rose above 0.5 at most locations. This finding confirmed our expectation that the higher GDP was, the more COVID-19 cases were, since high GDP always accompanies by more entertainment activities and more chances for face-To-face human contact. However, the interesting point was that around London, the GDP maintained uncorrelated and even negatively correlated with the cumulative cases as time went by. As for the number of pubs, the overall spatial distribution of correlation coefficients experienced unremarkable changes at three-Time points. The variable was significantly correlated with COVID-19 cases in the north. In contrast, in the south values kept below 0.5. Overall, this study provides an interesting view on investigating the relative factors of the COVID-19 pandemic. © 2022 IEEE.