COVID-19 fatalities by zip codes and socioeconomic indicators across various U.S. regions

Abstract

Background There is a paucity of literature addressing COVID-19 case-fatality ratios (CFR) by zip code (ZC). We aim to analyze trends in COVID-19 CFR, population density, and socioeconomic status (SES) indicators (unemployment, median household income) to identify ZCs heavily burdened by COVID-19. Methods Cross-sectional study to investigate the US prevalence of COVD-19 fatalities by ZC and SES. CFRs were calculated from state/county Departments of Health. Inclusion criteria were counties that reported cases/deaths by ZC and a CFR≥2%. This study was reported in line with the STROCSS criteria. Results 609/1,853 ZCs, spanning 327 counties in 7 states had CFRs ≥2%. A significant positive correlation was found between the CFR and median household income (Pearson correlation:0.107; 95% CI [289.1,1937.9]; p < 0.001). No significant correlations exist between the CFR, and population/mi (Sen-Crowe et al., 2020) [2] or unemployment rate. Significant associations exist between the CFR and young males and elderly females without public insurance. CFR was inversely associated with persons aged <44 and individuals aged ≥65. The percentage of nursing homes (NHs) within cities residing within high CFR ZCs range from 8.7% to 67.6%. Conclusion Significant positive association was found between the CFR and median household income. Population/mi (Sen-Crowe et al., 2020) [2] and unemployment rates, did not correlate to CFR. NHs were heavily distributed in high CFR zip codes. We recommend the targeted vaccination of zip codes with a large proportion of long-term care facilities. Finally, we recommend for improved screening and safety guidelines for vulnerable populations (e.g nursing home residents) and established protocols for when there is evidence of substantial infectious spread.

Effects of the built environment and human factors on the spread of COVID-19: A systematic literature review

“… Iyanda et al (2021) found a negative association between the number of cases/deaths and income. Interestingly, Sen-Crowe et al (2021) found a weak, positive and significant correlation between the share of cases of death and income. Poverty was another factor included in three papers conducted in the US.…”

“…Based on our review, many studies conducted in countries such as the US ( Sarmadi et al, 2021 ; White and Hébert-Dufresne, 2020 ), Italy ( Ilardi et al, 2020 ), Iran ( Ahmadi et al, 2020 ), Bangladesh ( Sharif et al, 2021 ; Alam, 2021 ; Rahman et al, 2021 ), Oman ( Al Kindi et al, 2021 ), France ( Tchicaya et al, 2021 ), Nigeria ( Bayode et al, 2022 ) and Scotland ( Rideout et al, 2021 ) found population density as a positive and significant predictor of COVID-19 cases on state scale. However, about 40 % of studies reported that population density is not a significant factor to explain the difference in COVID-19 cases in different states ( Ramírez-Aldana et al, 2020 ; Gupta et al, 2020 ; Perone, 2021 ; Gargiulo et al, 2020 ; Basellini and Camarda, 2021 ; Pilkington et al, 2021 ; Sen-Crowe et al, 2021 ).…”

Socioeconomic Inequalities in COVID-19 Incidence During Different Epidemic Phases in South Korea

“…Each measure represents a unique contribution to the socioeconomic association. Specifically, associations with COVID-19 were consistently observed for median household income ( 12 , 13 ) and minor ethnicity ( 1 , 14 , 15 ) but findings for deprivation index ( 16 , 17 ) and unemployment rate ( 13 , 14 ) were inconsistent, indicating that area-level SES measures have different values across time and place and that how they are measured is important ( 18 ).…”

Trauma Prevalence and Resource Utilization During 4 COVID-19 “Surges”: A National Analysis of Trauma Patients From 92 Trauma Centers

“… 6 , 7 , 8 Despite the enforcement of social distancing measures and the development of vaccines, COVID-related deaths continue to escalate especially among minorities and elderly populations. 9 , 10 , 11 , 12 …”