JMIR Public Health Surveill. 2021 Jun 2. doi: 10.2196/29205. Online ahead of print.
BACKGROUND: Previous studies have shown various social determinants of health (SDOH) may have contributed to the disparities in COVID-19 incidence and mortality among minorities and underserved populations at county or zip code level.
OBJECTIVE: This analysis was carried out at a granular spatial resolution of census tracts, to explore the spatial patterns and contextual SDOH associated with COVID-19 incidence from a Hispanic population mostly consisting of Mexican Americans living in Cameron County, TX on the border of US and Mexico. We performed age-stratified analysis to identify different contributing SDOH and quantify their effects by age groups.
METHODS: We included all reported COVID-19 positive cases confirmed by reverse transcription-polymerase chain reaction (RT-PCR) testing between March 19th (first case reported) and December 16th, 2020 in Cameron County, TX. Confirmed COVID-19 cases were aggregated to weekly counts by census tracts. We adopted a Bayesian spatiotemporal Negative Binomial model to investigate the COVID-19 incidence rate, in relation to census tract demographics and SDOH obtained from the American Community Survey (ACS). Moreover, we investigated the impact of local mitigation policy on COVID-19 by creating a binary variable “shelter-in-place”. The analysis was performed on all COVID-19 confirmed cases, and also age-stratified subgroups.
RESULTS: Our analysis revealed that the relative incidence risk (RR) of COVID-19 was higher among census tracts with a higher percentage of single parent household (RR=1.016; 95% CI: [1.005, 1.027]), and higher percentage of population of limited English proficiency (RR=1.015; 95% CI: [1.003, 1.028]). Lower RR was associated with lower income (RR=0.972; 95% CI: [0.953, 0.993]), and the percentage of population under 18 (RR=0.976; 95% CI: [0.959, 0.993]). The most significant association was related to the “shelter-in-place” variable, where the incidence risk of COVID-19 was reduced by over 50% comparing the time periods when policy present vs policy absent (RR=0.506; 95% [0.454, 0.563]). Moreover, age-stratified analyses identified different significant contributing factors, and varying magnitude of the “shelter-in-place” effect.
CONCLUSIONS: In our study, SDOH including social environment and local emergency measure were identified in relation to COVID-19 incidence risk at the census tract level in a highly disadvantaged population with limited health care access and high prevalence of chronic conditions. Results from our analysis provide key knowledge to design efficient testing strategies and assist local public health departments for COVID-19 control, mitigation and implementation of vaccine strategies.