ABSTRACT
BACKGROUND: The spread of the COVID-19 pandemic throughout the world presents an unprecedented challenge to public health inequities. People who use opioids may be a vulnerable group disproportionately impacted by the current pandemic, however, the limited prior research in this area makes it unclear whether COVID-19 and opioid use outcomes may be related, and whether other environmental and socioeconomic factors might play a role in explaining COVID-19 mortality. The objective of this study is to evaluate the association between opioid-related mortality and COVID-19 mortality across U.S. counties. METHODS: Data from 3142 counties across the U.S. were used to model the cumulative count of deaths due to COVID-19 up to June 2, 2020. A multivariable negative-binomial regression model was employed to evaluate the adjusted COVID-19 mortality rate ratios (aMRR). RESULTS: After controlling for covariates, counties with higher rates of opioid-related mortality per 100,000 persons were found to be significantly associated with higher rates of COVID-19 mortality (aMRR: 1.0134; 95% CI [1.0054, 1.0214]; P = 0.001). Counties with higher average daily Particulate Matter (PM2.5) exposure also saw significantly higher rates of COVID-19 mortality. Analyses revealed rural counties, counties with higher percentages of non-Hispanic whites, and counties with increased average maximum temperatures are significantly associated with lower mortality rates from COVID-19. CONCLUSIONS: This study indicates need for public health efforts in hard hit COVID-19 regions to also focus prevention efforts on overdose risk among people who use opioids. Future studies using individual-level data are needed to allow for detailed inferences.
ABSTRACT
With the emergence of the novel SARS-CoV-2 and the disease it causes; COVID-19, compliance with/adherence to protective measures is needed. Information is needed on which measures are, or are not, being undertaken. Data collected from the COVID Impact Survey, conducted by the non-partisan and objective research organization NORC at the University of Chicago on April, May, and June of 2020, were analyzed through weighted Quasi-Poisson regression modeling to determine the association of demographics, socioeconomics, and health conditions with protective health measures taken at the individual level in response to COVID-19. The three surveys included data from 18 regional areas including 10 states (CA, CO, FL, LA, MN, MO, MT, NY, OR, and TX) and 8 Metropolitan Statistical Areas (Atlanta, GA; Baltimore, MD; Birmingham, AL; Chicago, IL; Cleveland and Columbus, OH; Phoenix, AZ; and Pittsburgh, PA). Individuals with higher incomes, insurance, higher education levels, large household size, age 60+, females, minorities, those who have asthma, have hypertension, overweight or obese, and those who suffer from mental health issues during the pandemic were significantly more likely to report taking precautionary protective measures relative to their counterparts. Protective measures for the three subgroups with a known relationship to COVID-19 (positive for COVID-19, knowing an individual with COVID-19, and knowing someone who had died from COVID-19) were strongly associated with the protective health measures of washing hands, avoiding public places, and canceling social engagements. This study provides first baseline data on the response to the national COVID-19 pandemic at the individual level in the US. The found heterogeneity in the response to this pandemic by different variables can inform future research and interventions to reduce exposure to the novel SARS-CoV-2 virus.