The COVID-19-wildfire smoke paradox: Reduced risk of all-cause mortality due to wildfire smoke in Colorado during the first year of the COVID-19 pandemic.

BACKGROUND: In 2020, the American West faced two competing challenges: the COVID-19 pandemic and the worst wildfire season on record. Several studies have investigated the impact of wildfire smoke (WFS) on COVID-19 morbidity and mortality, but little is known about how these two public health challenges impact mortality risk for other causes. OBJECTIVES: Using a time-series design, we evaluated how daily risk of mortality due to WFS exposure differed for periods before and during the COVID-19 pandemic. METHODS: Our study included daily data for 11 counties in the Front Range region of Colorado (2010-2020). We assessed WFS exposure using data from the National Oceanic and Atmospheric Administration and used mortality counts from the Colorado Department of Public Health and Environment. We estimated the interaction between WFS and the pandemic (an indicator variable) on mortality risk using generalized additive models adjusted for year, day of week, fine particulate matter, ozone, temperature, and a smoothed term for day of year. RESULTS: WFS impacted the study area on 10% of county-days. We observed a positive association between the presence of WFS and all-cause mortality risk (incidence rate ratio (IRR) = 1.03, 95%CI: 1.01-1.04 for same-day exposures) during the period before the pandemic; however, WFS exposure during the pandemic resulted in decreased risk of all-cause mortality (IRR = 0.90, 95%CI: 0.87-0.93 for same-day exposures). DISCUSSION: We hypothesize that mitigation efforts during the first year of the pandemic, e.g., mask mandates, along with high ambient WFS levels encouraged health behaviors that reduced exposure to WFS and reduced risk of all-cause mortality. Our results suggest a need to examine how associations between WFS and mortality are impacted by pandemic-related factors and that there may be lessons from the pandemic that could be translated into health-protective policies during future wildfire events.

Association between air pollution and COVID-19 disease severity via Bayesian multinomial logistic regression with partially missing outcomes.

Recent ecological analyses suggest air pollution exposure may increase susceptibility to and severity of coronavirus disease 2019 (COVID-19). Individual-level studies are needed to clarify the relationship between air pollution exposure and COVID-19 outcomes. We conduct an individual-level analysis of long-term exposure to air pollution and weather on peak COVID-19 severity. We develop a Bayesian multinomial logistic regression model with a multiple imputation approach to impute partially missing health outcomes. Our approach is based on the stick-breaking representation of the multinomial distribution, which offers computational advantages, but presents challenges in interpreting regression coefficients. We propose a novel inferential approach to address these challenges. In a simulation study, we demonstrate our method's ability to impute missing outcome data and improve estimation of regression coefficients compared to a complete case analysis. In our analysis of 55,273 COVID-19 cases in Denver, Colorado, increased annual exposure to fine particulate matter in the year prior to the pandemic was associated with increased risk of severe COVID-19 outcomes. We also found COVID-19 disease severity to be associated with interactions between exposures. Our individual-level analysis fills a gap in the literature and helps to elucidate the association between long-term exposure to air pollution and COVID-19 outcomes.

Assessment of SARS-CoV-2 Seroprevalence by Community Survey and Residual Specimens, Denver, Colorado, July-August 2020.

OBJECTIVES: The number of SARS-CoV-2 infections is underestimated in surveillance data. Various approaches to assess the seroprevalence of antibodies to SARS-CoV-2 have different resource requirements and generalizability. We estimated the seroprevalence of antibodies to SARS-CoV-2 in Denver County, Colorado, via a cluster-sampled community survey. METHODS: We estimated the overall seroprevalence of antibodies to SARS-CoV-2 via a community seroprevalence survey in Denver County in July 2020, described patterns associated with seroprevalence, and compared results with cumulative COVID-19 incidence as reported to the health department during the same period. In addition, we compared seroprevalence as assessed with a temporally and geographically concordant convenience sample of residual clinical specimens from a commercial laboratory. RESULTS: Based on 404 specimens collected through the community survey, 8.0% (95% CI, 3.9%-15.7%) of Denver County residents had antibodies to SARS-CoV-2, an infection rate of about 7 times that of the 1.1% cumulative reported COVID-19 incidence during this period. The estimated infection-to-reported case ratio was highest among children (34.7; 95% CI, 11.1-91.2) and males (10.8; 95% CI, 5.7-19.3). Seroprevalence was highest among males of Black race or Hispanic ethnicity and was associated with previous COVID-19-compatible illness, a previous positive SARS-CoV-2 test result, and close contact with someone who had confirmed SARS-CoV-2 infection. Testing of 1598 residual clinical specimens yielded a seroprevalence of 6.8% (95% CI, 5.0%-9.2%); the difference between the 2 estimates was 1.2 percentage points (95% CI, -3.6 to 12.2 percentage points). CONCLUSIONS: Testing residual clinical specimens provided a similar seroprevalence estimate yet yielded limited insight into the local epidemiology of COVID-19 and might be less representative of the source population than a cluster-sampled community survey. Awareness of the limitations of various sampling strategies is necessary when interpreting findings from seroprevalence assessments.

Disproportionate Incidence of COVID-19 Infection, Hospitalizations, and Deaths Among Persons Identifying as Hispanic or Latino - Denver, Colorado March-October 2020.

Persons identifying as Hispanic or Latino (Hispanic) represent the second largest racial/ethnic group in the United States (1), yet understanding of the impact of coronavirus disease 2019 (COVID-19) in this population is limited. To evaluate COVID-19 health disparities in the community and inform public health, health system, and community-based interventions, local public health authorities analyzed the sociodemographic characteristics of persons who were diagnosed, hospitalized, and who died with COVID-19 in Denver, Colorado. During the first 7 months of the COVID-19 epidemic in Denver (March 6-October 6, 2020) the majority of adult COVID-19 cases (54.8%), hospitalizations (62.1%), and deaths (51.2%) were among persons identifying as Hispanic, more than double the proportion of Hispanic adults in the Denver community (24.9%) (1). Systemic drivers that influence how Hispanic persons live and work increase their exposure risks: compared with non-Hispanic persons, Hispanic persons with COVID-19 in Denver reported larger household sizes and were more likely to report known exposures to household and close contacts with COVID-19, working in an essential industry, and working while ill. Reducing the disproportionate incidence of COVID-19 morbidity and mortality among Hispanic persons will require implementation of strategies that address upstream social and environmental factors that contribute to an increased risk for both infection and transmission and that facilitate improved access to culturally congruent care.