Long-Term Fine Particulate Matter Concentrations and Prevalence of Severe Acute Respiratory Syndrome Coronavirus 2: Differential Relationships by Socioeconomic Status Among Pregnant Individuals in New York City.

We aimed to determine whether long-term ambient concentrations of fine particulate matter (particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5)) were associated with increased risk of testing positive for coronavirus disease 2019 (COVID-19) among pregnant individuals who were universally screened at delivery and whether socioeconomic status (SES) modified this relationship. We used obstetrical data collected from New-York Presbyterian Hospital/Columbia University Irving Medical Center in New York, New York, between March and December 2020, including data on Medicaid use (a proxy for low SES) and COVID-19 test results. We linked estimated 2018-2019 PM2.5 concentrations (300-m resolution) with census-tract-level population density, household size, income, and mobility (as measured by mobile-device use) on the basis of residential address. Analyses included 3,318 individuals; 5% tested positive for COVID-19 at delivery, 8% tested positive during pregnancy, and 48% used Medicaid. Average long-term PM2.5 concentrations were 7.4 (standard deviation, 0.8) µg/m3. In adjusted multilevel logistic regression models, we saw no association between PM2.5 and ever testing positive for COVID-19; however, odds were elevated among those using Medicaid (per 1-µg/m3 increase, odds ratio = 1.6, 95% confidence interval: 1.0, 2.5). Further, while only 22% of those testing positive showed symptoms, 69% of symptomatic individuals used Medicaid. SES, including unmeasured occupational exposures or increased susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to concurrent social and environmental exposures, may explain the increased odds of testing positive for COVID-19 being confined to vulnerable pregnant individuals using Medicaid.

Hydroxychloroquine/chloroquine for the treatment of hospitalized patients with COVID-19: An individual participant data meta-analysis.

BACKGROUND: Results from observational studies and randomized clinical trials (RCTs) have led to the consensus that hydroxychloroquine (HCQ) and chloroquine (CQ) are not effective for COVID-19 prevention or treatment. Pooling individual participant data, including unanalyzed data from trials terminated early, enables more detailed investigation of the efficacy and safety of HCQ/CQ among subgroups of hospitalized patients. METHODS: We searched ClinicalTrials.gov in May and June 2020 for US-based RCTs evaluating HCQ/CQ in hospitalized COVID-19 patients in which the outcomes defined in this study were recorded or could be extrapolated. The primary outcome was a 7-point ordinal scale measured between day 28 and 35 post enrollment; comparisons used proportional odds ratios. Harmonized de-identified data were collected via a common template spreadsheet sent to each principal investigator. The data were analyzed by fitting a prespecified Bayesian ordinal regression model and standardizing the resulting predictions. RESULTS: Eight of 19 trials met eligibility criteria and agreed to participate. Patient-level data were available from 770 participants (412 HCQ/CQ vs 358 control). Baseline characteristics were similar between groups. We did not find evidence of a difference in COVID-19 ordinal scores between days 28 and 35 post-enrollment in the pooled patient population (odds ratio, 0.97; 95% credible interval, 0.76-1.24; higher favors HCQ/CQ), and found no convincing evidence of meaningful treatment effect heterogeneity among prespecified subgroups. Adverse event and serious adverse event rates were numerically higher with HCQ/CQ vs control (0.39 vs 0.29 and 0.13 vs 0.09 per patient, respectively). CONCLUSIONS: The findings of this individual participant data meta-analysis reinforce those of individual RCTs that HCQ/CQ is not efficacious for treatment of COVID-19 in hospitalized patients.