Balte, Pallavi

ImportancePersistent symptoms and disability following SARS-CoV-2 infection, known as post–COVID-19 condition or “long COVID,” are frequently reported and pose a substantial personal and societal burden.ObjectiveTo determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.Design, Setting, and ParticipantsFor this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health–funded cohorts that have enrolled and followed participants since 1971. This report includes data collected through February 28, 2023, on adults aged 18 years or older with self-reported SARS-CoV-2 infection.ExposurePreinfection health conditions and lifestyle factors assessed before and during the pandemic via prepandemic examinations and pandemic-era questionnaires.Main Outcomes and MeasuresProbability of nonrecovery by 90 days and restricted mean recovery times were estimated using Kaplan-Meier curves, and Cox proportional hazards regression was performed to assess multivariable-adjusted associations with recovery by 90 days.ResultsOf 4708 participants with self-reported SARS-CoV-2 infection (mean [SD] age, 61.3 [13.8] years; 2952 women [62.7%]), an estimated 22.5% (95% CI, 21.2%-23.7%) did not recover by 90 days post infection. Median (IQR) time to recovery was 20 (8-75) days. By 90 days post infection, there were significant differences in restricted mean recovery time according to sociodemographic, clinical, and lifestyle characteristics, particularly by acute infection severity (outpatient vs critical hospitalization, 32.9 days [95% CI, 31.9-33.9 days] vs 57.6 days [95% CI, 51.9-63.3 days]; log-rank P < .001). Recovery by 90 days post infection was associated with vaccination prior to infection (hazard ratio [HR], 1.30; 95% CI, 1.11-1.51) and infection during the sixth (Omicron variant) vs first wave (HR, 1.25; 95% CI, 1.06-1.49). These associations were mediated by reduced severity of acute infection (33.4% and 17.6%, respectively). Recovery was unfavorably associated with female sex (HR, 0.85; 95% CI, 0.79-0.92) and prepandemic clinical cardiovascular disease (HR, 0.84; 95% CI, 0.71-0.99). No significant multivariable-adjusted associations were observed for age, educational attainment, smoking history, obesity, diabetes, chronic kidney disease, asthma, chronic obstructive pulmonary disease, or elevated depressive symptoms. Results were similar for reinfections.Conclusions and RelevanceIn this cohort study, more than 1 in 5 adults did not recover within 3 months of SARS-CoV-2 infection. Recovery within 3 months was less likely in women and those with preexisting cardiovascular disease and more likely in those with COVID-19 vaccination or infection during the Omicron variant wave.

Background: Adults with cardiovascular co-morbidities and risk factors are at greater risk of severe COVID-19. These same risk factors may also be associated with an attenuated antibody response to COVID-19 vaccines, although studies in diverse, U.S. population-based cohorts have been limited. Methods: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) conducted a serosurvey for SARS-CoV-2 antibodies via dried blood spot (DBS) in 14 U.S. cohorts. IgG antibodies to SARS-CoV-2 spike subunit 1 (S1) and nucleocapsid (N) were measured from DBS using a semi-quantitative microsphere immunoassay and reported as median fluorescence intensity (MFI). Multivariable adjusted linear models regressed log-transformed anti-S1 MFI on age, sex, race/ethnicity, education attainment, self-reported diabetes, hypertension, cardiovascular disease (CVD), chronic kidney disease, smoking history, body mass index (BMI), asthma, obstructive lung diseases, DBS batch, anti-N MFI, vaccine type, time between vaccine and DBS, and vaccine dose at time of DBS collection. Results are presented as the percent difference in anti-S1 MFI compared with a reference group. Results: There were 6614 vaccinated participants prior to booster regimens and DBS collection (April 2021-July 2022) with 50%, 48%, and 2% of the cohort who received BNT162b2, mRNA-1273, or other vaccines, respectively. The mean (SD) time between vaccination and DBS was 3.8 (1.8) months. Over 10% of the cohort had self-reported a history of diabetes, 55% had hypertension, and 74% had a BMI>25 kg/m 2 . Anti-S1 MFI decreased as the time between vaccine dose and DBS collection increased. Diabetes was associated with a 16.1% lower anti-S1 MFI (95%CI:-22.4,-9.5) whereas neither hypertension (-3.8%;95%CI:-9.3,2.1), nor cardiovascular disease history (-5.3%;95%CI:-16.3,7.4) were associated with anti-S1 MFI. Former and current smoking history were each associated with a lower anti-S1 MFI: (-6.6%;95%CI:-12.1,-0.8) and (-16.1%;95%CI:-24.7,-6.6), respectively. Participants with a BMI 25-29.9 kg/m 2 had a 7.6% higher anti-S1 MFI (95%CI:0.3,15.4) whereas those with a BMI of 30-35 kg/m 2 and >35 kg/m 2 had 6.2% (95%CI:-2.4,15.5) higher and 8.9% lower (95%CI:-17.6,0.7) MFI levels, respectively. Older age and male sex were each associated with a lower anti-S1 MFI and mRNA-1273 vaccine, Asian subgroup, higher anti-N titer, and prior COVID-19 infection were each associated with higher anti-S1 MFI. Chronic kidney disease, education attainment, and lung disease were not associated with anti-S1 MFI. Conclusions: Several traditional cardiovascular disease risk factors were associated with diminished humoral responses to the initial COVID-19 vaccine regimens in a diverse U.S. population-based cohort and may have implications on strategies to improve vaccine responses.

Rationale: The impact of the COVID-19 pandemic on tobacco use patterns remains incompletely understood. We aimed to examine changes in cigarette smoking patterns over the first 2 years of the COVID-19 pandemic (2020-22) in a large, multiethnic, US community-based sample. Methods: The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) ascertained the impact of the COVID-19 pandemic on participants from 14 longitudinal NIH-funded cohorts via 2 waves of standardized questionnaires conducted 2020-22. The C4R questionnaire collected data on cigarette use patterns for the current and immediate pre-pandemic periods (January-March 2020). These data were used to define pandemic-era smoking initiation, smoking cessation, and changes in smoking intensity. Multivariable logistic regression models were adjusted for centrally harmonized pre-pandemic data on sociodemographic characteristics, remote smoking history, and co-morbidities and pandemic-era psychological health, insomnia, and SARS-CoV-2 infection history ascertained through C4R questionnaires. Multiple imputation by chained equations was used to account for missing covariate data. Results: Of 17179 participants completing C4R questions on pandemic-era smoking behaviors, 1899 (11%) participants reported current smoking in the immediate pre-pandemic period (mean age 70 years, 59% women, 31% African American, 2% Hispanic, 1% Asian, 22% American Indian/Alaskan Native [AIAN]). Of these 181 (10%) self-reported quitting during the pandemic. Among 1718 (90%) who continued smoking, smoking intensity increased in 17% and decreased in 26%. Among 15093 participants who were not smoking prior to March 2020, 135 (0.9%) initiated smoking during the pandemic period, including 120 (89%) with a remote history of smoking and 15 (11%) with no history of smoking. Pandemic-era smoking cessation was associated with older age(80+ years vs <65 years [adjusted odds ratio; 95%CI] 2.1; 1.1-4.0), obesity(vs normal weight 1.6; 1.02-2.6) and history of SARS-CoV-2 infection (2.1; 1.3-3.1). Pandemic-era smoking initiation was associated with concurrent use of cannabis (3.1; 1.9-5.2), e-cigarette (29.6; 14.8-59.2), and/or alcohol (1.8; 1.1-2.9). Compared to non-Hispanic white participants, AIAN participants had lower odds of quitting (0.1; 0.03-0.6) and African American participants had higher odds of increased smoking intensity (2.0; 1.3-3.1). Depressive symptoms were associated with smoking initiation (2.4; 1.3-4.3) and increased smoking intensity (2.6; 1.5-4.5). Conclusion: Greater odds of smoking initiation and/or increased smoking intensity were observed in minoritized groups and participants reporting depressive symptoms. Majority of those who initiated smoking during pandemic-era were relapsers. Smoking cessation programs remain important to improving public health and reducing health disparities.