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Background: While factors associated with long COVID (LC) continue to be illuminated, little is known about recovery. This study used national survey data to assess factors associated with recovery from LC., Methods: We used data from the 2022 National Health Interview Survey, a cross-sectional sample of noninstitutionalized US adults. Survey analysis was used to account for oversampling and nonresponse bias and to obtain nationally representative estimates. A multivariable logistic regression model was used to identify potential predictors of LC recovery., Results: Among those reporting ever having COVID-19, 17.7% or an estimated 17.5 million American adults reported ever having LC, and among those with LC, 48.5% or an estimated 8.5 million reported having recovered. Multivariable logistic regression analysis showed that Hispanic adults were significantly more likely than White adults to report recovery from LC. At the same time, those with severe COVID-19 symptoms and those who had more than a high school degree, were aged 40 years or older, or were female were less likely to report recovery., Conclusion: Significant variations in LC recovery were noted across age, sex, race and ethnicity, education, and severity of COVID-19 symptoms. Further work is needed to elucidate the causes of these differences and identify strategies to increase recovery rates., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Long COVID is a multisystemic condition that affects the lives of millions of people globally, yet factors associated with it are poorly defined. Our purpose in this study was to identify factors associated with long COVID., Methods: This cross-sectional study used data from the 2022 Behavioral Risk Factor Surveillance System (BRFSS) and the 2022 National Health Interview Survey (NHIS). We restricted the sample to individuals aged 18 and older who reported a positive COVID-19 test or doctor's diagnosis. Individuals who reported symptoms of at least 3 months were assumed to have long COVID. We identified demographic and clinical characteristics associated with long COVID, in unadjusted and adjusted analyses., Results: The study included 124,313 individuals in the BRFSS cohort and 10,131 in the NHIS cohort who reported a COVID-19 infection, with 26,783 (21.5%) and 1797 (17.7%) reporting long COVID, respectively. We found middle age, female sex, lack of a college degree, and severity of acute COVID-19 infection to be associated with long COVID. In contrast, non-Hispanic Asian and Black Americans were less likely to report long COVID compared with non-Hispanic White individuals. These findings were consistent across datasets., Conclusions: Several demographic features were associated with long COVID, which may be the result of social, clinical, or biological influences., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

We analyzed feasibility of pooling saliva samples for severe acute respiratory syndrome coronavirus 2 testing and found that sensitivity decreased according to pool size: 5 samples/pool, 7.4% reduction; 10 samples/pool, 11.1%; and 20 samples/pool, 14.8%. When virus prevalence is >2.6%, pools of 5 require fewer tests; when <0.6%, pools of 20 support screening strategies.

Introduction: Healthcare workers (HCW) treating COVID-19 patients are at high risk for infection and may also spread infection through their contact with vulnerable patients. Smell loss has been associated with SARS-CoV-2 infection, but it is unknown whether monitoring for smell loss can be used to identify asymptomatic infection among high risk individuals. In this study we sought to determine if tracking smell sensitivity and loss using an at-home assessment could identify SARS-CoV-2 infection in HCW., Methods and Findings: We performed a prospective cohort study tracking 473 HCW across three months to determine if smell loss could predict SARS-CoV-2 infection in this high-risk group. HCW subjects completed a longitudinal, behavioral at-home assessment of olfaction with household items, as well as detailed symptom surveys that included a parosmia screening questionnaire, and real-time quantitative polymerase chain reaction testing to identify SARS-CoV-2 infection. Our main measures were the prevalence of smell loss in SARS-CoV-2-positive HCW versus SARS-CoV-2-negative HCW, and timing of smell loss relative to SARS-CoV-2 test positivity. SARS-CoV-2 was identified in 17 (3.6%) of 473 HCW. HCW with SARS-CoV-2 infection were more likely to report smell loss than SARS-CoV-2-negative HCW on both the at-home assessment and the screening questionnaire (9/17, 53% vs 105/456, 23%, P < .01). 6/9 (67%) of SARS-CoV-2-positive HCW reporting smell loss reported smell loss prior to having a positive SARS-CoV-2 test, and smell loss was reported a median of two days before testing positive. Neurological symptoms were reported more frequently among SARS-CoV-2-positive HCW who reported smell loss compared to those without smell loss (9/9, 100% vs 3/8, 38%, P < .01)., Conclusions: In this prospective study of HCW, self-reported changes in smell using two different measures were predictive of SARS-CoV-2 infection. Smell loss frequently preceded a positive test and was associated with neurological symptoms., Competing Interests: The authors have declared that no competing interests exist.

The current quantitative reverse transcription PCR (RT-qPCR) assay recommended for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing in the United States requires analysis of 3 genomic targets per sample: 2 viral and 1 host. To simplify testing and reduce the volume of required reagents, we devised a multiplex RT-qPCR assay to detect SARS-CoV-2 in a single reaction. We used existing N1, N2, and RP primer and probe sets by the Centers for Disease Control and Prevention, but substituted fluorophores to allow multiplexing of the assay. The cycle threshold (Ct) values of our multiplex RT-qPCR were comparable to those obtained by the single assay adapted for research purposes. Low copy numbers (≥500 copies/reaction) of SARS-CoV-2 RNA were consistently detected by the multiplex RT-qPCR. Our novel multiplex RT-qPCR improves upon current single diagnostics by saving reagents, costs, time, and labor., Competing Interests: The authors have declared that no competing interests exist.

The novel coronavirus SARS-CoV-2 was first detected in the Pacific Northwest region of the United States in January 2020, with subsequent COVID-19 outbreaks detected in all 50 states by early March. To uncover the sources of SARS-CoV-2 introductions and patterns of spread within the United States, we sequenced nine viral genomes from early reported COVID-19 patients in Connecticut. Our phylogenetic analysis places the majority of these genomes with viruses sequenced from Washington state. By coupling our genomic data with domestic and international travel patterns, we show that early SARS-CoV-2 transmission in Connecticut was likely driven by domestic introductions. Moreover, the risk of domestic importation to Connecticut exceeded that of international importation by mid-March regardless of our estimated effects of federal travel restrictions. This study provides evidence of widespread sustained transmission of SARS-CoV-2 within the United States and highlights the critical need for local surveillance., Competing Interests: Declaration of Interests A.L.W. is the principal investigator on a research grant from Pfizer to Yale University and has received consulting fees for participation in advisory boards for Pfizer., (Copyright © 2020 Elsevier Inc. All rights reserved.)