Researching COVID to enhance recovery (RECOVER) adult study protocol: Rationale, objectives and design (preprint)

Importance: SARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis. Methods: RECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged [≥]18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms. Discussion: RECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options.

Post-acute sequelae of COVID-19 in a non-hospitalized cohort: results from the Arizona CoVHORT (preprint)

Clinical presentation, outcomes, and duration of COVID-19 has ranged dramatically. While some individuals recover quickly, others suffer from persistent symptoms, collectively known as post - acute sequelae of SAR-CoV-2 (PASC). Most PASC research has focused on hospitalized COVID-19 patients with moderate to severe disease. We used data from a diverse population-based cohort of Arizonans to estimate prevalence of various symptoms of PASC, defined as experiencing at least one symptom 30 days or longer. There were 303 non-hospitalized individuals with a positive lab-confirmed COVID-19 test who were followed for a median of 61 days (range 30-250). COVID-19 positive participants were mostly female (70%), non-Hispanic white (68%), and on average 44 years old. Prevalence of PASC at 30 days post-infection was 68.7% (95%CI 63.4, 73.9). The most common symptoms were fatigue (37.5%), shortness-of-breath (37.5%), brain fog (30.8%), and stress (30.8%). The median number of symptoms was 3 (range 1-20). Amongst 157 participants with longer follow-up (≥60 days), PASC prevalence was 77.1%.

Symptoms of COVID-19 in a population-based cohort study (preprint)

Accurate diagnosis of potential SARS-CoV-2 infections by symptoms is one strategy for continuing global surveillance, particularly in low-resource communities. We conducted a prospective, population-based cohort study, the Arizona CoVHORT, among Arizona residents to elucidate the symptom profile of laboratory-confirmed COVID-19 participants(16.2%) compared to laboratory-confirmed negative(22.4%) and untested general population participants(61.4%). Among the 1514 study participants, those who were COVID-19 positive were more likely to be Hispanic(33.5%) and more likely to report obesity > 30 kg/m2(34.7%) compared to COVID-19 negative participants(19.2%; 31.0%) and untested CoVHORT participants(13.8%; 23.8%). Of the 245 laboratory-confirmed COVID-19 cases, 15.0% reported having had no symptoms. Of those that did report symptoms, the most commonly-reported first symptoms were sore throat(19.0%), headache(15.5%), cough(12.7%), runny nose/cold-like symptoms(12.1%), and fatigue(12.0%). In adjusted logistic regression models, COVID-19 positive participants were more likely than negative participants to experience loss of taste and smell(OR:35.7; 95% CI 18.4-69.5); bone or nerve pain(OR:17.9; 95% CI 6.7-47.4), vomiting(OR:10.8; 95% CI 3.1-37.5), nausea(OR:10.5; 95% CI 5.5-19.9), and headache(OR:8.4; 95% CI 5.6-12.8). When comparing confirmed COVID-19 cases with confirmed negative or untested participants, the pattern of symptoms that discriminates SARS-CoV-2 infection from those arising from other potential circulating pathogens may differ from general reports of symptoms among cases alone.

Quantifying meaningful adoption of a SARS-CoV-2 exposure notification app on the campus of the University of Arizona (preprint)

ObjectiveTo measure meaningful, local exposure notification usage without in-app analytics. MethodsWe surveyed app usage via case investigation interviews at the University of Arizona, with a focus on the period from September 9 to November 28, 2020, after automating the issuance of secure codes to verify positive test results. As independent validation, we compared the number of verification codes issued to the number of local cases. ResultsForty six percent (286/628) of infected persons interviewed by university case investigators reported having the app, and 55% (157/286) of these app users shared their positive SARS-CoV-2 test result in the app prior to the case investigation interview, comprising 25% (157/628) of those interviewed. This is corroborated by a 33% (565/1,713) ratio of code issuance (inflated by some unclaimed codes) to cases. Combining the 25% probability that those who test positive rapidly share their test result with a 46% probability that a person they infected can receive exposure notifications, an estimated 11.4% of transmission pairs exhibit meaningful app usage. High usage was achieved without the use of "push" notifications, in the context of a marketing campaign that leveraged social influencers. ConclusionsUsage can be assessed, without in-app analytics, within a defined local community such as a college campus rather than an entire jurisdiction. With marketing, high uptake in dense social networks like universities makes exposure notification an impactful complement to traditional contact tracing. Integrating verification code delivery into patient results portals was successful in making the exposure notification process rapid. 3 question summary box1) What is the current understanding of this subject?The extent to which exposure notification technology reduces SARS-CoV-2 transmission depends on usage among infected persons. 2) What does this report add to the literature?A novel metric estimates meaningful usage, and demonstrates potential transmission reduction on a college campus. Clear benefit was seen from simplifying verification of positive test results with automation. 3) What are the implications for public health practice?Defined communities can benefit from local deployment and marketing even in the absence of statewide deployment. Lifting current restrictions on deployment would allow more entities such as campuses to copy the model shown here to be successful.