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Background The COVID-19 pandemic has catalyzed a global public response and innovation in clinical study methods. Objective The COVID-19 Citizen Science study was designed to generate knowledge about participant-reported COVID-19 symptoms, behaviors, and disease occurrence. Methods COVID-19 Citizen Science is a longitudinal cohort study launched on March 26, 2020, on the Eureka Research Platform. This study illustrates important advances in digital clinical studies, including entirely digital study participation, targeted recruitment strategies, electronic consent, recurrent and time-updated assessments, integration with smartphone-based measurements, analytics for recruitment and engagement, connection with partner studies, novel engagement strategies such as participant-proposed questions, and feedback in the form of real-time results to participants. Results As of February 2021, the study has enrolled over 50,000 participants. Study enrollment and participation are ongoing. Over the lifetime of the study, an average of 59% of participants have completed at least one survey in the past 4 weeks. Conclusions Insights about COVID-19 symptoms, behaviors, and disease occurrence can be drawn through digital clinical studies. Continued innovation in digital clinical study methods represents the future of clinical research. International Registered Report Identifier (IRRID) DERR1-10.2196/28169

Despite some inconsistent reporting of symptoms, studies have demonstrated that at least 20% of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will remain asymptomatic. Although most global efforts have focused on understanding factors underlying severe illness in COVID-19 (coronavirus disease of 2019), the examination of asymptomatic infection provides a unique opportunity to consider early disease and immunologic features promoting rapid viral clearance. Owing to its critical role in the immune response, we postulated that variation in the human leukocyte antigen (HLA) loci may underly processes mediating asymptomatic infection. We enrolled 29,947 individuals registered in the National Marrow Donor Program for whom high-resolution HLA genotyping data were available in the UCSF Citizen Science smartphone-based study designed to track COVID-19 symptoms and outcomes. Our discovery cohort (n=1428) was comprised of unvaccinated, self-identified subjects who reported a positive test result for SARS-CoV-2. We tested for association of five HLA loci (HLA-A, -B, -C, -DRB1, -DQB1) with disease course and identified a strong association of HLA-B*15:01 with asymptomatic infection, and reproduced this association in two independent cohorts. Suggesting that this genetic association is due to pre-existing T-cell immunity, we show that T cells from pre-pandemic individuals carrying HLA-B*15:01 were reactive to the immunodominant SARS-CoV-2 S-derived peptide NQKLIANQF, and 100% of the reactive cells displayed memory phenotype. Finally, we characterize the protein structure of HLA-B*15:01-peptide complexes, demonstrating that the NQKLIANQF peptide from SARS-CoV-2, and the highly homologous NQKLIANAF from seasonal coronaviruses OC43-CoV and HKU1-CoV, share similar ability to be stabilized and presented by HLA-B*15:01, providing the molecular basis for T-cell cross-reactivity and HLA-B*15:01-mediated pre-existing immunity.

BACKGROUND Adults with cardiovascular disease risk factors (CVRFs) are also at increased risk of developing cognitive decline and dementia. However, it is often difficult to study the relationships between CVRFs and cognitive function because cognitive assessment typically requires time-consuming in-person neuropsychological evaluations that may not be feasible for real-world situations. OBJECTIVE We conducted a proof-of-concept study to determine if the association between CVRFs and cognitive function could be detected using web-based, self-administered cognitive tasks and CVRF assessment. METHODS We recruited 239 participants aged ≥50 years (mean age 62.7 years, SD 8.8; 42.7% [n=102] female, 88.7% [n=212] White) who were enrolled in the Health eHeart Study, a web-based platform focused on cardiac disease. The participants self-reported CVRFs (hypertension, high cholesterol, diabetes, and atrial fibrillation) using web-based health surveys between August 2016 and July 2018. After an average of 3 years of follow-up, we remotely evaluated episodic memory, working memory, and executive function via the web-based Posit Science platform, BrainHQ. Raw data were normalized and averaged into 3 domain scores. We used linear regression models to examine the association between CVRFs and cognitive function. RESULTS CVRF prevalence was 62.8% (n=150) for high cholesterol, 45.2% (n=108) for hypertension, 10.9% (n=26) for atrial fibrillation, and 7.5% (n=18) for diabetes. In multivariable models, atrial fibrillation was associated with worse working memory (β=-.51, 95% CI -0.91 to -0.11) and worse episodic memory (β=-.31, 95% CI -0.59 to -0.04); hypertension was associated with worse episodic memory (β=-.27, 95% CI -0.44 to -0.11). Diabetes and high cholesterol were not associated with cognitive performance. CONCLUSIONS Self-administered web-based tools can be used to detect both CVRFs and cognitive health. We observed that atrial fibrillation and hypertension were associated with worse cognitive function even in those in their 60s and 70s. The potential of mobile assessments to detect risk factors for cognitive aging merits further investigation.

BackgroundIn the absence of universal testing, effective therapies, or vaccines, identifying risk factors for viral infection, particularly readily modifiable exposures and behaviors, is required to identify effective strategies against viral infection and transmission.MethodsWe conducted a world-wide mobile application-based prospective cohort study available to English speaking adults with a smartphone. We collected self-reported characteristics, exposures, and behaviors, as well as smartphone-based geolocation data. Our main outcome was incident symptoms of viral infection, defined as fevers and chills plus one other symptom previously shown to occur with SARS-CoV-2 infection, determined by daily surveys.FindingsAmong 14, 335 participants residing in all 50 US states and 93 different countries followed for a median 21 days (IQR 10-26 days), 424 (3%) developed incident viral symptoms. In pooled multivariable logistic regression models, female biological sex (odds ration [OR] 1.75, 95% CI 1.39-2.20, pInterpretationWhile several immutable characteristics were associated with the risk of developing viral symptoms, multiple immediately modifiable exposures and habits that influence risk were also observed, potentially identifying readily accessible strategies to mitigate risk in the Covid-19 era.FundingThis study was funded by IU2CEB021881-01 and 3U2CEB021881-05S1 from the NIH/ NIBIB to Drs. Marcus, Olgin, and Pletcher.Research in contextEvidence before this studyPredictors of incident viral infection have been determined largely from cross-sectional studies prone to recall bias among individuals representing geographically constrained regions, and most were conducted before the era of the current Covid-19 pandemic.Added value of this studyWe conducted a world-wide, mobile application-based, longitudinal cohort study utilizing time-updated predictors and outcomes, providing novel and current information regarding risk-factors for incident viral symptoms based on real-time information in the era of Covid-19.Implications of all the available evidenceThese data suggest that certain immutable characteristics influence the risk for incident viral symptoms, while smoking cessation, physical distancing to avoid contact with individuals outside the household, regular exercise, and sanitizing one’s phone may each help mitigate the risk of viral infection.

IMPORTANCE: Atrial fibrillation (AF) is the most common arrhythmia. Although patients have reported that various exposures determine when and if an AF event will occur, a prospective evaluation of patient-selected triggers has not been conducted, and the utility of characterizing presumed AF-related triggers for individual patients remains unknown. OBJECTIVE: To test the hypothesis that n-of-1 trials of self-selected AF triggers would enhance AF-related quality of life. DESIGN, SETTING, AND PARTICIPANTS: A randomized clinical trial lasting a minimum of 10 weeks tested a smartphone mobile application used by symptomatic patients with paroxysmal AF who owned a smartphone and were interested in testing a presumed AF trigger. Participants were screened between December 22, 2018, and March 29, 2020. INTERVENTIONS: n-of-1 Participants received instructions to expose or avoid self-selected triggers in random 1-week blocks for 6 weeks, and the probability their trigger influenced AF risk was then communicated. Controls monitored their AF over the same time period. MAIN OUTCOMES AND MEASURES: AF was assessed daily by self-report and using a smartphone-based electrocardiogram recording device. The primary outcome comparing n-of-1 and control groups was the Atrial Fibrillation Effect on Quality-of-Life (AFEQT) score at 10 weeks. All participants could subsequently opt for additional trigger testing. RESULTS: Of 446 participants who initiated (mean [SD] age, 58 [14] years; 289 men [58%]; 461 White [92%]), 320 (72%) completed all study activities. Self-selected triggers included caffeine (n = 53), alcohol (n = 43), reduced sleep (n = 31), exercise (n = 30), lying on left side (n = 17), dehydration (n = 10), large meals (n = 7), cold food or drink (n = 5), specific diets (n = 6), and other customized triggers (n = 4). No significant differences in AFEQT scores were observed between the n-of-1 vs AF monitoring-only groups. In the 4-week postintervention follow-up period, significantly fewer daily AF episodes were reported after trigger testing compared with controls over the same time period (adjusted relative risk, 0.60; 95% CI, 0.43- 0.83; P

BackgroundCardiac arrhythmias have been observed among patients hospitalised with acute COVID-19 infection, and palpitations remain a common symptom among the much larger outpatient population of COVID-19 survivors in the convalescent stage of the disease.ObjectiveTo determine arrhythmia prevalence among outpatients after a COVID-19 diagnosis.MethodsAdults with a positive COVID-19 test and without a history of arrhythmia were prospectively evaluated with 14-day ambulatory electrocardiographic monitoring. Participants were instructed to trigger the monitor for palpitations.ResultsA total of 51 individuals (mean age 42±11 years, 65% women) underwent monitoring at a median 75 (IQR 34–126) days after a positive COVID-19 test. Median monitoring duration was 13.2 (IQR 10.5–13.8) days. No participant demonstrated atrial fibrillation, atrial flutter, sustained supraventricular tachycardia (SVT), sustained ventricular tachycardia or infranodal atrioventricular block. Nearly all participants (96%) had an ectopic burden of ConclusionsWe did not find evidence of malignant or sustained arrhythmias in outpatients after a positive COVID-19 diagnosis. While palpitations were common, symptoms frequently corresponded to sinus rhythm/sinus tachycardia or non-malignant arrhythmias such as isolated ectopy or non-sustained SVT. While these findings cannot exclude the possibility of serious arrhythmias in select individuals, they do not support a strong or widespread proarrhythmic effect of COVID-19 infection after resolution of acute illness.

ObjectiveUntil effective treatments and vaccines are made readily and widely available, preventative behavioural health measures will be central to the SARS-CoV-2 public health response. While current recommendations are grounded in general infectious disease prevention practices, it is still not entirely understood which particular behaviours or exposures meaningfully affect one’s own risk of incident SARS-CoV-2 infection. Our objective is to identify individual-level factors associated with one’s personal risk of contracting SARS-CoV-2.DesignProspective cohort study of adult participants from 26 March 2020 to 8 October 2020.SettingThe COVID-19 Citizen Science Study, an international, community and mobile-based study collecting daily, weekly and monthly surveys in a prospective and time-updated manner.ParticipantsAll adult participants over the age of 18 years were eligible for enrolment.Primary outcome measureThe primary outcome was incident SARS-CoV-2 infection confirmed via PCR or antigen testing.Results28 575 unique participants contributed 2 479 149 participant-days of data across 99 different countries. Of these participants without a history of SARS-CoV-2 infection at the time of enrolment, 112 developed an incident infection. Pooled logistic regression models showed that increased age was associated with lower risk (OR 0.98 per year, 95% CI 0.97 to 1.00, p=0.019), whereas increased number of non-household contacts (OR 1.10 per 10 contacts, 95% CI 1.01 to 1.20, p=0.024), attending events of at least 10 people (OR 1.26 per 10 events, 95% CI 1.07 to 1.50, p=0.007) and restaurant visits (OR 1.95 per 10 visits, 95% CI 1.42 to 2.68, pConclusionsOur study identified three modifiable health behaviours, namely the number of non-household contacts, attending large gatherings and restaurant visits, which may meaningfully influence individual-level risk of contracting SARS-CoV-2.