Despite the widespread implementation of public health measures, COVID-19 continues to spread in the United States. To facilitate an agile response to the pandemic, we developed How We Feel, a web and mobile application that collects longitudinal self-reported survey responses on health, behavior, and demographics. Here we report results from over 500,000 users in the United States from April 2, 2020 to May 12, 2020. We show that self-reported surveys can be used to build predictive models to identify likely COVID-19 positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation, show a variety of exposure, occupation, and demographic risk factors for COVID-19 beyond symptoms, reveal factors for which users have been SARS-CoV-2 PCR tested, and highlight the temporal dynamics of symptoms and self-isolation behavior. These results highlight the utility of collecting a diverse set of symptomatic, demographic, exposure, and behavioral self-reported data to fight the COVID-19 pandemic.

COVID-19 can cause significant mortality in the elderly in Long Term Care Facilities (LTCF). We describe four LTCF outbreaks where mass testing identified a high proportion of asymptomatic infections (4-41% in health care workers and 20-75% in residents), indicating that symptom-based screening alone is insufficient for monitoring for COVID-19 transmission.

Despite social distancing and shelter-in-place policies, COVID-19 continues to spread in the United States. A lack of timely information about factors influencing COVID-19 spread and testing has hampered agile responses to the pandemic. We developed How We Feel, an extensible web and mobile application that aggregates self-reported survey responses, to fill gaps in the collection of COVID-19-related data. How We Feel collects longitudinal and geographically localized information on users' health, behavior, and demographics. Here we report results from over 500,000 users in the United States from April 2, 2020 to May 12, 2020. We show that self- reported surveys can be used to build predictive models of COVID-19 test results, which may aid in identification of likely COVID-19 positive individuals. We find evidence among our users for asymptomatic or presymptomatic presentation, as well as for household and community exposure, occupation, and demographics being strong risk factors for COVID-19. We further reveal factors for which users have been SARS-CoV-2 PCR tested, as well as the temporal dynamics of self- reported symptoms and self-isolation behavior in positive and negative users. These results highlight the utility of collecting a diverse set of symptomatic, demographic, and behavioral self- reported data to fight the COVID-19 pandemic.

Objective: To describe epidemiologic and genomic characteristics of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak in a large skilled nursing facility (SNF), and the strategies that controlled transmission. Design, Setting, and Participants: Cohort study during March 22–May 4, 2020 of all staff and residents at a 780-bed SNF in San Francisco, California. Methods: Contact tracing and symptom screening guided targeted testing of staff and residents; respiratory specimens were also collected through serial point prevalence surveys (PPS) in units with confirmed cases. Cases were confirmed by real-time reverse transcription–polymerase chain reaction testing for SARS-CoV-2; whole genome sequencing (WGS) characterized viral isolate lineages and relatedness. Infection prevention and control (IPC) interventions included restricting from work any staff who had close contact to a confirmed case; restricting movements between units; implementing surgical face masking facility-wide; and recommended PPE (isolation gown, gloves, N95 respirator and eye protection) for clinical interactions in units with confirmed cases. Results: Of 725 staff and residents tested through targeted testing and serial PPS, twenty-one (3%) were SARS-CoV-2-positive; sixteen (76%) staff and 5 (24%) residents. Fifteen (71%) were linked to a single unit. Targeted testing identified 17 (81%) cases; PPS identified 4 (19%). Most (71%) cases were identified prior to IPC intervention. WGS was performed on SARS-CoV-2 isolates from four staff and four residents; five were of Santa Clara County lineage and the three others were distinct lineages. Conclusions: Early implementation of targeted testing, serial PPS, and multimodal IPC interventions limited SARS-CoV-2 transmission within the SNF.

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