As the COVID-19 pandemic progresses, obtaining information on symptoms dynamics is of essence. Here, we extracted data from primary-care electronic health records and nationwide distributed surveys to assess the longitudinal dynamics of symptoms prior to and throughout SARS-CoV-2 infection. Information was available for 206,377 individuals, including 2471 positive cases. The two datasources were discordant, with survey data capturing most of the symptoms more sensitively. The most prevalent symptoms included fever, cough and fatigue. Loss of taste and smell 3 weeks prior to testing, either self-reported or recorded by physicians, were the most discriminative symptoms for COVID-19. Additional discriminative symptoms included self-reported headache and fatigue and a documentation of syncope, rhinorrhea and fever. Children had a significantly shorter disease duration. Several symptoms were reported weeks after recovery. By a unique integration of two datasources, our study shed light on the longitudinal course of symptoms experienced by cases in primary care.

No abstract

Background Multiple voluntary surveillance platforms were developed across the world in response to the COVID-19 pandemic, providing a real-time understanding of population-based COVID-19 epidemiology. During this time, testing criteria broadened and health-care policies matured. We aimed to test whether there were consistent associations of symptoms with SARS-CoV-2 test status across three surveillance platforms in three countries (two platforms per country), during periods of testing and policy changes.Methods For this observational study, we used data of observations from three volunteer COVID-19 digital surveillance platforms (Carnegie Mellon University and University of Maryland Facebook COVID-19 Symptom Survey, ZOE COVID Symptom Study app, and the Corona Israel study) targeting communities in three countries (Israel, the UK, and the USA; two platforms per country). The study population included adult respondents (age 18-100 years at baseline) who were not health-care workers. We did logistic regression of self-reported symptoms on self-reported SARS-CoV-2 test status (positive or negative), adjusted for age and sex, in each of the study cohorts. We compared odds ratios (ORs) across platforms and countries, and we did meta-analyses assuming a random effects model. We also evaluated testing policy changes, COVID-19 incidence, and time scales of duration of symptoms and symptomto-test time. FindingsBetween April 1 and July 31, 2020, 514 459 tests from over 10 million respondents were recorded in the six surveillance platform datasets. Anosmia-ageusia was the strongest, most consistent symptom associated with a positive COVID-19 test (robust aggregated rank one, meta-analysed random effects OR 16•96, 95% CI 13•13-21•92). Fever (rank two, 6•45, 4•25-9•81), shortness of breath (rank three, 4•69, 3•14-7•01), and cough (rank four, 4•29, 3•13-5•88) were also highly associated with test positivity. The association of symptoms with test status varied by duration of illness, timing of the test, and broader test criteria, as well as over time, by country, and by platform.Interpretation The strong association of anosmia-ageusia with self-reported positive SARS-CoV-2 test was consistently observed, supporting its validity as a reliable COVID-19 signal, regardless of the participatory surveillance platform, country, phase of illness, or testing policy. These findings show that associations between COVID-19 symptoms and test positivity ranked similarly in a wide range of scenarios. Anosmia, fever, and respiratory symptoms consistently had the strongest effect estimates and were the most appropriate empirical signals for symptom-based public health surveillance in areas with insufficient testing or benchmarking capacity. Collaborative syndromic surveillance could enhance real-time epidemiological investigations and public health utility globally.

Coronavirus infection spreads in clusters and therefore early identification of these clusters is critical for slowing down the spread of the virus. Here, we propose that daily population-wide surveys that assess the development of symptoms caused by the virus could serve as a strategic and valuable tool for identifying such clusters to inform epidemiologists, public health officials, and policy makers. We show preliminary results from a survey of over 58,000 Israelis and call for an international consortium to extend this concept in order to develop predictive models. We expect such data to allow: Faster detection of spreading zones and patients; Obtaining a current snapshot of the number of people in each area who have developed symptoms; Predicting future spreading zones several days before an outbreak occurs; Evaluating the effectiveness of the various social distancing measures taken, and their contribution to reduce the number of symptomatic people. Such information can provide a valuable tool for decision makers to decide which areas need strengthening of social distancing measures and which areas can be relieved. Preliminary analysis shows that in neighborhoods with confirmed COVID-19 patient history, more responders report on COVID-19 associated symptoms, demonstrating the potential utility of our approach for detection of outbreaks. Researchers from other countries including the U.S, India, Italy, Spain, Germany, Mexico, Finland, Sweden, Norway and several others have adopted our approach and we are collaborating to further improve it. We call with urgency for other countries to join this international consortium, and to share methods and data collected from these daily, simple, one-minute surveys.

Importance: Data regarding the clinical characteristics of COVID-19 infection is rapidly accumulating. However, most studies thus far are based on hospitalized patients and lack longitudinal follow up. As the majority of COVID-19 cases are not hospitalized, prospective studies of symptoms in the population presenting to primary care are needed. Objective: To assess the longitudinal dynamic of clinical symptoms in non-hospitalized individuals prior to and throughout the diagnosis of SARS-CoV-2 infection. Design, Setting, and Participants: From 1/3/2020 to 07/06/2020, information on symptoms from either surveys or primary care visits was available for 206,377 individuals, including 2,471 who tested positive for COVID-19. Data were extracted from electronic health records (EHR) of the second largest Health Maintenance Organization in Israel, consisting of both results of PCR tests and symptoms recorded by primary care physicians, and linked longitudinal self reported symptoms. Exposures: Diagnosis of COVID-19 disease was made by PCR testing for SARS-CoV-2 from nasopharyngeal swabs. Main Outcomes and Measures: Longitudinal prevalence of clinical symptoms Results: In adults, the most prevalent symptoms recorded in EHR were cough (11.6%), fever (10.3%), and myalgia (7.7%) and the most prevalent self-reported symptoms were cough (21%), fatigue (19%) and rhinorrhea and/or nasal congestion (17%). In children, the most prevalent symptoms recorded in the EHR were fever (7%), cough (5.5%) and abdominal pain (2.4%). Emotional disturbances were documented in 15.9% of the positive adults and 4.2% of the children. Loss of taste and smell, either self-reported or documented by a physician, 3 weeks prior to testing, were the most discriminative symptoms in adults (OR =11.18 and OR=5.47 respectively). Additional symptoms included self reported confusion (OR =4.02), and fatigue (OR = 1.73) and a documentation of syncope, rhinorrhea (OR = 2.09 for both ) and fever (OR= 1.62 ) by a physician. Mean time to recovery was 23.5 +- 9.9 days. Children had a significantly shorter disease duration (21.7 +- 8.8 days, p-value=0.01). Several symptoms, including fatigue, myalgia, runny nose and shortness of breath were reported weeks after recovery. Conclusions and Relevance: As the COVID-19 pandemic progresses rapidly worldwide, obtaining accurate information on symptoms and their progression is of essence. Our study shed light on the full clinical spectrum of symptoms experienced by infected individuals in primary care, and may alert physicians for the possibility of COVID-19 infection.