Real-time tracking of self-reported symptoms to predict potential COVID-19

Abstract

A total of 2,618,862 participants reported their potential symptoms of COVID-19 on a smartphone-based app. Among the 18,401 who had undergone a SARS-CoV-2 test, the proportion of participants who reported loss of smell and taste was higher in those with a positive test result (4,668 of 7,178 individuals; 65.03%) than in those with a negative test result (2,436 of 11,223 participants; 21.71%) (odds ratio = 6.74; 95% confidence interval = 6.31-7.21). A model combining symptoms to predict probable infection was applied to the data from all app users who reported symptoms (805,753) and predicted that 140,312 (17.42%) participants are likely to have COVID-19.

Keywords

Coronavirus disease 2019 (COVID-19)2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Tracking (education)MedicineBetacoronavirusPandemicVirologyInternal medicinePsychologyOutbreakDiseaseInfectious disease (medical specialty)

MeSH Terms

AdultAgedBetacoronavirusCOVID-19Computer SystemsCoronavirus InfectionsCoughDisease NotificationDyspneaFatigueFemaleHumansMaleMiddle AgedMobile ApplicationsModelsBiologicalOlfaction DisordersPandemicsPneumoniaViralProdromal SymptomsPrognosisSARS-CoV-2Self ReportSeverity of Illness IndexSmartphoneTaste DisordersUnited KingdomUnited States

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Publication Info

Year: 2020
Type: article
Volume: 26
Issue: 7
Pages: 1037-1040
Citations: 1492
Access: Closed

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APA Style

                            
                                
                                    Cristina Menni, 
                                
                                    Ana M. Valdes, 
                                
                                    Maxim B. Freidin
                                
                                et al.
                            
                            (2020). 
                            Real-time tracking of self-reported symptoms to predict potential COVID-19. 
                            Nature Medicine
                            , 26
                            (7)
                            , 1037-1040.
                            https://doi.org/10.1038/s41591-020-0916-2
                        

Identifiers

DOI: 10.1038/s41591-020-0916-2
PMID: 32393804
PMCID: PMC7751267

Data Quality

Data completeness: 90%