Who should we test for COVID-19? A triage model built from national symptom surveys

Abstract

The gold standard for COVID-19 diagnosis is detection of viral RNA in a reverse transcription PCR test. Due to global limitations in testing capacity, effective prioritization of individuals for testing is essential. Here, we devised a model that estimates the probability of an individual to test positive for COVID-19 based on answers to 9 simple questions regarding age, gender, presence of prior medical conditions, general feeling, and the symptoms fever, cough, shortness of breath, sore throat and loss of taste or smell, all of which have been associated with COVID-19 infection. Our model was devised from a subsample of a national symptom survey that was answered over 2 million times in Israel over the past 2 months and a targeted survey distributed to all residents of several cities in Israel. Overall, 43,752 adults were included, from which 498 self-reported as being COVID-19 positive. We successfully validated the model on held-out individuals from Israel where it achieved a positive predictive value (PPV) of 46.3% at a 10% sensitivity and demonstrated its applicability outside of Israel by further validating it on an independently collected symptom survey dataset from the U.K., U.S. and Sweden, where it achieved a PPV of 34.7% at 10% sensitivity. Moreover, evaluating the model's performance on this latter independent dataset on entries collected one week prior to the PCR test and up to the day of the test we found the highest performance on the day of the test. As our tool can be used online and without the need of exposure to suspected patients, it may have worldwide utility in combating COVID-19 by better directing the limited testing resources through prioritization of individuals for testing, thereby increasing the rate at which positive individuals can be identified and isolated.

Longitudinal symptom dynamics of COVID-19 infection

“…In children, the result was not statistically significant, possibly due to a small sample size. Although anosmia and ageusia were initially less described as COVID-19 symptoms 3,6 , and were not part of the Israeli testing policy throughout the study period, they further emerged as the most predictive symptoms for COVID-19 in this study and others 10,12,22 , and were also found to be the most prolong symptoms in infected individuals 23 . Health organizations worldwide have gradually added it to the list of COVID-19 related symptoms including the USA CDC 24 , the UK 25 and Israel 26 .…”

“…Less common symptoms included sputum production, headache, haemoptysis, and diarrhea [3][4][5][6][7][8] . Further on, anosmia and ageusia also emerged as prevalent and relatively discriminative symptoms of COVID-19 infection [9][10][11][12] . As clinical data started to accumulate, reviews describing the potential cardiovascular 13 , gastrointestinal 14 , neurological 15 , and cutaneous manifestations 16 of the disease were published.…”

Longitudinal symptom dynamics of COVID-19 infection in primary care

“…In children, the result was not statistically significant, possibly due to a small sample size. Although anosmia and ageusia were initially less described as COVID-19 symptoms 3,6 , and were not part of the Israeli testing policy throughout the study period, they further emerged as the most predictive symptoms for COVID-19, in this study and others 9,11 , and health organisations worldwide have gradually added it to the list of COVID-19 related symptoms including the USA CDC 23 , the UK 24 and Israel 25 .…”

“…Less common symptoms included sputum production, headache , haemoptysis and diarrhea [3][4][5][6][7][8] . Further on, anosmia and ageusia also emerged as prevalent and relatively discriminative symptoms of COVID-19 infection [9][10][11][12] . As clinical data started to accumulate, reviews describing the potential cardiovascular 13 , gastrointestinal 14 , neurological 15 and cutaneous manifestations 16 of the disease were published.…”

Self-reported symptoms in healthy young adults to predict potential coronavirus disease 2019

“…Hence, prioritizing testing and efficiently isolating positive cases is a vital aim. To this end, several studies examined the utility of self-reported symptoms in predicting coronavirus disease 2019 (COVID-19) and found a correlation between constitutional and respiratory symptoms with a positive test [ [11] , [12] , [13] ]. However, low response rates in young healthy adults [ 12 , 13 ] and their exclusion from studies [ 11 ], results in a dearth of data guiding testing in this population.…”