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COVID-19 novel coronavirus test sample

Israeli researchers have determined in a new study that the initial symptom of loss of taste (ageusia) and smell (anosmia) is the strongest predictor of a positive test result for COVID-19, the disease caused by SARS-CoV-2, the novel coronavirus.

The paper, entitled ‘Who should we test for COVID-19? A triage model built from national symptom surveys‘ was published May 21, 2020 in the online medical journal MedRxiv, and listed confusion as the next strongest predictor, followed by fatigue and then diarrhea. Fever, headache and cough came later, as opposed to their initial appearance as primary symptoms when COVID-19 first began to terrorize the world last December.

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The researchers noted, in fact, that “the extended features model” they created in the course of their work “suggested that while dry cough has an essential role in predicting COVID-19 diagnosis, moist cough does not and thus may help distinguish between cases of COVID19 and other infections.”

A total of 695,586 and 66,447 responses by adults age 20 and up to a survey online and an IVR version, respectively, were reviewed by the members of the research team, which included Weizmann Institute of Science, Ruth Rappaport Children’s Hospital Rambam Healthcare Campus, The public knowledge workshop of Tel Aviv, Maccabi Healthcare Services, Clalit Research Institute Clalit Health Services, and the School of Public Health at Sackler Faculty of Medicine Tel Aviv University.

Only responses in Hebrew were included to avoid translation discrepancies, the researchers said. Eventually, overall 43,752 responses were eventually included in the study, of which 498 self-reported as being COVID-19 diagnosed.

The researchers pointed out that most of the diagnostic models that have been published up to this point on the subject of COVID-19 have been based on datasets from China. They have included complex features that needed to be extracted through blood tests and imaging scans, which made them more difficult and time-consuming to use.

“In this work, we devised a prediction model which was based solely on self-reported information, and as such it could be easily deployed and used instantly in other countries,” the researchers said, suggesting that for nations with fewer resources and tighter budgets, their model might be a better fit.

“Overall, our approach can be utilized worldwide to direct the limited resources towards individuals who are more likely to test positive for COVID-19, leading to faster isolation of infected patients and therefore to reduced rates of virus spread.”

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Hana Levi Julian is a Middle East news analyst with a degree in Mass Communication and Journalism from Southern Connecticut State University. A past columnist with The Jewish Press and senior editor at Arutz 7, Ms. Julian has written for Babble.com, Chabad.org and other media outlets, in addition to her years working in broadcast journalism.