The researchers then created a mathematical model that predicted with almost 80% accuracy whether an individual is likely to have COVID-19 based on their age, sex and a combination of four key symptoms: loss of smell or taste, severe or persistent cough, fatigue and skipping meals.
Researchers gathered the information from almost 2.5 million people in the United Kingdom and about 170,000 people in the United States who said if they were feeling well or felt symptoms into a smartphone app from March 24 to April 21. It was based on data from a COVID-19 smartphone app.
"However, as Sars-CoV-2 is a new virus, there is no long-term evidence of immunity".
"COVID-19 is a very stressful experience for everyone, particularly those with complex mental health needs", Dr Brown said.
"This study provides a baseline understanding of the early disease burden of COVID-19 in pediatric patients", said Hariprem Rajasekhar, a pediatric intensivist involved in conducting the study at Robert Wood Johnson Medical School's Department of Pediatrics. Under-testing of patients with COVID-19 can lead to further spread of the disease.
Using the United Kingdom cohort, researchers identified that a combination of loss of smell and taste, fatigue, persistent cough, and loss of appetite resulted in the best symptom prediction model for COVID-19.
The authors followed 48 American and Canadian children and young adults (from newborns to 21 years old) who were admitted to pediatric intensive care units (PICU) for COVID-19 in March and April.
The authors said their study suggests that children may have different COVID-19 symptoms than adults. They found a wide range of symptoms compared to cold and flu, and warn against focusing only on fever and cough. Of these children, one had an evident history of exposure to the coronavirus, suspected history of exposure in one, while no such history of exposure was found among the rest.
Citing the limitations of the study, the researchers said the prediction is based on self-reported nature of the included data, which they said can not replace physiological assessments of smell and taste function, or testing people's samples for SARS-CoV-2 genetic material.
Professor Gray agreed. "This is a group that's probably going to need more support, with isolation, physical distancing, hand washing etc, and clinicians may be the ones who need to be thinking and working on this to assist this vulnerable population", he said.
Based on these data, the researchers estimated how numerous untested app users were likely to be infected, too.
They added that this would help in focussing tracking and testing efforts where they are most needed.
The research consisted of an observational study of COVID-19 testing of 961 health care workers.