Beyond predicting the number of infections: predicting who is likely to be COVID negative or positive (Preprint)

Author:

Zhang Stephen X.ORCID,Sun Shuhua,Jahanshahi Asghar Afshar,Wang Yifei,Madavani Abbas Nazarian,Dinani Maryam Mokhtar

Abstract

BACKGROUND

The current COVID-19 pandemic and the severe shortage of testing kits in many countries pose a first and foremost problem in medical informatics—the information on the risk predictors of people who are at greater risk of contracting COVID-19 to enable more targeted infectious disease prevention, communication, testing, and control.

OBJECTIVE

This study aims to identify individuals’ likelihood to be COVID negative or positive, enabling more targeted infectious disease prevention and control.

METHODS

We conducted a primary survey of 521 adults on April 1-10, 2020 in Iran, where the official infection rate was 0.08%. In our sample, 3% reported positive and 15% were unsure whether they were infected. This relatively high positive rate enabled us to conduct the analysis at 5% significance level.

RESULTS

Adults who exercised more were more likely to be COVID-19 negative. Each additional hour of exercise per day predicted a 78% increase in the likelihood of being COVID-19 negative. Adults with chronic medical illnesses were 48% more likely to be COVID-19 negative. In terms of work situation, those who worked from home were the most likely to be COVID-19 negative, and those who had stopped working were the most likely to be COVID-19 positive. Individuals in larger organizations were less likely to be COVID-19 positive.

CONCLUSIONS

This study enables more targeted infectious disease prevention and control by identifying the risk factors of COVID-19 infections from a set of readily accessible information on demographic and work characteristics. We hope this research opens a new research avenue of medical informatics to help healthcare services to predict the individual likelihood of COVID-19 infection by risk factors.

Publisher

JMIR Publications Inc.

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