Beyond Predicting the Number of Infections: Predicting Who is Likely to Be COVID Negative or Positive

Abstract

Stephen X Zhang,1 Shuhua Sun,2 Asghar Afshar Jahanshahi,3 Yifei Wang,4 Abbas Nazarian Madavani,5 Jizhen Li,6 Maryam Mokhtari Dinani7 1Faculty of the Professions, University of Adelaide, Adelaide, SA, Australia; 2A. B. Freeman School of Business, Tulane University, New Orleans, LA, USA; 3CENTRUM Católica Graduate Business School (CCGBS), Pontificia Universidad Católica del Perú (PUCP), Lima, Peru; 4School of Economics and Management, Tongji University, Shanghai, People’s Republic of China; 5Faculty of Sport Sciences, Shahid Rajaee Teacher Training University, Tehran, Iran; 6School of Economics & Management, Tsinghua University, Beijing, People’s Republic of China; 7Faculty of Sport Sciences, Alzahra University, Tehran, IranCorrespondence: Stephen X ZhangFaculty of the Professions, University of Adelaide, 9-28 Nexus 10 Tower, 10 Pulteney St, Adelaide, SA 5000, AustraliaTel [phone]Fax [phone]Email [email protected]: This study aims to identify individuals’ likelihood of being COVID negative or positive, enabling more targeted infectious disease prevention and control when there is a shortage of COVID-19 testing kits.Methods: We conducted a primary survey of 521 adults on April 1– 10, 2020 in Iran, where 3% reported being COVID-19 positive and 15% were unsure whether they were infected. This relatively high positive rate enabled us to conduct the analysis at the 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 health issues were 48% more likely to be COVID-19 negative. Those working from home were the most likely to be COVID-19 negative, and those who had stopped working due to the pandemic were the most likely to be COVID-19 positive. Adults employed in larger organizations were less likely to be COVID-19 positive.Conclusion: 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. We hope this research opens a new research avenue to predict the individual likelihood of COVID-19 infection by risk factors.Keywords: individual infection prediction, COVID-19 infection, testing shortage, risk factors

Keywords

• individual infection prediction
• covid-19 infection
• testing shortage
• risk factors