Beyond predicting the number of infections: Predicting who is likely to be covid negative or positive

Stephen Xu Zhang, Shuhua Sun, Asghar Afshar Jahanshahi, Yifei Wang, Abbas Nazarian Madavani, Jizhen Li, Maryam Mokhtari Dinani

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

8 Citas (Scopus)

Resumen

Background: 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 informa-tion. We hope this research opens a new research avenue to predict the individual likelihood of COVID-19 infection by risk factors.
Idioma originalEspañol
Páginas (desde-hasta)2811-2818
Número de páginas8
PublicaciónRisk Management and Healthcare Policy
Volumen13
EstadoPublicada - 1 ene. 2020

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