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Beyond Predicting the Number of Infections: Predicting Who is Likely to Be COVID Negative or Positive
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, w...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721298/ https://www.ncbi.nlm.nih.gov/pubmed/33299369 http://dx.doi.org/10.2147/RMHP.S273755 |
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author | Zhang, Stephen X Sun, Shuhua Afshar Jahanshahi, Asghar Wang, Yifei Nazarian Madavani, Abbas Li, Jizhen Mokhtari Dinani, Maryam |
author_facet | Zhang, Stephen X Sun, Shuhua Afshar Jahanshahi, Asghar Wang, Yifei Nazarian Madavani, Abbas Li, Jizhen Mokhtari Dinani, Maryam |
author_sort | Zhang, Stephen X |
collection | PubMed |
description | 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 information. We hope this research opens a new research avenue to predict the individual likelihood of COVID-19 infection by risk factors. |
format | Online Article Text |
id | pubmed-7721298 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Dove |
record_format | MEDLINE/PubMed |
spelling | pubmed-77212982020-12-08 Beyond Predicting the Number of Infections: Predicting Who is Likely to Be COVID Negative or Positive Zhang, Stephen X Sun, Shuhua Afshar Jahanshahi, Asghar Wang, Yifei Nazarian Madavani, Abbas Li, Jizhen Mokhtari Dinani, Maryam Risk Manag Healthc Policy Original Research 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 information. We hope this research opens a new research avenue to predict the individual likelihood of COVID-19 infection by risk factors. Dove 2020-12-03 /pmc/articles/PMC7721298/ /pubmed/33299369 http://dx.doi.org/10.2147/RMHP.S273755 Text en © 2020 Zhang et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php). |
spellingShingle | Original Research Zhang, Stephen X Sun, Shuhua Afshar Jahanshahi, Asghar Wang, Yifei Nazarian Madavani, Abbas Li, Jizhen Mokhtari Dinani, Maryam Beyond Predicting the Number of Infections: Predicting Who is Likely to Be COVID Negative or Positive |
title | Beyond Predicting the Number of Infections: Predicting Who is Likely to Be COVID Negative or Positive |
title_full | Beyond Predicting the Number of Infections: Predicting Who is Likely to Be COVID Negative or Positive |
title_fullStr | Beyond Predicting the Number of Infections: Predicting Who is Likely to Be COVID Negative or Positive |
title_full_unstemmed | Beyond Predicting the Number of Infections: Predicting Who is Likely to Be COVID Negative or Positive |
title_short | Beyond Predicting the Number of Infections: Predicting Who is Likely to Be COVID Negative or Positive |
title_sort | beyond predicting the number of infections: predicting who is likely to be covid negative or positive |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7721298/ https://www.ncbi.nlm.nih.gov/pubmed/33299369 http://dx.doi.org/10.2147/RMHP.S273755 |
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