Current Data Gaps in Modeling Essential Worker Absenteeism Due to COVID-19

With the uncertain physical and mental health implications of COVID-19 infection, companies have taken a myriad of actions that aim to reduce the risk of employees contracting the virus, with most grounded in reducing or eliminating in-person interactions. Our preliminary analysis indicates that whi...

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Bibliographic Details
Published in:	Disaster medicine and public health preparedness Vol. 15; no. 4; p. e10
Main Authors:	White, Zackery, Schlegelmilch, Jeff, Ratner, Jackie, Saxena, Gunjan, Wongsodirdjo, Kevin, Aguilar, Susanna, Kushner, Daniel, Ortega, Jim, Paaso, Aleksi, Bahramirad, Shay
Format:	Journal Article
Language:	English
Published:	United States 01-08-2021
Subjects:	Absenteeism COVID-19 - epidemiology COVID-19 - therapy Data Collection - standards Employment - statistics & numerical data Hospitalization Humans Models, Statistical COVID-19 absenteeism critical Infrastructure modelling pandemics
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Summary:	With the uncertain physical and mental health implications of COVID-19 infection, companies have taken a myriad of actions that aim to reduce the risk of employees contracting the virus, with most grounded in reducing or eliminating in-person interactions. Our preliminary analysis indicates that while there is some data to support modelling absenteeism, there are gaps in the available evidence, requiring the use of assumptions that limit precision and efficacy for decision support. Improved data on time-to-recovery after hospitalization, absenteeism due to family or other household member illness, and mental health's impact on returning to work will support the development of more robust absenteeism models and analytical approaches.
ISSN:	1938-744X
DOI:	10.1017/dmp.2020.353