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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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Detalles Bibliográficos
Autores principales: White, Zackery, Schlegelmilch, Jeff, Ratner, Jackie, Saxena, Gunjan, Wongsodirdjo, Kevin, Aguilar, Susanna, Kushner, Daniel, Ortega, Jim, Paaso, Aleksi, Bahramirad, Shay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591754/
https://www.ncbi.nlm.nih.gov/pubmed/32907678
http://dx.doi.org/10.1017/dmp.2020.353
Descripción
Sumario: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.