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

White, Zachery; Schlegelmilch, Jeffrey; Ratner, Jacqueline J.; Saxena, Gunjan; Wongsodirdjo, Kevin S.; Aguilar, Susanna; Kushner, Daniel; Ortega, Jim; Paaso, Aleksi; Bahramirad, Shay

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.


  • thumnail for current_data_gaps_in_modeling_essential_worker_absenteeism_due_to_covid19_JDMPHP.pdf current_data_gaps_in_modeling_essential_worker_absenteeism_due_to_covid19_JDMPHP.pdf application/pdf 125 KB Download File

Also Published In

Disaster Medicine and Public Health Preparedness

More About This Work

Academic Units
National Center for Disaster Preparedness
Published Here
October 28, 2020