The number of sick leave days has risen noticeably since the end of COVID-19 restrictions across Europe. In Austria, employees were absent for more than 15 days on average in 2024—around 20% more than before the pandemic. A substantial share of this increase is linked to respiratory illnesses such as influenza and COVID-19, but the underlying drivers remain poorly understood. This development affects not only public health but also the economy and questions of social equity, as certain groups of workers are more affected than others.

The increase in sick leave may be linked to a combination of biological, behavioural, and social factors whose roles remain to be clarified. Undetected COVID-19 infections could be contributing to the statistics. At the same time, the interruption of normal infection cycles during the pandemic may have left the population more susceptible to seasonal respiratory viruses. Shifts in workplace culture also appear relevant, as staying at home when feeling unwell has become more common. Finally, lower vaccination uptake in certain groups may have reduced protection against circulating pathogens.

To explore these factors, the project combines several unique Austrian data sources. These include the Austrian Micro Data Center established by Statistik Austria, which provides access to linked population and employment data under strict privacy protection. We also use national health surveys, sick-leave records from the social insurance system, and wastewater surveillance data that give early signals of circulating viruses. Using these data, we will build a new model that links infections to sick leave and its economic consequences, and projects how trends may evolve in the future and under different policy scenarios.

The project will generate new insights into what is driving the rise in sick leave and how these trends may develop in the years ahead. Public authorities will gain an evidence base for designing fair and effective health and labour policies. Employers and unions will benefit from forecasts of workforce availability and sector-specific risks. Beyond Austria, the methods developed here will provide an international reference for linking infection dynamics to labour-market outcomes under strict privacy safeguards. By engaging stakeholders throughout and publishing aggregated results openly, the project will ensure that its findings are translated into practice and support both national decision-making and international research.

The project is funded by the Data:Research:Austria grant programme of the Austrian Academy of Sciences.