Productivity changes during the entire COVID-19 pandemic and its associated risk factors

Objectives: investigate productivity loss during the COVID-19 pandemic and identify risk patterns by examining indicators of work quantity and quality in a population-based cohort in the North of the Netherlands. Methods: Longitudinal data from the Work and Income module of the Lifelines Covid-19 cohort were used, enriched with registry data from Statistics Netherlands. Data of n=11,462 workers were collected from 2020 to 2022. Productivity loss was measured using four indicators: unemployment, sickness absence rate, loss of work hours, and loss of work quality. Generalized estimating equations (GEE) were used to examine the association between socioeconomic, health-, and work-related characteristics and productivity loss indicators. Results: Unemployment remained low (<0.5%) throughout the study period. In contrast, the prevalence of sickness absence, reduction of work hours and loss work quality peaked at 8.7%, 15%, and 4.7% respectively. Two sets of indicators emerged from the analysis. Socioeconomic characteristics were associated with higher risk for unemployment and sickness absence, and lower odds for loss of hours and work quality. Other characteristics, such as critical job, were significantly associated with higher odds for sickness absence and loss of quality, while having lower for unemployment and loss of hours. Discussion: Despite low unemployment rates, other aspects of productivity loss were more prevalent throughout the pandemic. The indicator sets provide guidance on the gaps in support during pandemic. When preparing for future crises, attention should be paid to both quantity and quality aspects of productivity loss and their risk factors to protect workers and minimize losses in productivity.