Protection of healthcare workforce is of paramount relevance for the care of infected and non-infected patients in the setting of a pandemic such as coronavirus disease 2019 (COVID-19). Healthcare workers are at increased risk to become infected because of contact to infected patients, infected co-workers and their community outside the hospital.
The ideal organisational strategy to protect the healthcare workforce in a situation in which social distancing cannot be maintained at the workplace remains to be determined. In this study, we have mathematically modelled strategies for the employment of hospital workforce with the goal to simulate health and productivity of the workers. Therefore, deterministic models were extended to account for stochastic influences potentially occurring in rather small populations.
The models were also designed to determine if desynchronization of medical teams by dichotomizing the workers may protect the workforce. Our studies model workforce productivity depending on the infection rate, the presence of reinfection and the efficiency of home office. As an application example, we apply our theory to the case of coronavirus disease 2019 (COVID-19). The results of the models reveal that a desynchronization strategy in which two medical teams work alternating for 7 days reduces the infection rate of the healthcare workforce. In case of immunity to the infectious agent this affect is mainly relevant at early stages of the pandemic. This effect is independent on infection rates and increases the overall workforce productivity under certain situations.