Stay-At-Home Orders during the COVID-19 Pandemic and the Effect on Hospitalization among Workers
There is ongoing policy discussion and public debate about the net effects of the non-medical interventions (NMIs) that were put in place to mitigate the spread of COVID-19. These measures were implemented to control the pandemic and may have produced unanticipated negative health effects, especially during lockdown times when the “stay-at-home order” (SHOs) were in place for non-essential workers. This study will evaluate if the SOHs had their intended effect of reducing inpatient utilization.
Goal
When the COVID-19 pandemic began, one of the key concerns was excess demand for inpatient beds and particularly inpatient intensive care unit (ICU) beds. How effective the “stay at home” policy was at reducing the transmission of COVID-19 and thereby ICU beds is unknown. In this study, we will analyze the effect of stay-at-home orders among essential workers and non-essential workers on the probability of hospitalization for COVID-19 in both the short and midterm.
Approach
Health outcomes will be measured in terms of hospitalizations and length of stay. We will examine the marginal impact of staying at home on increased risk of hospitalization.
The analytic approach will include a difference-in-differences model which is a quasi-experimental design that compares the changes in outcomes over time between essential workers who were more exposed to COVID-19 (”treatment group”) during lockdowns and non-essential workers who were not (“comparison group”). We compare the effect of the lockdown, analyzing the difference between the change in outcomes before and after (difference one) in the treatment versus control group (difference two).
Collaboration partners
Dr. van den Broek-Altenburg is Principal Investigator on this project. She is trained as a Health Services Researcher, with cognates in Biostatistics, Epidemiology and Health Economics. She has 20 years of experience experience in health policy and health economics.
Dr. Bram Bakker is co-Investigator on this project. He has a graduate degree in Psychology with an emphasis on methodology, cognitive science and computational modeling and a PhD in modelling and machine learning with neural networks.
Drs. Van den Broek and Bakker will be assisted by a team of experts from national and international academia and public health.
(Expected) Results
The attempt to minimize COVID-19 related hospitalizations may have been offset by an increase in the probability of hospitalization due to reduced access to primary care. The direction of the effect is but the magnitude is unclear. We expect the probability of hospitalization to be higher among non-essential workers after the lockdown order was lifted. This “rebound” effect may be mitigated by vaccines or other factors, but the magnitude will show the true effect of the SHOs on total COVID-19 related hospitalizations.
This project will provide important guidance about how to design policies to maximize inpatient availability in future pandemics.