Modeling the impact of healthcare personnel compensation and benefits on the spread of COVID-19 in skilled nursing facilities
- 1Biomathematics Graduate Program, Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States of America
- 2Department of Population Health and Pathobiology, North Carolina State University, Raleigh, North Carolina, United States of America
- 3Department of Mathematics, University of Tennessee, Knoxville, Tennessee, United States of America
Abstract
The COVID-19 pandemic highlighted the vulnerability of older adults. Older adults are particularly at risk when in group home settings. One particular type of group living, skilled nursing facilities (SNF), was highly impacted by COVID-19, with their residents accounting for a substantial proportion of pandemic-related deaths. Mitigating the number of infections and thus deaths in this population has been a subject of many studies. However, these studies often focus on interventions such as isolation, vaccination, and the use of PPE when interacting with residents, which are resident-focused. This study aims to evaluate the efficacy of healthcare personnel (HCP)-focused interventions. The interventions of focus include full-time employment, compulsory sick leave policies, and vaccination requirements. To study these interventions, we used an agent-based model (ABM) with synthetic populations derived from census data over a period of one year. Along with the interventions, we included a scenario in which none of the policies were enforced, serving as a baseline. We compared two main outcomes: the total number of infections and the outbreak count. Comparisons to the baseline show absolute decreases in infections among residents and personnel for all interventions, with the combination of sick leave and full-time personnel resulting in a 12% reduction in resident infections (from 172.65 ± 1.11 [95% Confidence Interval] to 150.72 ± 0.96); and 45% reduction in personnel infections (from 8.45 ± 0.07 to 4.73 ± 0.04). These findings provide a robust framework for policy development to enhance safety and the quality of care in SNF.
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BibTeX
@article{sweet2026modeling,
title = {{Modeling the impact of healthcare personnel compensation and benefits on the spread of COVID-19 in skilled nursing facilities}},
author = {Abigail Sweet and Sarah Rhea and Suzanne M. Lenhart and Agricola Odoi and Cristina Lanzas and Alun Lloyd},
journal = {PLOS Aging and Health},
year = {2026},
month = sep,
doi = {10.1371/journal.page.0000040},
url = {https://doi.org/10.1371/journal.page.0000040},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Modeling the impact of healthcare personnel compensation and benefits on the spread of COVID-19 in skilled nursing facilities
AU - Abigail Sweet
AU - Sarah Rhea
AU - Suzanne M. Lenhart
AU - Agricola Odoi
AU - Cristina Lanzas
AU - Alun Lloyd
PY - 2026
DA - 2026/09/17
JO - PLOS Aging and Health
DO - 10.1371/journal.page.0000040
UR - https://doi.org/10.1371/journal.page.0000040
AB - The COVID-19 pandemic highlighted the vulnerability of older adults. Older adults are particularly at risk when in group home settings. One particular type of group living, skilled nursing facilities (SNF), was highly impacted by COVID-19, with their residents accounting for a substantial proportion of pandemic-related deaths. Mitigating the number of infections and thus deaths in this population has been a subject of many studies. However, these studies often focus on interventions such as isolation, vaccination, and the use of PPE when interacting with residents, which are resident-focused. This study aims to evaluate the efficacy of healthcare personnel (HCP)-focused interventions. The interventions of focus include full-time employment, compulsory sick leave policies, and vaccination requirements. To study these interventions, we used an agent-based model (ABM) with synthetic populations derived from census data over a period of one year. Along with the interventions, we included a scenario in which none of the policies were enforced, serving as a baseline. We compared two main outcomes: the total number of infections and the outbreak count. Comparisons to the baseline show absolute decreases in infections among residents and personnel for all interventions, with the combination of sick leave and full-time personnel resulting in a 12% reduction in resident infections (from 172.65 ± 1.11 [95% Confidence Interval] to 150.72 ± 0.96); and 45% reduction in personnel infections (from 8.45 ± 0.07 to 4.73 ± 0.04). These findings provide a robust framework for policy development to enhance safety and the quality of care in SNF.
SN - 3070-801X
ER -