{
  "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.",
  "abstract_shown": true,
  "affiliations": [
    "Biomathematics Graduate Program, Department of Mathematics, North Carolina State University, Raleigh, North Carolina, United States of America",
    "Department of Population Health and Pathobiology, North Carolina State University, Raleigh, North Carolina, United States of America",
    "Department of Mathematics, University of Tennessee, Knoxville, Tennessee, United States of America"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Abigail Sweet"
    },
    {
      "affs": [
        1
      ],
      "name": "Sarah Rhea"
    },
    {
      "affs": [
        2
      ],
      "name": "Suzanne M. Lenhart"
    },
    {
      "name": "Agricola Odoi"
    },
    {
      "name": "Cristina Lanzas"
    },
    {
      "name": "Alun Lloyd"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/708wwfhfd4g60.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.page.0000040",
  "fulltext_url": null,
  "id": "708wwfhfd4g60",
  "issns": [
    "3070-801X"
  ],
  "landing_url": "https://doi.org/10.1371/journal.page.0000040",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2611|COVID-19 epidemiological studies"
    ],
    [
      "plos",
      "/Biology and life sciences/Immunology/Vaccination and immunization"
    ],
    [
      "plos",
      "/Computer and information sciences/Systems science/Agent-based modeling"
    ],
    [
      "plos",
      "/Medicine and health sciences/Epidemiology"
    ],
    [
      "plos",
      "/Medicine and health sciences/Epidemiology/Medical risk factors"
    ],
    [
      "plos",
      "/Medicine and health sciences/Health care/Health care facilities"
    ],
    [
      "plos",
      "/Medicine and health sciences/Immunology/Vaccination and immunization"
    ],
    [
      "plos",
      "/Medicine and health sciences/Medical conditions/Infectious diseases/Infectious disease control/Vaccines"
    ],
    [
      "plos",
      "/Medicine and health sciences/Medical conditions/Infectious diseases/Viral diseases/COVID 19"
    ],
    [
      "plos",
      "/Medicine and health sciences/Public and occupational health/Preventive medicine/Vaccination and immunization"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Systems science/Agent-based modeling"
    ],
    [
      "plos",
      "/Research and analysis methods/Simulation and modeling/Agent-based modeling"
    ],
    [
      "plos",
      "/Social sciences/Economics/Labor economics/Employment"
    ]
  ],
  "openalex": "W7213453798",
  "pdf_url": "https://journals.plos.org/agingandhealth/article/file?id=10.1371/journal.page.0000040&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-17",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/708wwfhfd4g60.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:49Z",
      "native_id": "10.1371/journal.page.0000040",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.page.0000040"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "plos:immunology",
      "subfield": "immunology"
    },
    {
      "field": "medicine",
      "origin": "plos:epidemiology",
      "subfield": "epidemiology-public-health"
    },
    {
      "field": "medicine",
      "origin": "plos:infectious diseases",
      "subfield": "infectious-disease"
    }
  ],
  "title": "Modeling the impact of healthcare personnel compensation and benefits on the spread of COVID-19 in skilled nursing facilities",
  "title_text": "Modeling the impact of healthcare personnel compensation and benefits on the spread of COVID-19 in skilled nursing facilities",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:49Z",
  "url": "https://research.draconitic.com/paper/708wwfhfd4g60",
  "venue": "PLOS Aging and Health",
  "versions": []
}