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Improving mathematical modeling of interventions to prevent healthcare-associated infections by interrupting transmission or pathogens: How common modeling assumptions about colonized individuals impact intervention effectiveness estimates
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Camden D. Gowler,
Roles Formal analysis, Methodology, Software, Writing – original draft
Affiliations Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America, Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, United States of America
⨯ - Rachel B. Slayton,
- Sujan C. Reddy,
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Justin J. O’Hagan
Roles Conceptualization, Formal analysis, Methodology, Software, Writing – review & editing
* E-mail: justinohagan@gmail.com
Affiliation Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America
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https://orcid.org/0000-0003-3596-614X
Improving mathematical modeling of interventions to prevent healthcare-associated infections by interrupting transmission or pathogens: How common modeling assumptions about colonized individuals impact intervention effectiveness estimates
- Camden D. Gowler,
- Rachel B. Slayton,
- Sujan C. Reddy,
- Justin J. O’Hagan
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- Published: February 28, 2022
- https://doi.org/10.1371/journal.pone.0264344