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Deconstructing the effects of stochasticity on transmission of hospital-acquired infections in ICUs

The inherent stochasticity in transmission of hospital-acquired infections (HAIs) has complicated our understanding of transmission pathways. It is particularly difficult to detect the impact of changes in the environment on acquisition rate due to stochasticity. In this study, we investigated the i...

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Autores principales: Haghpanah, Fardad, Lin, Gary, Klein, Eili
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498044/
https://www.ncbi.nlm.nih.gov/pubmed/37711144
http://dx.doi.org/10.1098/rsos.230277
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author Haghpanah, Fardad
Lin, Gary
Klein, Eili
author_facet Haghpanah, Fardad
Lin, Gary
Klein, Eili
author_sort Haghpanah, Fardad
collection PubMed
description The inherent stochasticity in transmission of hospital-acquired infections (HAIs) has complicated our understanding of transmission pathways. It is particularly difficult to detect the impact of changes in the environment on acquisition rate due to stochasticity. In this study, we investigated the impact of uncertainty (epistemic and aleatory) on nosocomial transmission of HAIs by evaluating the effects of stochasticity on the detectability of seasonality of admission prevalence. For doing so, we developed an agent-based model of an ICU and simulated the acquisition of HAIs considering the uncertainties in the behaviour of the healthcare workers (HCWs) and transmission of pathogens between patients, HCWs, and the environment. Our results show that stochasticity in HAI transmission weakens our ability to detect the effects of a change, such as seasonality patterns, on acquisition rate, particularly when transmission is a low-probability event. In addition, our findings demonstrate that data compilation can address this issue, while the amount of required data depends on the size of the said change and the degree of uncertainty. Our methodology can be used as a framework to assess the impact of interventions and provide decision-makers with insight about the minimum required size and target of interventions in a healthcare facility.
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spelling pubmed-104980442023-09-14 Deconstructing the effects of stochasticity on transmission of hospital-acquired infections in ICUs Haghpanah, Fardad Lin, Gary Klein, Eili R Soc Open Sci Mathematics The inherent stochasticity in transmission of hospital-acquired infections (HAIs) has complicated our understanding of transmission pathways. It is particularly difficult to detect the impact of changes in the environment on acquisition rate due to stochasticity. In this study, we investigated the impact of uncertainty (epistemic and aleatory) on nosocomial transmission of HAIs by evaluating the effects of stochasticity on the detectability of seasonality of admission prevalence. For doing so, we developed an agent-based model of an ICU and simulated the acquisition of HAIs considering the uncertainties in the behaviour of the healthcare workers (HCWs) and transmission of pathogens between patients, HCWs, and the environment. Our results show that stochasticity in HAI transmission weakens our ability to detect the effects of a change, such as seasonality patterns, on acquisition rate, particularly when transmission is a low-probability event. In addition, our findings demonstrate that data compilation can address this issue, while the amount of required data depends on the size of the said change and the degree of uncertainty. Our methodology can be used as a framework to assess the impact of interventions and provide decision-makers with insight about the minimum required size and target of interventions in a healthcare facility. The Royal Society 2023-09-13 /pmc/articles/PMC10498044/ /pubmed/37711144 http://dx.doi.org/10.1098/rsos.230277 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Mathematics
Haghpanah, Fardad
Lin, Gary
Klein, Eili
Deconstructing the effects of stochasticity on transmission of hospital-acquired infections in ICUs
title Deconstructing the effects of stochasticity on transmission of hospital-acquired infections in ICUs
title_full Deconstructing the effects of stochasticity on transmission of hospital-acquired infections in ICUs
title_fullStr Deconstructing the effects of stochasticity on transmission of hospital-acquired infections in ICUs
title_full_unstemmed Deconstructing the effects of stochasticity on transmission of hospital-acquired infections in ICUs
title_short Deconstructing the effects of stochasticity on transmission of hospital-acquired infections in ICUs
title_sort deconstructing the effects of stochasticity on transmission of hospital-acquired infections in icus
topic Mathematics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498044/
https://www.ncbi.nlm.nih.gov/pubmed/37711144
http://dx.doi.org/10.1098/rsos.230277
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