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Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers

A major strategy to prevent the spread of COVID-19 is the limiting of in-person contacts. However, limiting contacts is impractical or impossible for the many disabled people who do not live in care facilities but still require caregivers to assist them with activities of daily living. We seek to de...

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Autores principales: Valles, Thomas E., Shoenhard, Hannah, Zinski, Joseph, Trick, Sarah, Porter, Mason A., Lindstrom, Michael R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9232173/
https://www.ncbi.nlm.nih.gov/pubmed/35584133
http://dx.doi.org/10.1371/journal.pcbi.1010042
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author Valles, Thomas E.
Shoenhard, Hannah
Zinski, Joseph
Trick, Sarah
Porter, Mason A.
Lindstrom, Michael R.
author_facet Valles, Thomas E.
Shoenhard, Hannah
Zinski, Joseph
Trick, Sarah
Porter, Mason A.
Lindstrom, Michael R.
author_sort Valles, Thomas E.
collection PubMed
description A major strategy to prevent the spread of COVID-19 is the limiting of in-person contacts. However, limiting contacts is impractical or impossible for the many disabled people who do not live in care facilities but still require caregivers to assist them with activities of daily living. We seek to determine which interventions can best prevent infections of disabled people and their caregivers. To accomplish this, we simulate COVID-19 transmission with a compartmental model that includes susceptible, exposed, asymptomatic, symptomatically ill, hospitalized, and removed/recovered individuals. The networks on which we simulate disease spread incorporate heterogeneity in the risk levels of different types of interactions, time-dependent lockdown and reopening measures, and interaction distributions for four different groups (caregivers, disabled people, essential workers, and the general population). Of these groups, we find that the probability of becoming infected is largest for caregivers and second largest for disabled people. Consistent with this finding, our analysis of network structure illustrates that caregivers have the largest modal eigenvector centrality of the four groups. We find that two interventions—contact-limiting by all groups and mask-wearing by disabled people and caregivers—most reduce the number of infections in disabled and caregiver populations. We also test which group of people spreads COVID-19 most readily by seeding infections in a subset of each group and comparing the total number of infections as the disease spreads. We find that caregivers are the most potent spreaders of COVID-19, particularly to other caregivers and to disabled people. We test where to use limited infection-blocking vaccine doses most effectively and find that (1) vaccinating caregivers better protects disabled people from infection than vaccinating the general population or essential workers and that (2) vaccinating caregivers protects disabled people from infection about as effectively as vaccinating disabled people themselves. Our results highlight the potential effectiveness of mask-wearing, contact-limiting throughout society, and strategic vaccination for limiting the exposure of disabled people and their caregivers to COVID-19.
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spelling pubmed-92321732022-06-25 Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers Valles, Thomas E. Shoenhard, Hannah Zinski, Joseph Trick, Sarah Porter, Mason A. Lindstrom, Michael R. PLoS Comput Biol Research Article A major strategy to prevent the spread of COVID-19 is the limiting of in-person contacts. However, limiting contacts is impractical or impossible for the many disabled people who do not live in care facilities but still require caregivers to assist them with activities of daily living. We seek to determine which interventions can best prevent infections of disabled people and their caregivers. To accomplish this, we simulate COVID-19 transmission with a compartmental model that includes susceptible, exposed, asymptomatic, symptomatically ill, hospitalized, and removed/recovered individuals. The networks on which we simulate disease spread incorporate heterogeneity in the risk levels of different types of interactions, time-dependent lockdown and reopening measures, and interaction distributions for four different groups (caregivers, disabled people, essential workers, and the general population). Of these groups, we find that the probability of becoming infected is largest for caregivers and second largest for disabled people. Consistent with this finding, our analysis of network structure illustrates that caregivers have the largest modal eigenvector centrality of the four groups. We find that two interventions—contact-limiting by all groups and mask-wearing by disabled people and caregivers—most reduce the number of infections in disabled and caregiver populations. We also test which group of people spreads COVID-19 most readily by seeding infections in a subset of each group and comparing the total number of infections as the disease spreads. We find that caregivers are the most potent spreaders of COVID-19, particularly to other caregivers and to disabled people. We test where to use limited infection-blocking vaccine doses most effectively and find that (1) vaccinating caregivers better protects disabled people from infection than vaccinating the general population or essential workers and that (2) vaccinating caregivers protects disabled people from infection about as effectively as vaccinating disabled people themselves. Our results highlight the potential effectiveness of mask-wearing, contact-limiting throughout society, and strategic vaccination for limiting the exposure of disabled people and their caregivers to COVID-19. Public Library of Science 2022-05-18 /pmc/articles/PMC9232173/ /pubmed/35584133 http://dx.doi.org/10.1371/journal.pcbi.1010042 Text en © 2022 Valles et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Valles, Thomas E.
Shoenhard, Hannah
Zinski, Joseph
Trick, Sarah
Porter, Mason A.
Lindstrom, Michael R.
Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers
title Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers
title_full Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers
title_fullStr Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers
title_full_unstemmed Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers
title_short Networks of necessity: Simulating COVID-19 mitigation strategies for disabled people and their caregivers
title_sort networks of necessity: simulating covid-19 mitigation strategies for disabled people and their caregivers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9232173/
https://www.ncbi.nlm.nih.gov/pubmed/35584133
http://dx.doi.org/10.1371/journal.pcbi.1010042
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