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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.
  • Valles TE; Department of Mathematics, University of California, San Diego, San Diego, California, United States of America.
  • Shoenhard H; Department of Mathematics, University of California, Los Angeles, Los Angeles, California, United States of America.
  • Zinski J; Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
  • Trick S; Department of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.
  • Porter MA; Assistant Editor at tvo.org (TVOntario), Toronto, Ontario, Canada.
  • Lindstrom MR; Department of Mathematics, University of California, Los Angeles, Los Angeles, California, United States of America.
PLoS Comput Biol ; 18(5): e1010042, 2022 05.
Article in English | MEDLINE | ID: covidwho-1854923
ABSTRACT
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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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2022 Document Type: Article Affiliation country: Journal.pcbi.1010042

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Topics: Vaccines Limits: Humans Language: English Journal: PLoS Comput Biol Journal subject: Biology / Medical Informatics Year: 2022 Document Type: Article Affiliation country: Journal.pcbi.1010042