Evidence map›Paper›PMID 35584133›Full record

ArticlePLoS computational biology2022

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

Thomas E Valles, Hannah Shoenhard, Joseph Zinski, Sarah Trick, Mason A Porter, Michael R Lindstrom

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Thomas E VallesDepartment of Mathematics, University of California, San Diego, San Diego, California, United States of America.
Hannah ShoenhardDepartment of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0002-9085-9139
Joseph ZinskiDepartment of Cell and Developmental Biology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.ORCID 0000-0002-5120-5386
Sarah TrickAssistant Editor at tvo.org (TVOntario), Toronto, Ontario, Canada.
Mason A PorterDepartment of Mathematics, University of California, Los Angeles, Los Angeles, California, United States of America.
Michael R LindstromDepartment of Mathematics, University of California, Los Angeles, Los Angeles, California, United States of America.ORCID 0000-0002-2841-1691
University of California, Los Angeles · USUniversity of Pennsylvania · USSanta Fe Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19Activities of Daily LivingCaregiversCommunicable Disease ControlHumans

Identifiers

PMID35584133
PMCPMC9232173
OpenAlexW3202901190

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.