Evidence map›Paper›PMID 34551000›Full record

ArticlePloS one2021

"Hot-spotting" to improve vaccine allocation by harnessing digital contact tracing technology: An application of percolation theory.

Mark D Penney, Yigit Yargic, Lee Smolin, Edward W Thommes, Madhur Anand, Chris T Bauch

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Mark D PenneyPerimeter Institute for Theoretical Physics, Waterloo, Ontario, Canada.ORCID 0000-0002-5883-1099
Yigit YargicPerimeter Institute for Theoretical Physics, Waterloo, Ontario, Canada.
Lee SmolinPerimeter Institute for Theoretical Physics, Waterloo, Ontario, Canada.
Edward W ThommesVaccine Epidemiology and Modeling, Sanofi Pasteur, Toronto, Ontario, Canada.
Madhur AnandSchool of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada.
Chris T BauchDepartment of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Vaccinating individuals with more exposure to others can be disproportionately effective, in theory, but identifying these individuals is difficult and has long prevented implementation of such strategies. Here, we propose how the technology underlying digital contact tracing could be harnessed to boost vaccine coverage among these individuals. In order to assess the impact of this "hot-spotting" proposal we model the spread of disease using percolation theory, a collection of analytical techniques from statistical physics. Furthermore, we introduce a novel measure which we call the efficiency, defined as the percentage decrease in the reproduction number per percentage of the population vaccinated. We find that optimal implementations of the proposal can achieve herd immunity with as little as half as many vaccine doses as a non-targeted strategy, and is attractive even for relatively low rates of app usage.

Indexed as

Contact TracingCOVID-19COVID-19 VaccinesHumansImmunity, HerdMass VaccinationMobile ApplicationsModels, StatisticalSARS-CoV-2COVID-19 Vaccines

Identifiers

PMID34551000
PMCPMC8457469

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.