Evidence map›Paper›PMID 36301932›Full record

ArticlePloS one2022

Community structured model for vaccine strategies to control COVID19 spread: A mathematical study.

Elena Aruffo, Pei Yuan, Yi Tan, Evgenia Gatov, Effie Gournis, Sarah Collier, Nick Ogden, Jacques Bélair, Huaiping Zhu

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

  1. Pooled it
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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

9 authors at 3 institutions in 1 country.

Elena AruffoCentre for Diseases Modeling (CDM), York University, Toronto, Ontario, Canada.
Pei YuanCentre for Diseases Modeling (CDM), York University, Toronto, Ontario, Canada.
Yi TanCentre for Diseases Modeling (CDM), York University, Toronto, Ontario, Canada.
Evgenia GatovToronto Public Health, Toronto, Ontario, Canada.
Effie GournisToronto Public Health, Toronto, Ontario, Canada.
Sarah CollierToronto Public Health, Toronto, Ontario, Canada.
Nick OgdenPublic Health Agency of Canada, Ottawa, Ontario, Canada.
Jacques BélairCentre for Diseases Modeling (CDM), York University, Toronto, Ontario, Canada.
Huaiping ZhuCentre for Diseases Modeling (CDM), York University, Toronto, Ontario, Canada.ORCID 0000-0003-2718-595X
York University · CAToronto Public Health · CAPublic Health Agency of Canada · CA

Funding

CIHR
6 · The paper itself

Abstract

Initial efforts to mitigate the COVID-19 pandemic have relied heavily on non-pharmaceutical interventions (NPIs), including physical distancing, hand hygiene, and mask-wearing. However, an effective vaccine is essential to containing the spread of the virus. We developed a compartmental model to examine different vaccine strategies for controlling the spread of COVID-19. Our framework accounts for testing rates, test-turnaround times, and vaccination waning immunity. Using reported case data from the city of Toronto, Canada between Mar-Dec, 2020 we defined epidemic phases of infection using contact rates as well as the probability of transmission upon contact. We investigated the impact of vaccine distribution by comparing different permutations of waning immunity, vaccine coverage and efficacy throughout various stages of NPI's relaxation in terms of cases and deaths. The basic reproduction number is also studied. We observed that widespread vaccine coverage substantially reduced the number of cases and deaths. Under phases with high transmission, an early or late reopening will result in new resurgence of the infection, even with the highest coverage. On the other hand, under phases with lower transmission, 60% of coverage is enough to prevent new infections. Our analysis of R0 showed that the basic reproduction number is reduced by decreasing the tests turnaround time and transmission in the household. While we found that household transmission can decrease following the introduction of a vaccine, public health efforts to reduce test turnaround times remain important for virus containment.

Indexed as

COVID-19VaccinesCommunicable Disease ControlHumansPandemicsSARS-CoV-2Vaccines

Identifiers

PMID36301932
PMCPMC9612529
OpenAlexW4307410401

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.