Evidence map›Paper›PMID 33961878›Full record

ArticleMathematical biosciences2021

COVID-19 optimal vaccination policies: A modeling study on efficacy, natural and vaccine-induced immunity responses.

Manuel Adrian Acuña-Zegarra, Saúl Díaz-Infante, David Baca-Carrasco, Daniel Olmos-Liceaga

Open access · greenAbstract read
In one paragraph

Article in Mathematical biosciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
10.0field-weighted citation impact, top 1% 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

39 citing papers in PubMed, 1 synthesis or guideline pooled it, 127 citations in OpenAlex.

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  20. COVID-19 vaccination challenges: A mini-review.Human vaccines & immunotherapeutics · 2022
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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

4 authors at 2 institutions in 1 country.

Manuel Adrian Acuña-ZegarraDepartamento de Matemáticas, Universidad de Sonora, Blvd. Luis Encinas y Rosales S/N, Hermosillo, Col. Centro, Sonora, C.P. 83000, Mexico. Electronic address: adrian.acuna@unison.mx.
Saúl Díaz-InfanteCONACYT-Universidad de Sonora, Departamento de Matemáticas, Blvd. Luis Encinas y Rosales S/N, Hermosillo, Col. Centro, Sonora, C.P. 83000, Mexico. Electronic address: saul.diazinfante@unison.mx.
David Baca-CarrascoDepartamento de Matemáticas, Instituto Tecnológico de Sonora, 5 de Febrero 818 Sur, Col. Centro, Ciudad Obregón, Sonora, C.P. 85000, Mexico. Electronic address: david.baca@itson.edu.mx.
Daniel Olmos-LiceagaDepartamento de Matemáticas, Universidad de Sonora, Blvd. Luis Encinas y Rosales S/N, Hermosillo, Col. Centro, Sonora, C.P. 83000, Mexico. Electronic address: daniel.olmos@unison.mx.
Universidad de Sonora · MXSonora Institute of Technology · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

About a year into the pandemic, COVID-19 accumulates more than two million deaths worldwide. Despite non-pharmaceutical interventions such as social distance, mask-wearing, and restrictive lockdown, the daily confirmed cases remain growing. Vaccine developments from Pfizer, Moderna, and Gamaleya Institute reach more than 90% efficacy and sustain the vaccination campaigns in multiple countries. However, natural and vaccine-induced immunity responses remain poorly understood. There are great expectations, but the new SARS-CoV-2 variants demand to inquire if the vaccines will be highly protective or induce permanent immunity. Further, in the first quarter of 2021, vaccine supply is scarce. Consequently, some countries that are applying the Pfizer vaccine will delay its second required dose. Likewise, logistic supply, economic and political implications impose a set of grand challenges to develop vaccination policies. Therefore, health decision-makers require tools to evaluate hypothetical scenarios and evaluate admissible responses. Following some of the WHO-SAGE recommendations, we formulate an optimal control problem with mixed constraints to describe vaccination schedules. Our solution identifies vaccination policies that minimize the burden of COVID-19 quantified by the number of disability-adjusted years of life lost. These optimal policies ensure the vaccination coverage of a prescribed population fraction in a given time horizon and preserve hospitalization occupancy below a risk level. We explore "via simulation" plausible scenarios regarding efficacy, coverage, vaccine-induced, and natural immunity. Our simulations suggest that response regarding vaccine-induced immunity and reinfection periods would play a dominant role in mitigating COVID-19.

Indexed as

Mass VaccinationModels, TheoreticalCOVID-19COVID-19 VaccinesHumansOutcome and Process Assessment, Health CareCOVID-19 VaccinesCOVID-19DALYsNatural immunityOptimal controlReinfectionVaccination policyVaccine efficacyVaccine-induced immunityVaccine profileWHO-SAGE

Identifiers

PMID33961878
PMCPMC8095066
OpenAlexW3158778663

What OpenQuestion holds

Textmetadata
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.