Evidence map›Paper›PMID 35197495›Full record

ArticleScientific reports2022

Risk factor targeting for vaccine prioritization during the COVID-19 pandemic.

Lloyd A C Chapman, Poojan Shukla, Isabel Rodríguez-Barraquer, Priya B Shete, Tomás M León, Kirsten Bibbins-Domingo, George W Rutherford, Robert Schechter, Nathan C Lo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 pooled it
–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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  18. A novel mathematical model for prioritization of individuals to receive vaccine considering governmental health protocols.The European journal of health economics : HEPAC : health economics in prevention and care · 2023
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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.

Lloyd A C ChapmanDivision of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco, San Francisco, CA, 94110, USA. lloyd.chapman1@lshtm.ac.uk.
Poojan ShuklaDivision of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco, San Francisco, CA, 94110, USA.
Isabel Rodríguez-BarraquerDivision of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco, San Francisco, CA, 94110, USA.
Priya B SheteCoronavirus Sciences Branch, California Department of Public Health, Richmond, CA, USA.
Tomás M LeónCoronavirus Sciences Branch, California Department of Public Health, Richmond, CA, USA.
Kirsten Bibbins-DomingoDepartment of Medicine, University of California, San Francisco, San Francisco, CA, 94110, USA.
George W RutherfordDepartment of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
Robert SchechterImmunization Branch, California Department of Public Health, Richmond, CA, USA.
Nathan C LoDivision of HIV, Infectious Diseases, and Global Medicine, University of California, San Francisco, San Francisco, CA, 94110, USA. nathan.lo@ucsf.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A key public health question during any disease outbreak when limited vaccine is available is who should be prioritized for early vaccination. Most vaccine prioritization analyses only consider variation in risk of infection and death by a single risk factor, such as age. We provide a more granular approach with stratification by demographics, risk factors, and location. We use this approach to compare the impact of different COVID-19 vaccine prioritization strategies on COVID-19 cases, deaths and disability-adjusted life years (DALYs) over the first 6 months of vaccine rollout, using California as a case example. We estimate the proportion of cases, deaths and DALYs averted relative to no vaccination for strategies prioritizing vaccination by a single risk factor and by multiple risk factors (e.g. age, location). When targeting by a single risk factor, we find that age-based targeting averts the most deaths (62% for 5 million individuals vaccinated) and DALYs (38%) and targeting essential workers averts the least deaths (31%) and DALYs (24%) over the first 6 months of rollout. However, targeting by two or more risk factors simultaneously averts up to 40% more DALYs. Our findings highlight the potential value of multiple-risk-factor targeting of vaccination against COVID-19 and other infectious diseases, but must be balanced with feasibility for policy.

Indexed as

COVID-19COVID-19 VaccinesVaccinationAdolescentAdultAgedCaliforniaDisability-Adjusted Life YearsFemaleHealth PrioritiesHumansMaleMiddle AgedPandemicsRisk FactorsSARS-CoV-2COVID-19 Vaccines

Identifiers

PMID35197495
PMCPMC8866501

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.