Evidence map›Paper›PMID 41285435›Full record

ArticleBMJ global health2025

Vaccine selection strategies and their implications for individual versus population well-being.

Neil G Bennett, Maddalena Ferranna, Xiaofan Liu, David E Bloom

Abstract read
In one paragraph

Article in BMJ global health, 2025. 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

4 authors.

Neil G BennettCUNY Institute for Demographic Research, City University of New York, New York, New York, USA ferranna@usc.edu neil.bennett@baruch.cuny.edu.
Maddalena FerrannaDepartment of Pharmaceutical and Health Economics, University of Southern California, Los Angeles, California, USA ferranna@usc.edu neil.bennett@baruch.cuny.edu.ORCID 0000-0002-3892-8301
Xiaofan LiuDepartment of Pharmaceutical and Health Economics, University of Southern California, Los Angeles, California, USA.
David E BloomDepartment of Global Health and Population, Harvard TH Chan School of Public Health, Boston, Massachusetts, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionEarly constraints on vaccine supply during the COVID-19 pandemic prompted many public health leaders to recommend taking the first vaccine available, though many individuals chose to wait for a 'more effective' vaccine. This indicates a potential tension between the vaccination strategy that individuals find in their own best interest and the one that maximises population well-being.

methodsWe integrate a mathematical epidemiological model and an economic decision-making model to determine the conditions under which rational and self-interested individuals opt to wait for a more effective vaccine instead of taking the one readily available and whether their choices align with what is optimal from a population-level perspective. We consider different assumptions about the characteristics of the available vaccines and the severity of the pandemic, and we investigate the population health consequences if individuals stray from the vaccination strategy that best promotes population well-being.

resultsTaking the first vaccine available is not always optimal from a population-level perspective, but uncertainty about the characteristics of a subsequent vaccine increases the likelihood that this is indeed in the best interest of the population as a whole. However, protection offered by the vaccination of others may induce a greater proportion of rational and self-interested individuals to wait for the more effective vaccine than what would be optimal from a population-level perspective. If individuals decide to follow their own best interests, more people will end up waiting for the more effective vaccine, resulting in more infections and deaths during the waiting period.

conclusionsOur results will help policymakers facing future pandemics to craft recommendations that reduce disease transmission and save lives when early vaccines may be less effective than future vaccines.

Indexed as

COVID-19COVID-19 VaccinesVaccinationDecision MakingHumansPandemicsSARS-CoV-2COVID-19 VaccinesDecision MakingGlobal HealthHealth economicsMathematical modellingVaccines

Identifiers

PMID41285435
PMCPMC12645640

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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.