Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 437

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Optimizing Influenza Vaccine Distribution

Medlock, Jan, Galvani, Alison P.·2009·Science

Abstract

Rethinking Vaccine Distribution: The distribution of vaccines is a complex issue lying at the intersection of public health, economics, and ethics and it cannot be decided in hindsight as an epidemic unfolds. Thus, mathematical modeling can be valuable for guiding policy, and Medlock and Galvani (p. 1705 , published online 20 August) present an analysis of how to distribute influenza vaccine among different age groups in a way that will minimize transmission. Scenarios were developed for different outcomes that tell us what happens, in terms of numbers of infections, mortality, and cost, when various cohorts are targeted for vaccination under different epidemic conditions, and compare 1918- and 1957-like epidemics. The scenarios could apply equally well to antiviral drug distribution. The conclusion is that the current recommendations for vaccine distribution from the U.S. Centers for Disease Control and Prevention may need to be revised to include age-related patterns of transmission to minimize the impact of epidemic influenza.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1126/science.1175570

Cites

28 of 28 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 28 references

Cited by

See all 437

Metadata

Authors
Medlock, J., & Galvani, A. P.
Venue
Science
Published
2009-09-25
Volume
325
Issue
5948
Pages
1705-1708
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2097289778
Cited by
437
References
28
FWCI
21.18
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Optimizing Influenza Vaccine Distribution. https://app.cochat.ai/papers/10.1126/science.1175570
The paper
Medlock, J., & Galvani, A. P. (2009). Optimizing Influenza Vaccine Distribution. Science. https://doi.org/10.1126/science.1175570

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.