Evidence map›Paper›PMID 40333206›Full record

ArticleVaccines2025

Using Measles Outbreaks to Identify Under-Resourced Health Systems in Low- and Middle-Income Countries: A Predictive Model.

Gabrielle P D MacKechnie, Milena Dalton, Dominic Delport, Stefanie Vaccher

Abstract read
In one paragraph

Article in Vaccines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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.

Gabrielle P D MacKechnieBurnet Institute, Melbourne, VIC 3004, Australia.ORCID 0009-0009-0778-5596
Milena DaltonBurnet Institute, Melbourne, VIC 3004, Australia.ORCID 0000-0001-8479-1855
Dominic DelportBurnet Institute, Melbourne, VIC 3004, Australia.
Stefanie VaccherBurnet Institute, Melbourne, VIC 3004, Australia.ORCID 0000-0001-5170-4110

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

objectivesMeasles is a vaccine-preventable disease with a high level of transmissibility. Outbreaks of measles continue globally, with gaps in healthcare and immunisation resulting in pockets of susceptible individuals. Measles outbreaks have been proposed as a "canary in the coal mine" of under-resourced health systems, uncovering broader system weaknesses. We aim to understand whether under-resourced health systems are associated with increased odds of large measles outbreaks in low- and middle-income countries (LMICs).

methodsWe used an ecological study design to identify measles outbreaks that occurred in LMICs between 2010 and 2020. Health systems were represented using a set of health system indicators for the corresponding outbreak country, guided by the World Health Organization's building blocks of health systems framework. These indicators were: the proportion of births delivered in a health facility, the number of nurses and midwives per 10,000 population, and domestic general government health expenditure per capita in USD. We analysed the associations using a predictive model and assessed the accuracy of this model.

resultsThe analysis included 78 outbreaks. We found an absence of any association between the included health system indicators and large measles outbreaks. When testing predictive accuracy, the model obtained a Brier score of 0.21, which indicates that the model is not informative in predicting large measles outbreaks. We found that missing data did not affect the results of the model.

conclusionsLarge measles outbreaks were not able to be used to identify under-resourced health systems in LMICs. However, further research is required to understand whether this association may exist when taking other factors, including smaller outbreaks, into account.

Indexed as

disease outbreaksepidemicshealthcarehealth serviceshealth systemsmeasles

Identifiers

PMID40333206
PMCPMC12031049

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