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Record W4415151493 · doi:10.1186/s13062-025-00693-0

Measles and public health: an integrative approach

2025· article· en· W4415151493 on OpenAlexaboutno aff
Francesco Branda, Marta Giovanetti, Nicola Petrosillo, Mohamed Mustaf Ahmed, Maria Teresa Perra, Daria Sanna, Giancarlo Ceccarelli, Massimo Ciccozzi, Enrico Bucci, Fabio Scarpa

Bibliographic record

VenueBiology Direct · 2025
Typearticle
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMeaslesOutbreakEpidemiologyVaccinationPandemicTransmission (telecommunications)Public healthMeasles vaccine

Abstract

fetched live from OpenAlex

BACKGROUND: Measles, once considered under control in many high-income countries, has experienced a notable resurgence in recent years due to declining vaccination rates, increased vaccine hesitancy, and gaps in public health preparedness. This study provides an overview of the current measles outbreaks in two socio-culturally distinct realities, both facing a challenging epidemiological situation, i.e., the Region of the Americas and Italy, the European country most impacted after Romania. The aim is to understand transmission dynamics and identify factors contributing to outbreak severity. RESULTS: Epidemiological data show that Canada experienced an unprecedented increase in measles incidence, particularly in Ontario and Alberta, where spatial modelling revealed relative risks greater than 30 in high burden areas (i.e., the estimated likelihood of measles occurrence in these areas was more than 30 times higher than the national average, based on Bayesian spatial modeling). In Mexico, the epidemic was highly localised, with over 90% of cases and all but one death concentrated in the state of Chihuahua. In the United States, 89% of cases were linked to epidemic outbreaks, with Texas showing significant spatial clustering and daily growth rates of over 4% in high-risk counties. In Italy, the 2024 outbreak marked a significant increase in measles cases compared to previous years, primarily affecting unvaccinated individuals. Over 50% of those affected required hospitalization, and major urban regions such as Lazio and Lombardy experienced sustained transmission. An initial phase of exponential growth (66% monthly) was followed by a plateau, with no significant decline observed, underlining delays in containment and persistent immune deficiencies. From genetic point of view, the study revealed the predominance of genotype D8, known for sustained global circulation, suggesting a single transmission chain behind the recent outbreaks. Phylogenetic analysis showed no significant intra-genotypic diversification, suggesting that the outbreak likely originated from a single introduction event followed by rapid, localized transmission. This limited genetic variation is consistent with a short transmission window and the absence of strong evolutionary pressure. CONCLUSION: The outbreaks in the United States and Italy, despite differences in healthcare systems and sociopolitical contexts, reveal common underlying issues. In the U.S., the epidemic was characterized by clusters of unvaccinated individuals in certain communities, while Italy faced challenges due to gaps in routine immunization programs and delays in responding to the outbreak. Both outbreaks illustrate the devastating impact of under-vaccination, inadequate surveillance, and the spread of misinformation on public health. Our results contribute to a deeper understanding of the dynamics of measles recurrence, providing a solid basis for science-based prevention and control measures. Furthermore, the study emphasises the importance of continuous and integrated surveillance to detect emerging or divergent strains at an early stage. CLINICAL TRIAL NUMBER: Not applicable.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0100.006
Science and technology studies0.0020.010
Scholarly communication0.0110.009
Open science0.0020.010
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.362
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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