Evidence map›Paper›PMID 41654706›Full record

ArticleBMC infectious diseases2026

Forecasting and quantifying the role of vaccination strategies in the 2025 Texas measles outbreak: a modeling and time series analysis approach.

Chidozie W Chukwu

Abstract read
In one paragraph

Article in BMC infectious diseases, 2026. 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.

  1. Article
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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

1 author.

Chidozie W ChukwuDepartment of Mathematical Sciences, Georgia Southern University, Street, Statesboro, GA, 30460, USA. wiliam.chukwu@gmail.com.ORCID http://orcid.org/0000-0002-2780-5357

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we present a novel compartmental model to capture the transmission dynamics of measles, incorporating both single- and double-dose vaccination strategies. The model accounts for differential vaccine efficacies between partially and fully vaccinated individuals, providing a more realistic representation of population immunity. To quantify and forecast the future trajectory of measles in Texas, we calibrated our model using the 2025 measles outbreak data from Texas, USA, from January 20 to May 27, 2025. In addition, we employed time series forecasting approaches, Facebook Prophet and Gated Recurrent Units (GRU), to predict daily new measles cases. Results from the forecasting analysis reveal that the Prophet model outperformed the GRU model based on standard performance metrics. Both models suggest that measles will persist in Texas with an estimated average of 1-2 (95% CI, 1-2 ), daily new cases per day until August 30, 2025, unless additional public health interventions are implemented. Our findings highlight the importance of achieving and maintaining high vaccination coverage to prevent future outbreaks and mitigate the long-term risk of endemic measles. This study provides valuable insights for policymakers and health authorities aiming to strengthen measles control strategies in both endemic and non-endemic regions of Texas, USA.Clinical trialNot applicable.

Indexed as

Disease OutbreaksMeaslesMeasles VaccineVaccinationEpidemiological ModelsForecastingHumansTexasVaccination CoverageMeasles VaccineDynamical resultsMeasles ForecastingNumerical simulationsPredictionVaccination strategies

Identifiers

PMID41654706
PMCPMC12977517

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.