ReviewVaccine2020
Using models to shape measles control and elimination strategies in low- and middle-income countries: A review of recent applications.
Review in Vaccine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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.
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.
Who cites it
26 citing papers in PubMed, 48 citations in OpenAlex.
- Article
- Bridging Traditional Modeling and Artificial Intelligence in Measles Epidemiology: Methods, Applications, and Future Directions-A Narrative Review.Journal of clinical medicine · 2026Review
- Article
- Recent Advances in Strategies Against Measles Spread: Clinical and Epidemiological Aspects, Impact, Vaccine Innovations, and Sustainable Recommendations.TheScientificWorldJournal · 2026Review
- Investigating persistent measles dynamics associated with population immunity in Chad: a national secondary data model analysis from 2011 to 2025.IJID regions · 2025Article
- Prediction of subnational-level vaccination coverage estimates using routine surveillance data and survey data.Vaccine · 2025Article
- Measles in Canada: modelling outbreaks with variable vaccine coverage and interventions.BMC infectious diseases · 2025Article
- Concordance of coverage estimates from routine and survey data of measles second dose vaccine in Western Kenya.Frontiers in epidemiology · 2025Article
- Modelling the spatial variability and uncertainty for under-vaccination and zero-dose children in fragile settings.Scientific reports · 2024Article
- High-Resolution Geospatial Mapping of Zero-Dose and Underimmunized Children Following Nigeria's 2021 Multiple Indicator Cluster Survey/National Immunization Coverage Survey.The Journal of infectious diseases · 2024Article
- Possible Paths to Measles Eradication: Conceptual Frameworks, Strategies, and Tactics.Vaccines · 2024Review
- Optimal Timing Regularly Outperforms Higher Coverage in Preventative Measles Supplementary Immunization Campaigns.Vaccines · 2024Article
- Analysis of the yearly transition function in measles disease modeling.Statistics in medicine · 2024Article
- Fractional-Order Epidemic Model for Measles Infection.Scientifica · 2024Article
- Evaluating effective measles vaccine coverage in the Malaysian population accounting for between-dose correlation and vaccine efficacy.BMC public health · 2023Article
- Article
- Analysis of the different interventions scenario for programmatic measles control in Bangladesh: A modelling study.PloS one · 2023Article
- Measles seroprevalence in persons over one year of age in Chandigarh, India.Human vaccines & immunotherapeutics · 2022Article
- The Development and Distribution of the COVID-19 Vaccine.American journal of respiratory and critical care medicine · 2022Article
- Every Child on the Map: A Theory of Change Framework for Improving Childhood Immunization Coverage and Equity Using Geospatial Data and Technologies.Journal of medical Internet research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 8 institutions in 2 countries.
Funding
Abstract
After many decades of vaccination, measles epidemiology varies greatly between and within countries. National immunization programs are therefore encouraged to conduct regular situation analyses and to leverage models to adapt interventions to local needs. Here, we review applications of models to develop locally tailored interventions to support control and elimination efforts. In general, statistical and semi-mechanistic transmission models can be used to synthesize information from vaccination coverage, measles incidence, demographic, and/or serological data, offering a means to estimate the spatial and age-specific distribution of measles susceptibility. These estimates complete the picture provided by vaccination coverage alone, by accounting for natural immunity. Dynamic transmission models can then be used to evaluate the relative impact of candidate interventions for measles control and elimination and the expected future epidemiology. In most countries, models predict substantial numbers of susceptible individuals outside the age range of routine vaccination, which affects outbreak risk and necessitates additional intervention to achieve elimination. More effective use of models to inform both vaccination program planning and evaluation requires the development of training to enhance broader understanding of models and where feasible, building capacity for modelling in-country, pipelines for rapid evaluation of model predictions using surveillance data, and clear protocols for incorporating model results into decision-making.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.