ArticleStatistics in medicine2019
Estimation and prediction for a mechanistic model of measles transmission using particle filtering and maximum likelihood estimation.
Article in Statistics in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- A coupled disease-misinformation model of measles transmission in the Canadian context.Infectious Disease Modelling · 2026Article
- Bridging Traditional Modeling and Artificial Intelligence in Measles Epidemiology: Methods, Applications, and Future Directions-A Narrative Review.Journal of clinical medicine · 2026Review
- Estimating the basic reproduction number of measles in low-and middle-income settings using 172 seroprevalence studies: A modelling approach.PLOS global public health · 2026Article
- Factors determining the overlap between recipients of the first and second dose of measles vaccine in nineteen surveys.Scientific reports · 2025Article
- Progress Toward Measles Elimination - Worldwide, 2000-2023.MMWR. Morbidity and mortality weekly report · 2024Article
- Progress towards Measles and Rubella Elimination in the South-East Asia Region-2013-2023.Vaccines · 2024Review
- Evaluating Scope and Bias of Population-Level Measles Serosurveys: A Systematized Review and Bias Assessment.Vaccines · 2024Review
- Contribution of vaccination to improved survival and health: modelling 50 years of the Expanded Programme on Immunization.Lancet (London, England) · 2024Article
- Analysis of the yearly transition function in measles disease modeling.Statistics in medicine · 2024Article
- Progress Toward Measles Elimination - Worldwide, 2000-2022.MMWR. Morbidity and mortality weekly report · 2023Article
- Measles and rubella elimination: protecting children through immunization in South-East Asia Region (SEAR).The Lancet regional health. Southeast Asia · 2023Review
- Progress Toward Measles Elimination - African Region, 2017-2021.MMWR. Morbidity and mortality weekly report · 2023Article
- Progress Toward Regional Measles Elimination - Worldwide, 2000-2021.MMWR. Morbidity and mortality weekly report · 2022Article
- Differential health impact of intervention programs for time-varying disease risk: a measles vaccination modeling study.BMC medicine · 2022Article
- Progress Toward Regional Measles Elimination - Worldwide, 2000-2020.MMWR. Morbidity and mortality weekly report · 2021Article
- Lives saved with vaccination for 10 pathogens across 112 countries in a pre-COVID-19 world.eLife · 2021Article
- Article
- Challenges in forming inferences from limited data: a case study of malaria parasite maturation.Journal of the Royal Society, Interface · 2021Article
- Research Progress on the Early Monitoring of Pine Wilt Disease Using Hyperspectral Techniques.Sensors (Basel, Switzerland) · 2020Review
- Estimation and prediction for a mechanistic model of measles transmission using particle filtering and maximum likelihood estimation.Statistics in medicine · 2019Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Disease incidence reported directly within health systems frequently reflects a partial observation relative to the true incidence in the population. State-space models present a general framework for inferring both the dynamics of infectious disease processes and the unobserved burden of disease in the population. Here, we present a state-space model of measles transmission and vaccine-based interventions at the country-level and a particle filter-based estimation procedure. Our dynamic transmission model builds on previous work by incorporating population age-structure to allow explicit representation of age-targeted vaccine interventions. We illustrate the performance of estimators of model parameters and predictions of unobserved states on simulated data from two dynamic models: one on the annual time-scale of observations and one on the biweekly time-scale of the epidemiological dynamics. We show that our model results in approximately unbiased estimates of unobserved burden and the underreporting rate. We further illustrate the performance of the fitted model for prediction of future disease burden in the next one to 15 years.
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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.