ArticleProceedings of the National Academy of Sciences of the United States of America2018
Data-driven model for the assessment of
Article in Proceedings of the National Academy of Sciences of the United States of America, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Incorporating human dynamic populations in models of infectious disease transmission: a systematic review.BMC infectious diseases · 2022Pooled it
- A Systematic Review of Social Contact Surveys to Inform Transmission Models of Close-contact Infections.Epidemiology (Cambridge, Mass.) · 2019Pooled it
- RNA vaccines: The dawn of a new age for tuberculosis?Human vaccines & immunotherapeutics · 2025Review
- Effect of population aging on pulmonary tuberculosis burden in Zhejiang Province, China: a population-based study.Frontiers in public health · 2025Article
- Model-based impact evaluation of new tuberculosis vaccines in aging populations under different modeling scenarios: the case of China.Frontiers in public health · 2024Article
- Addressing mechanism bias in model-based impact forecasts of new tuberculosis vaccines.Nature communications · 2023Article
- Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics.Nature communications · 2023Article
- An RNA-Based Vaccine Platform for Use againstVaccines · 2023Article
- Exploring human mixing patterns based on time use and social contact data and their implications for infectious disease transmission models.BMC infectious diseases · 2022Article
- Updating age-specific contact structures to match evolving demography in a dynamic mathematical model of tuberculosis vaccination.PLoS computational biology · 2022Article
- Changing Epidemiology of TB in Shandong, China Driven by Demographic Changes.Frontiers in medicine · 2022Article
- It Takes a Village: The Multifaceted Immune Response toFrontiers in immunology · 2022Review
- Modeling the impact of COVID-19 on future tuberculosis burden.Communications medicine · 2022Article
- Association between tuberculosis in men and social network structure in Kampala, Uganda.BMC infectious diseases · 2021Article
- Factors associated with localization of tuberculosis disease among patients in a high burden country: A health facility-based comparative study in Ethiopia.Journal of clinical tuberculosis and other mycobacterial diseases · 2021Article
- Close contact infection dynamics over time: insights from a second large-scale social contact survey in Flanders, Belgium, in 2010-2011.BMC infectious diseases · 2021Article
- Data-driven contact structures: From homogeneous mixing to multilayer networks.PLoS computational biology · 2020Article
- Bridging the gap between efficacy trials and model-based impact evaluation for new tuberculosis vaccines.Nature communications · 2019Article
- Estimating age-mixing patterns relevant for the transmission of airborne infections.Epidemics · 2019Article
- Article
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7 authors.
Funding
Abstract
In the case of tuberculosis (TB), the capabilities of epidemic models to produce quantitatively robust forecasts are limited by multiple hindrances. Among these, understanding the complex relationship between disease epidemiology and populations' age structure has been highlighted as one of the most relevant. TB dynamics depends on age in multiple ways, some of which are traditionally simplified in the literature. That is the case of the heterogeneities in contact intensity among different age strata that are common to all airborne diseases, but still typically neglected in the TB case. Furthermore, while demographic structures of many countries are rapidly aging, demographic dynamics are pervasively ignored when modeling TB spreading. In this work, we present a TB transmission model that incorporates country-specific demographic prospects and empirical contact data around a data-driven description of TB dynamics. Using our model, we find that the inclusion of demographic dynamics is followed by an increase in the burden levels predicted for the next decades in the areas of the world that are most hit by the disease today. Similarly, we show that considering realistic patterns of contacts among individuals in different age strata reshapes the transmission patterns reproduced by the models, a result with potential implications for the design of age-focused epidemiological interventions.
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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.