70330 20250127144948.0 doi 10.1073/pnas.1720606115 sideral 105911 ART-2018-105911 eng Arregui, S. Universidad de Zaragoza (orcid)0000-0003-3259-0933 Data-driven model for the assessment of mycobacterium tuberculosis transmission in evolving demographic structures 2018 Access copy available to the general public Unrestricted 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. info:eu-repo/grantAgreement/EC/FP7/317532/EU/Foundational Research on MULTIlevel comPLEX networks and systems/MULTIPLEX info:eu-repo/grantAgreement/EC/H2020/643381/EU/TBVAC2020; Advancing novel and promising TB vaccine candidates from discovery to preclinical and early clinical development/TBVAC2020 This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 643381-TBVAC2020 info:eu-repo/grantAgreement/ES/ISCIII/FIS/PI15-0317 info:eu-repo/grantAgreement/ES/MINECO/BIO2014-52580P info:eu-repo/grantAgreement/ES/MINECO/FIS2014-55867-P info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 9.58 2018 MULTIDISCIPLINARY SCIENCES 6 / 68 = 0.088 2018 Q1 T1 5.601 2018 Multidisciplinary 2018 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Iglesias, M.J. Universidad de Zaragoza (orcid)0000-0003-2266-8602 Samper, S. Marinova, D. Universidad de Zaragoza (orcid)0000-0001-8644-120X Martin, C. Universidad de Zaragoza (orcid)0000-0003-2993-5478 Sanz, J. Moreno, Y. Universidad de Zaragoza (orcid)0000-0002-0895-1893 1008 630 Universidad de Zaragoza Dpto. Microb.Med.Pr.,Sal.Públ. Área Microbiología 1008 X Universidad de Zaragoza Dpto. Microb.Med.Pr.,Sal.Públ. Proy. investigación HQA 2004 405 Universidad de Zaragoza Dpto. Física Teórica Área Física Teórica 1008 615 Universidad de Zaragoza Dpto. Microb.Med.Pr.,Sal.Públ. Área Medic.Prevent.Salud Públ. 115, 14 (2018), E3238-E3245 Proc. Natl. Acad. Sci. Proceedings of the National Academy of Sciences of the United States of America 0027-8424 1295126 http://zaguan.unizar.es/record/70330/files/texto_completo.pdf Versión publicada 144093 http://zaguan.unizar.es/record/70330/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:70330 articulos driver 2025-01-27-14:45:24 ARTICLE