当前位置: X-MOL 学术Proc. Natl. Acad. Sci. U.S.A. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Data-driven model for the assessment of Mycobacterium tuberculosis transmission in evolving demographic structures [Medical Sciences]
Proceedings of the National Academy of Sciences of the United States of America ( IF 9.4 ) Pub Date : 2018-04-03 00:00:00 , DOI: 10.1073/pnas.1720606115
Sergio Arregui 1, 2 , María José Iglesias 3, 4 , Sofía Samper 4, 5 , Dessislava Marinova 3, 4 , Carlos Martin 3, 4, 6 , Joaquín Sanz 7, 8 , Yamir Moreno 1, 2, 9
Affiliation  

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.



中文翻译:


用于评估不断变化的人口结构中结核分枝杆菌传播的数据驱动模型[医学科学]



就结核病 (TB) 而言,流行病模型进行定量稳健预测的能力受到多重障碍的限制。其中,了解疾病流行病学与人口年龄结构之间的复杂关系被认为是最相关的问题之一。结核病动态在多种方面取决于年龄,其中一些传统上在文献中被简化。这就是不同年龄层之间接触强度存在异质性的情况,这种异质性对于所有空气传播疾病来说都很常见,但在结核病病例中通常仍然被忽视。此外,虽然许多国家的人口结构正在迅速老龄化,但在对结核病传播进行建模时普遍忽视了人口动态。在这项工作中,我们提出了一种结核病传播模型,该模型结合了特定国家的人口前景和围绕结核病动态的数据驱动描述的经验接触数据。使用我们的模型,我们发现,在纳入人口动态之后,预计未来几十年世界上受该疾病影响最严重的地区的负担水平将会增加。同样,我们表明,考虑不同年龄层个体之间的现实接触模式会重塑模型再现的传播模式,这一结果对设计以年龄为重点的流行病学干预措施具有潜在影响。

更新日期:2018-04-04
down
wechat
bug