Department of Bioenvironmental Systems Engineering, National Taiwan University, Taipei, Taiwan, ROC.
Epidemiol Infect. 2014 Feb;142(2):358-70. doi: 10.1017/S0950268813001040. Epub 2013 May 16.
Understanding how seasonality shapes the dynamics of tuberculosis (TB) is essential in determining risks of transmission and drug resistance in (sub)tropical regions. We developed a relative fitness-based multidrug-resistant (MDR) TB model incorporated with seasonality and a probabilistic assessment model to assess infection risk in Taiwan regions. The model accurately captures the seasonal transmission and population dynamics of TB incidence during 2006-2008 and MDR TB in high TB burden areas during 2006-2010 in Taiwan. There is ~3% probability of having exceeded 50% of the population infected attributed to MDR TB. Our model not only provides insight into the understanding of the interactions between seasonal dynamics of TB and environmental factors but is also capable of predicting the seasonal patterns of TB incidence associated with MDR TB infection risk. A better understanding of the mechanisms of TB seasonality will be critical in predicting the impact of public control programmes.
了解季节性如何影响结核病(TB)的动态对于确定(亚)热带地区的传播和耐药风险至关重要。我们开发了一个基于相对适应性的耐多药(MDR)TB 模型,该模型结合了季节性和概率评估模型,以评估台湾地区的感染风险。该模型准确地捕捉了 2006-2008 年期间 TB 发病率的季节性传播和人群动态,以及 2006-2010 年期间高 TB 负担地区的 MDR TB。有~3%的可能性是由于 MDR TB 导致超过 50%的人口感染。我们的模型不仅提供了对 TB 季节性动态与环境因素之间相互作用的深入了解,还能够预测与 MDR TB 感染风险相关的 TB 发病率的季节性模式。更好地了解 TB 季节性的机制将对预测公共控制计划的影响至关重要。