Porco T C, Blower S M
San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 710, San Francisco, California, 94102, USA.
Theor Popul Biol. 1998 Oct;54(2):117-32. doi: 10.1006/tpbi.1998.1366.
Previously we have formulated transmission models of untreated tuberculosis epidemics (Blower et al., Nature, Medicine 1 (1995), 815-821); in this paper, we present time-dependent uncertainty and sensitivity analyses in order to quantitatively understand the transmission dynamics of tuberculosis epidemics in the absence of treatment. The time-dependent uncertainty analysis enabled us to evaluate the variability in the epidemiological outcome variables of the model during the progression of a tuberculosis epidemic. Calculated values (from the uncertainty analysis) for the disease incidence, disease prevalence, and mortality rates were approximately consistent with historical data. The time-dependent sensitivity analysis revealed that only a few of the model's input parameters significantly affected the severity of a tuberculosis epidemic; these parameters were the disease reactivation rate, the fraction of infected individuals who develop tuberculosis soon after infection, the number of individuals that an infectious individual infects per year, the disease death rate, and the population recruitment rate. Our analysis demonstrates that it is possible to improve our understanding of the behavior of tuberculosis epidemics by applying time-dependent uncertainty and sensitivity analysis to a transmission model.
此前我们已经构建了未治疗肺结核流行病的传播模型（Blower等人，《自然》，《医学》1（1995），815 - 821）；在本文中，我们进行了随时间变化的不确定性和敏感性分析，以便定量理解未治疗情况下肺结核流行病的传播动态。随时间变化的不确定性分析使我们能够评估肺结核流行病发展过程中模型流行病学结果变量的变异性。疾病发病率、患病率和死亡率的计算值（来自不确定性分析）与历史数据大致相符。随时间变化的敏感性分析表明，模型中只有少数输入参数会显著影响肺结核流行病的严重程度；这些参数是疾病再激活率、感染后不久就患肺结核的感染个体比例、每个感染个体每年感染的个体数量、疾病死亡率和人口招募率。我们的分析表明，通过对传播模型应用随时间变化的不确定性和敏感性分析，有可能增进我们对肺结核流行病行为的理解。
