Ackley Sarah F, Lee Robyn S, Worden Lee, Zwick Erin, Porco Travis C, Behr Marcel A, Pepperell Caitlin S
Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
Proctor Foundation, University of California, San Francisco, CA, USA.
R Soc Open Sci. 2019 Mar 20;6(3):180999. doi: 10.1098/rsos.180999. eCollection 2019 Mar.
A recent study reported on a tuberculosis (TB) outbreak in a largely Inuit village. Among newly infected individuals, exposure to additional active cases was associated with an increasing probability of developing active disease within a year. Using binomial risk models, we evaluated two potential mechanisms by which multiple infections during the first year following initial infection could account for increasing disease risk with increasing exposures. In the , each infectious contact confers an independent risk of an infection, and infections contribute independently to active disease. In the , disease risk follows a sigmoidal function with small numbers of infectious contacts conferring a low risk of active disease and large numbers of contacts conferring a high risk. To determine the dynamic impact of reinfection during the early phase of infection, we performed simulations from a modified Reed-Frost model of TB dynamics following spread from an initial number of cases. We parametrized this model with the maximum-likelihood estimates from the reinfection and threshold models in addition to the observed distribution of exposures among new infections. We find that both models can plausibly account for the observed increase in disease risk with increasing infectious contacts, but the threshold model confers a better fit than a nested model without a threshold ( = 0.04). Our simulations indicate that multiple exposures to infectious individuals during this critical time period can lead to dramatic increases in outbreak size. In order to decrease TB burden in high-prevalence settings, it may be necessary to implement measures aimed at preventing repeated exposures, in addition to preventing primary infection.
最近一项研究报告了一个主要为因纽特人的村庄爆发的结核病疫情。在新感染的个体中，接触其他活动性病例与一年内发展为活动性疾病的概率增加有关。我们使用二项式风险模型评估了两种潜在机制，通过这两种机制，初次感染后第一年的多次感染可能导致随着接触增加疾病风险上升。在一种机制中，每次感染性接触都会带来独立的感染风险，且感染对活动性疾病的影响相互独立。在另一种机制中，疾病风险呈S形函数，少量感染性接触导致活动性疾病风险较低，而大量接触则导致高风险。为了确定感染早期再感染的动态影响，我们根据从初始病例传播后的结核病动态变化的改良里德 - 弗罗斯特模型进行了模拟。我们用再感染和阈值模型的最大似然估计值以及新感染中观察到的接触分布对该模型进行参数化。我们发现这两种模型都能合理地解释随着感染性接触增加观察到的疾病风险上升，但阈值模型比没有阈值的嵌套模型拟合得更好（P = 0.04）。我们的模拟表明，在这个关键时期多次接触感染性个体可能导致疫情规模急剧增加。为了降低高流行地区的结核病负担，除了预防初次感染外，可能还需要采取措施防止反复接触。
