Department of Preventive and Social Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
Center for Safety, Health and Environment of Chulalongkorn University, Bangkok, Thailand.
PLoS One. 2024 Jul 19;19(7):e0305264. doi: 10.1371/journal.pone.0305264. eCollection 2024.
This study aimed to assess and compare the probability of tuberculosis (TB) transmission based on five dynamic models: the Wells-Riley equation, two Rudnick & Milton-proposed models based on air changes per hour (ACH) and liters per second per person (L/s/p), the model proposed by Issarow et al, and the Applied Susceptible-Exposed-Infected-Recovered (SEIR) TB transmission model. This study also aimed to determine the impact of model parameters on such probabilities in three Thai prisons. A cross-sectional study was conducted using data from 985 prison cells. The TB transmission probability for each cell was calculated using parameters relevant to the specific model formula, and the magnitude of the model agreement was examined by Spearman's rank correlation and Bland-Altman plot. Subsequently, a multiple linear regression analysis was conducted to investigate the influence of each model parameter on the estimated probability. Results revealed that the median (Quartiles 1 and 3) of TB transmission probability among these cells was 0.052 (0.017, 0.180). Compared with the pioneered Wells-Riley's model, the remaining models projected discrepant TB transmission probability from less to more commensurate to the degree of model modification from the pioneered model as follows: Rudnick & Milton (ACH), Issarow et al., and Rudnick & Milton (L/s/p), and the applied SEIR models. The ventilation rate and number of infectious TB patients in each cell or zone had the greatest impact on the estimated TB transmission probability in most models. Additionally, the number of inmates in each cell, the area per person in square meters, and the inmate turnover rate were identified as high-impact parameters in the applied SEIR model. All stakeholders must urgently address these influential parameters to reduce TB transmission in prisons. Moreover, further studies are required to determine their relative validity in accurately predicting TB incidence in prison settings.
本研究旨在评估和比较基于五个动态模型的结核病（TB）传播概率：Wells-Riley 方程、基于每小时空气交换次数（ACH）和每人每秒升数（L/s/p）的两个 Rudnick & Milton 提出的模型、Issarow 等人提出的模型，以及应用的易感-暴露-感染-恢复（SEIR）TB 传播模型。本研究还旨在确定模型参数对泰国三个监狱中这些概率的影响。采用来自 985 个牢房的数据进行了一项横断面研究。使用与特定模型公式相关的参数计算每个牢房的 TB 传播概率，并通过 Spearman 等级相关和 Bland-Altman 图检查模型一致性的大小。随后，进行了多元线性回归分析，以研究每个模型参数对估计概率的影响。结果显示，这些牢房中 TB 传播概率的中位数（第 1 和第 3 四分位数）为 0.052（0.017，0.180）。与开创性的 Wells-Riley 模型相比，剩余模型预测的 TB 传播概率从较少到更符合从开创性模型修改的程度，如下所示：Rudnick & Milton（ACH）、Issarow 等人和 Rudnick & Milton（L/s/p），以及应用的 SEIR 模型。每个牢房或区域的通风率和传染性结核患者人数对大多数模型中的估计 TB 传播概率影响最大。此外，每个牢房的囚犯人数、每人平方米面积和囚犯周转率被确定为应用 SEIR 模型中的高影响参数。所有利益相关者必须紧急解决这些有影响力的参数，以减少监狱中的 TB 传播。此外，还需要进一步研究以确定它们在准确预测监狱环境中的 TB 发病率方面的相对有效性。
