Mathematics Institute, University of Warwick, Coventry CV4 7AL, UK.
Zeeman Institute (SBIDER), University of Warwick, Coventry CV4 7AL, UK.
J R Soc Interface. 2021 Oct;18(183):20210419. doi: 10.1098/rsif.2021.0419. Epub 2021 Oct 6.
Stochastic methods for modelling disease dynamics enable the direct computation of the probability of elimination of transmission. For the low-prevalence disease of human African trypanosomiasis (gHAT), we develop a new mechanistic model for gHAT infection that determines the full probability distribution of the gHAT infection using Kolmogorov forward equations. The methodology allows the analytical investigation of the probabilities of gHAT elimination in the spatially connected villages of different prevalence health zones of the Democratic Republic of Congo, and captures the uncertainty using exact methods. Our method provides a more realistic approach to scaling the probability of elimination of infection between single villages and much larger regions, and provides results comparable to established models without the requirement of detailed infection structure. The novel flexibility allows the interventions in the model to be implemented specific to each village, and this introduces the framework to consider the possible future strategies of test-and-treat or direct treatment of individuals living in villages where cases have been found, using a new drug.
用于模拟疾病动态的随机方法能够直接计算出消除传播的概率。对于人类非洲锥虫病（gHAT）这种低流行疾病，我们开发了一种新的 gHAT 感染机制模型，该模型使用柯尔莫哥洛夫向前方程确定了 gHAT 感染的完整概率分布。该方法允许使用精确方法分析刚果民主共和国不同流行健康区的空间连接村庄中消除 gHAT 的概率，并且利用精确方法捕捉不确定性。我们的方法为在单个村庄和更大的区域之间消除感染的概率提供了一种更现实的方法，并且提供了与没有详细感染结构的既定模型可比的结果。新颖的灵活性允许针对每个村庄具体实施模型中的干预措施，并且这为使用新药考虑在已发现病例的村庄中对个体进行检测和治疗或直接治疗的可能未来策略引入了框架。
