Department of Biochemistry, Stellenbosch University, Private Bag X1, Matieland, 7602, Stellenbosch, South Africa.
Molecular Cell Physiology, Vrije Universiteit, De Boelelaan 1087, 1081 HV, Amsterdam, The Netherlands.
BMC Bioinformatics. 2021 Jul 24;22(1):384. doi: 10.1186/s12859-021-04289-z.
The fidelity and reliability of disease model predictions depend on accurate and precise descriptions of processes and determination of parameters. Various models exist to describe within-host dynamics during malaria infection but there is a shortage of clinical data that can be used to quantitatively validate them and establish confidence in their predictions. In addition, model parameters often contain a degree of uncertainty and show variations between individuals, potentially undermining the reliability of model predictions. In this study models were reproduced and analysed by means of robustness, uncertainty, local sensitivity and local sensitivity robustness analysis to establish confidence in their predictions.
Components of the immune system are responsible for the most uncertainty in model outputs, while disease associated variables showed the greatest sensitivity for these components. All models showed a comparable degree of robustness but displayed different ranges in their predictions. In these different ranges, sensitivities were well-preserved in three of the four models.
Analyses of the effects of parameter variations in models can provide a comparative tool for the evaluation of model predictions. In addition, it can assist in uncovering model weak points and, in the case of disease models, be used to identify possible points for therapeutic intervention.
疾病模型预测的保真度和可靠性取决于对过程的准确和精确描述以及参数的确定。有各种模型可用于描述疟疾感染期间的宿主内动态，但缺乏可用于对其进行定量验证并建立对其预测的信心的临床数据。此外，模型参数通常包含一定程度的不确定性，并在个体之间存在差异，这可能会破坏模型预测的可靠性。在这项研究中，通过稳健性、不确定性、局部敏感性和局部敏感性稳健性分析来重现和分析模型，以建立对其预测的信心。
免疫系统的各个组成部分是模型输出中不确定性最大的因素，而与疾病相关的变量则对这些成分表现出最大的敏感性。所有模型都显示出相当程度的稳健性，但在预测方面显示出不同的范围。在这些不同的范围内，三个模型中的两个保持了良好的敏感性。
对模型中参数变化的影响进行分析，可以为模型预测的评估提供一种比较工具。此外，它还有助于发现模型的弱点，并且在疾病模型的情况下，可用于确定可能的治疗干预点。
