Uncovering the effects of heterogeneity and parameter sensitivity on within-host dynamics of disease: malaria as a case study

Shade Horn, Jacky L. Snoep, David D. van Niekerk*

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review


Background: 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.

Results: 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.

Conclusion: 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.

Original languageEnglish
Article number384
Pages (from-to)1-21
Number of pages21
JournalBMC Bioinformatics
Early online date24 Jul 2021
Publication statusPublished - Dec 2021

Bibliographical note

Funding Information:
We acknowledge the financial assistance from the DST/NRF in South Africa, particularly for funding the SARChI initiative (Jacky Snoep NRF-SARCHI-82813), and the CSUR (David van Niekerk ID 116298) and Innovation Doctoral Scholarships (Shade Horn ID 121296) programmes.

Publisher Copyright:
© 2021, The Author(s).

Copyright 2021 Elsevier B.V., All rights reserved.


  • Malaria
  • Modelling
  • Sensitivity analysis
  • Within-host


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