Computational Modelling of malaria diagnostic test
Date Available
2018-05-10Type
datasetData Creator
Ryu, KyungsukStefan, Melanie
Fitzpatrick, Richard
Publisher
University of Edinburgh. Biomedical SciencesMetadata
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Citation
Ryu, Kyungsuk; Stefan, Melanie; Fitzpatrick, Richard. (2018). Computational Modelling of malaria diagnostic test, [dataset]. University of Edinburgh. Biomedical Sciences. https://doi.org/10.7488/ds/2347.Description
Early diagnosis of malaria is important for the prevention of malaria disease outbreak and providing an affected person with appropriate treatment early on. In malaria-endemic areas, where resources and access to health care are limited, the malaria rapid diagnostic test (mRDT) has widely been used because it is easy to use, cheap and fast. However, mRDT is prone to several limitations, such as inconsistent diagnostic specificity and sensitivity between different brands. Here, we build the first computational chemical kinetic model of mRDT which allows simulation of different parameter sets by using complex pathway simulator software (COPASI). Our model successfully reproduces in-vivo experimental results, confirming its validity. Using our model, we explore the principle of mRDT and demonstrate the potential for enhancing the diagnostic range of mRDT through parameter optimisation. Moreover, we use our model to investigate the prozone effect, the false negative response resulting from hyper-parasitaemia. This has previously been observed when using only the mRDT against Plasmodium histidine-rich protein-2 (pHRP-2) and not Plasmodium lactate dehydrogenase (pLDH). Our model can reproduce this result and is the first to provide a mechanistic explanation for why test differs in their susceptibility to the prozone effect. N.B. The COPAS software is open source and may be downloaded from: http://copasi.org/The following licence files are associated with this item: