Malaria Journal

, 13:O19 | Cite as

Science and innovation in malaria diagnostics

  • Sanjeev Krishna
  • NanoMal
Open Access
Oral presentation
  • 915 Downloads

Keywords

Malaria Drug Resistance Plasmodium Multidrug Resistance Plasmodium Falciparum 

Five species of Plasmodium naturally infect humans. Some species cause non-specific symptoms that can sometimes progress rapidly to severe and fatal outcomes. Early diagnosis and appropriate treatment interrupts progression and cures disease. Confirmation of diagnosis of malaria currently relies on microscopy, or on application of rapid diagnostic tests (RDTs) that are becoming increasingly widely available and are recommended to confirm infection before treating it. The diagnosis of malaria by itself is not sufficient to optimise individual therapies because there is a growing problem of multidrug resistance in parasites (particularly Plasmodium falciparum). This limits the use of some drugs or combinations by severely compromising their efficacy.

Diagnostic strategies for management of malaria can therefore be improved in several ways. First by an increase in sensitivity of detection of parasites that should improve of the thresholds for detection by the current generation of RDTs because they cannot identify low parasitaemias. Second, a diagnostic that can differentiate all the naturally infecting species of parasite needs to be developed. Finally, rapid (point-of-care) assessment of the drug resistance status of parasites will add greatly to the treatment strategies available to manage individual patients. Technological platforms that can deliver information that is currently missing for the personalised management of malaria infections are being developed and these advances will be presented and discussed in the context of the global burden of disease caused by malaria.

Notes

Acknowledgements

Funded by a grant from the EU under the FP7 innovations programme.

Copyright information

© Krishna and NanoMal; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • Sanjeev Krishna
    • 1
  • NanoMal
    • 1
  1. 1.St. George’s, University of LondonUK

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