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The pathogenic basis of malaria

Author

Listed:
  • Louis H. Miller

    (Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health)

  • Dror I. Baruch

    (Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health)

  • Kevin Marsh

    (KEMRI-Wellcome Trust Collaboration Programme, Center for Geographic Medicine Research Coast)

  • Ogobara K. Doumbo

    (Malaria Research and Training Center)

Abstract

Malaria is today a disease of poverty and underdeveloped countries. In Africa, mortality remains high because there is limited access to treatment in the villages. We should follow in Pasteur's footsteps by using basic research to develop better tools for the control and cure of malaria. Insight into the complexity of malaria pathogenesis is vital for understanding the disease and will provide a major step towards controlling it. Those of us who work on pathogenesis must widen our approach and think in terms of new tools such as vaccines to reduce disease. The inability of many countries to fund expensive campaigns and antimalarial treatment requires these tools to be highly effective and affordable.

Suggested Citation

  • Louis H. Miller & Dror I. Baruch & Kevin Marsh & Ogobara K. Doumbo, 2002. "The pathogenic basis of malaria," Nature, Nature, vol. 415(6872), pages 673-679, February.
    • Handle: RePEc:nat:nature:v:415:y:2002:i:6872:d:10.1038_415673a
    DOI: 10.1038/415673a
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    Cited by:

    1. Qilong Li & Kunying Lv & Ning Jiang & Tong Liu & Nan Hou & Liying Yu & Yixin Yang & Anni Feng & Yiwei Zhang & Ziwei Su & Xiaoyu Sang & Ying Feng & Ran Chen & Wenyue Xu & Liwang Cui & Yaming Cao & Qiju, 2024. "SOD3 suppresses early cellular immune responses to parasite infection," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Chen, Hongyan & Wang, Wendi & Fu, Rui & Luo, Jianfeng, 2015. "Global analysis of a mathematical model on malaria with competitive strains and immune responses," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 132-152.
    3. Titus Okello Orwa & Rachel Waema Mbogo & Livingstone Serwadda Luboobi, 2018. "Mathematical Model for Hepatocytic-Erythrocytic Dynamics of Malaria," International Journal of Mathematics and Mathematical Sciences, Hindawi, vol. 2018, pages 1-18, July.
    4. Ping Chun Wu & Yan Quan Lee & Mattias Möller & Jill R. Storry & Martin L. Olsson, 2023. "Elucidation of the low-expressing erythroid CR1 phenotype by bioinformatic mining of the GATA1-driven blood-group regulome," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

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