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Plasmodium knowlesi transmission: integrating quantitative approaches from epidemiology and ecology to understand malaria as a zoonosis

期刊

PARASITOLOGY
卷 143, 期 4, 页码 389-400

出版社

CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0031182015001821

关键词

malaria; mosquito; vector; zoonosis; Plasmodium knowlesi; macaque; infectious disease transmission; mathematical model; R-0; reproduction number

资金

  1. Medical Research Council
  2. Natural Environment Research Council
  3. Economic and Social Research Council
  4. Biotechnology and Biosciences Research Council through the Environmental and Social Ecology of Human Infectious Diseases Initiative (ESEI) [G1100796]
  5. Biotechnology and Biological Sciences Research Council [1517720] Funding Source: researchfish
  6. Medical Research Council [G1100796] Funding Source: researchfish
  7. MRC [G1100796] Funding Source: UKRI

向作者/读者索取更多资源

The public health threat posed by zoonotic Plasmodium knowlesi appears to be growing: it is increasingly reported across South East Asia, and is the leading cause of malaria in Malaysian Borneo. Plasmodium knowlesi threatens progress towards malaria elimination as aspects of its transmission, such as spillover from wildlife reservoirs and reliance on outdoor-biting vectors, may limit the effectiveness of conventional methods of malaria control. The development of new quantitative approaches that address the ecological complexity of P. knowlesi, particularly through a focus on its primary reservoir hosts, will be required to control it. Here, we review what is known about P. knowlesi transmission, identify key knowledge gaps in the context of current approaches to transmission modelling, and discuss the integration of these approaches with clinical parasitology and geostatistical analysis. We highlight the need to incorporate the influences of fine-scale spatial variation, rapid changes to the landscape, and reservoir population and transmission dynamics. The proposed integrated approach would address the unique challenges posed by malaria as a zoonosis, aid the identification of transmission hot-spots, provide insight into the mechanistic links between incidence and land use change and support the design of appropriate interventions.

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