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The Dynamics of Naturally Acquired Immunity to Plasmodium falciparum Infection

Overview of attention for article published in PLoS Computational Biology, October 2012
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Title
The Dynamics of Naturally Acquired Immunity to Plasmodium falciparum Infection
Published in
PLoS Computational Biology, October 2012
DOI 10.1371/journal.pcbi.1002729
Pubmed ID
Authors

Mykola Pinkevych, Janka Petravic, Kiprotich Chelimo, James W. Kazura, Ann M. Moormann, Miles P. Davenport

Abstract

Severe malaria occurs predominantly in young children and immunity to clinical disease is associated with cumulative exposure in holoendemic settings. The relative contribution of immunity against various stages of the parasite life cycle that results in controlling infection and limiting disease is not well understood. Here we analyse the dynamics of Plasmodium falciparum malaria infection after treatment in a cohort of 197 healthy study participants of different ages in order to model naturally acquired immunity. We find that both delayed time-to-infection and reductions in asymptomatic parasitaemias in older age groups can be explained by immunity that reduces the growth of blood stage as opposed to liver stage parasites. We found that this mechanism would require at least two components - a rapidly acting strain-specific component, as well as a slowly acquired cross-reactive or general immunity to all strains. Analysis and modelling of malaria infection dynamics and naturally acquired immunity with age provides important insights into what mechanisms of immune control may be harnessed by malaria vaccine strategists.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 145 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Tanzania, United Republic of 1 <1%
France 1 <1%
Brazil 1 <1%
United Kingdom 1 <1%
Denmark 1 <1%
Spain 1 <1%
United States 1 <1%
Philippines 1 <1%
Unknown 137 94%

Demographic breakdown

Readers by professional status Count As %
Student > Master 29 20%
Student > Ph. D. Student 26 18%
Researcher 24 17%
Student > Bachelor 19 13%
Student > Doctoral Student 9 6%
Other 15 10%
Unknown 23 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 29%
Biochemistry, Genetics and Molecular Biology 20 14%
Medicine and Dentistry 20 14%
Immunology and Microbiology 13 9%
Computer Science 6 4%
Other 15 10%
Unknown 29 20%