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Explaining Observed Infection and Antibody Age-Profiles in Populations with Urogenital Schistosomiasis

Overview of attention for article published in PLoS Computational Biology, October 2011
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Title
Explaining Observed Infection and Antibody Age-Profiles in Populations with Urogenital Schistosomiasis
Published in
PLoS Computational Biology, October 2011
DOI 10.1371/journal.pcbi.1002237
Pubmed ID
Authors

Kate M. Mitchell, Francisca Mutapi, Nicholas J. Savill, Mark E. J. Woolhouse

Abstract

Urogenital schistosomiasis is a tropical disease infecting more than 100 million people in sub-Saharan Africa. Individuals in endemic areas endure repeated infections with long-lived schistosome worms, and also encounter larval and egg stages of the life cycle. Protective immunity against infection develops slowly with age. Distinctive age-related patterns of infection and specific antibody responses are seen in endemic areas, including an infection 'peak shift' and a switch in the antibody types produced. Deterministic models describing changing levels of infection and antibody with age in homogeneously exposed populations were developed to identify the key mechanisms underlying the antibody switch, and to test two theories for the slow development of protective immunity: that (i) exposure to dying (long-lived) worms, or (ii) experience of a threshold level of antigen, is necessary to stimulate protective antibody. Different model structures were explored, including alternative stages of the life cycle as the main antigenic source and the principal target of protective antibody, different worm survival distributions, antigen thresholds and immune cross-regulation. Models were identified which could reproduce patterns of infection and antibody consistent with field data. Models with dying worms as the main source of protective antigen could reproduce all of these patterns, but so could some models with other continually-encountered life stages acting as the principal antigen source. An antigen threshold enhanced the ability of the model to replicate these patterns, but was not essential for it to do so. Models including either non-exponential worm survival or cross-regulation were more likely to be able to reproduce field patterns, but neither of these was absolutely required. The combination of life cycle stage stimulating, and targeted by, antibody was found to be critical in determining whether models could successfully reproduce patterns in the data, and a number of combinations were excluded as being inconsistent with field data.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Kenya 1 2%
Unknown 59 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 25%
Researcher 8 13%
Student > Bachelor 7 11%
Student > Master 7 11%
Professor 4 7%
Other 11 18%
Unknown 9 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 30%
Medicine and Dentistry 8 13%
Mathematics 4 7%
Biochemistry, Genetics and Molecular Biology 3 5%
Environmental Science 3 5%
Other 11 18%
Unknown 14 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 November 2011.
All research outputs
#23,154,082
of 25,806,080 outputs
Outputs from PLoS Computational Biology
#8,653
of 9,043 outputs
Outputs of similar age
#140,506
of 152,353 outputs
Outputs of similar age from PLoS Computational Biology
#123
of 129 outputs
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