Modelling the roles of antibody titre and avidity in protection from Plasmodium falciparum malaria infection following RTS,S/AS01 vaccination
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Supporting information
Published version
Author(s)
Type
Journal Article
Abstract
Anti-circumsporozoite antibody titres have been established as an essential indicator for evaluating the immunogenicity and protective capacity of the RTS,S/AS01 malaria vaccine. However, a new delayed-fractional dose regime of the vaccine was recently shown to increase vaccine efficacy, from 62.5% (95% CI 29.4–80.1%) under the original dosing schedule to 86.7% (95% CI, 66.8–94.6%) without a corresponding increase in antibody titres. Here we reanalyse the antibody data from this challenge trial to determine whether IgG avidity may help to explain efficacy better than IgG titre alone by adapting a within-host mathematical model of sporozoite inoculation. We demonstrate that a model incorporating titre and avidity provides a substantially better fit to the data than titre alone. These results also suggest that in individuals with a high antibody titre response that also show high avidity (both metrics in the top tercile of observed values) delayed-fractional vaccination provided near perfect protection upon first challenge (98.2% [95% Credible Interval 91.6–99.7%]). This finding suggests that the quality of the vaccine induced antibody response is likely to be an important determinant in the development of highly efficacious pre-erythrocytic vaccines against malaria.
Date Issued
2020-11-03
Date Acceptance
2020-09-24
Citation
Vaccine, 2020, 38 (47), pp.7498-7507
ISSN
0264-410X
Publisher
Elsevier
Start Page
7498
End Page
7507
Journal / Book Title
Vaccine
Volume
38
Issue
47
Copyright Statement
© 2020 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Sponsor
Medical Research Council (MRC)
Imperial College LOndon
Grant Number
MR/L006529/1
Subjects
Antibody response
Correlates of protection
Malaria
Mathematical modelling
Predictive vaccine efficacy
Sporozoites
Virology
06 Biological Sciences
07 Agricultural and Veterinary Sciences
11 Medical and Health Sciences
Publication Status
Published
Date Publish Online
2020-10-09