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Publication
Expanding vaccine efficacy estimation with dynamic models fitted to cross-sectional prevalence data post-licensure
| Name: | Description: | Size: | Format: | |
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| artigo principal | 1.3 MB | Adobe PDF | ||
| material suplementar 1 | 900.02 KB | Adobe PDF |
Authors
Advisor(s)
Abstract(s)
The efficacy of vaccines is typically estimated prior to implementation, on the basis of randomized controlled trials. This does not preclude, however, subsequent assessment post-licensure, while mass-immunization and nonlinear transmission feedbacks are in place. In this paper we show how cross-sectional prevalence data post-vaccination can be interpreted in terms of pathogen transmission processes and vaccine parameters, using a dynamic epidemiological model. We advocate the use of such frameworks for model-based vaccine evaluation in the field, fitting trajectories of cross-sectional prevalence of pathogen strains before and after intervention. Using SI and SIS models, we illustrate how prevalence ratios in vaccinated and non-vaccinated hosts depend on true vaccine efficacy, the absolute and relative strength of competition between target and non-target strains, the time post follow-up, and transmission intensity. We argue that a mechanistic approach should be added to vaccine efficacy estimation against multi-type pathogens, because it naturally accounts for inter-strain competition and indirect effects, leading to a robust measure of individual protection per contact. Our study calls for systematic attention to epidemiological feedbacks when interpreting population level impact. At a broader level, our parameter estimation procedure provides a promising proof of principle for a generalizable framework to infer vaccine efficacy post-licensure.
Description
Keywords
Vaccination model Strain replacement Co-infection Competition ODE parameter inference
Citation
Erida Gjini, M. Gabriela M. Gomes, Expanding vaccine efficacy estimation with dynamic models fitted to cross-sectional prevalence data post-licensure, Epidemics, Volume 14, March 2016, Pages 71-82, ISSN 1755-4365, http://dx.doi.org/10.1016/j.epidem.2015.11.001.
Publisher
Elsivier Science BV