Expanding vaccine efficacy estimation with dynamic models fitted to cross-sectional prevalence data post-licensure

Gjini, Erida; Gomes, M. Gabriela M.

Publication

Expanding vaccine efficacy estimation with dynamic models fitted to cross-sectional prevalence data post-licensure

2016-03Journal article

dc.contributor.author	Gjini, Erida
dc.contributor.author	Gomes, M. Gabriela M.
dc.date.accessioned	2016-03-21T13:34:54Z
dc.date.available	2016-03-21T13:34:54Z
dc.date.issued	2016-03
dc.description.abstract	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.	pt_PT
dc.description.sponsorship	sem patrocinadores explícitos no artigo.	pt_PT
dc.identifier.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.	pt_PT
dc.identifier.doi	10.1016/j.epidem.2015.11.001	pt_PT
dc.identifier.uri	http://hdl.handle.net/10400.7/565
dc.language.iso	eng	pt_PT
dc.peerreviewed	yes	pt_PT
dc.publisher	Elsivier Science BV	pt_PT
dc.relation.publisherversion	http://www.sciencedirect.com/science/article/pii/S1755436515000948	pt_PT
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/	pt_PT
dc.subject	Vaccination model	pt_PT
dc.subject	Strain replacement	pt_PT
dc.subject	Co-infection	pt_PT
dc.subject	Competition	pt_PT
dc.subject	ODE parameter inference	pt_PT
dc.title	Expanding vaccine efficacy estimation with dynamic models fitted to cross-sectional prevalence data post-licensure	pt_PT
dc.type	journal article
dspace.entity.type	Publication
oaire.citation.endPage	82	pt_PT
oaire.citation.startPage	71	pt_PT
oaire.citation.title	Epidemics	pt_PT
oaire.citation.volume	14	pt_PT
rcaap.rights	openAccess	pt_PT
rcaap.type	article	pt_PT