Measuring vaccine efficacy from epidemics of acute infectious agents
Identifieur interne : 006B19 ( Main/Merge ); précédent : 006B18; suivant : 006B20Measuring vaccine efficacy from epidemics of acute infectious agents
Auteurs : Ira M. Longini Jr. [États-Unis] ; M. Elizabeth Halloran [États-Unis] ; Michael Haber [États-Unis] ; Robert T. Chen [États-Unis]Source :
- Statistics in Medicine [ 0277-6715 ] ; 1993-02.
Abstract
A good measure of field vaccine efficacy should evaluate the direct protective effect of vaccination on the person who receives the vaccine. The conventional estimator for vaccine efficacy depends on population level factors that are either unrelated or indirectly related to the direct biological action of the vaccine on persons, including population structure, duration of the study, the fraction vaccinated, and herd immunity, that is, indirect effects. Indirect effects can cause the conventional vaccine efficacy estimator to be inaccurate. We review alternative vaccine efficacy estimators that control for indirect effects at the population level. Thus, they are more accurate than the conventional estimator. We use epidemic simulations to explore the robustness of the conventional and proposed estimators under different field conditions. In addition, we apply the different vaccine efficacy estimators to data from a measles epidemic in Muyinga, Burundi.
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DOI: 10.1002/sim.4780120309
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<front><div type="abstract" xml:lang="en">A good measure of field vaccine efficacy should evaluate the direct protective effect of vaccination on the person who receives the vaccine. The conventional estimator for vaccine efficacy depends on population level factors that are either unrelated or indirectly related to the direct biological action of the vaccine on persons, including population structure, duration of the study, the fraction vaccinated, and herd immunity, that is, indirect effects. Indirect effects can cause the conventional vaccine efficacy estimator to be inaccurate. We review alternative vaccine efficacy estimators that control for indirect effects at the population level. Thus, they are more accurate than the conventional estimator. We use epidemic simulations to explore the robustness of the conventional and proposed estimators under different field conditions. In addition, we apply the different vaccine efficacy estimators to data from a measles epidemic in Muyinga, Burundi.</div>
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