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Evaluation of Influenza Vaccination Efficacy: A Universal Epidemic Model.
Nizolenko, Lily Ph; Bachinsky, Alexander G; Bazhan, Sergei I.
Affiliation
  • Nizolenko LP; Vector State Research Center of Virology and Biotechnology, Koltsovo, Novosibirsk Region 630559, Russia.
  • Bachinsky AG; Vector State Research Center of Virology and Biotechnology, Koltsovo, Novosibirsk Region 630559, Russia.
  • Bazhan SI; Vector State Research Center of Virology and Biotechnology, Koltsovo, Novosibirsk Region 630559, Russia.
Biomed Res Int ; 2016: 5952890, 2016.
Article in En | MEDLINE | ID: mdl-27668256
ABSTRACT
By means of a designed epidemic model, we evaluated the influence of seasonal vaccination coverage as well as a potential universal vaccine with differing efficacy on the aftermath of seasonal and pandemic influenza. The results of the modeling enabled us to conclude that, to control a seasonal influenza epidemic with a reproduction coefficient R0 ≤ 1.5, a 35% vaccination coverage with the current seasonal influenza vaccine formulation is sufficient, provided that other epidemiology measures are regularly implemented. Increasing R0 level of pandemic strains will obviously require stronger intervention. In addition, seasonal influenza vaccines fail to confer protection against antigenically distinct pandemic influenza strains. Therefore, the necessity of a universal influenza vaccine is clear. The model predicts that a potential universal vaccine will be able to provide sufficient reliable (90%) protection against pandemic influenza only if its efficacy is comparable with the effectiveness of modern vaccines against seasonal influenza strains (70%-80%); given that at least 40% of the population has been vaccinated in advance, ill individuals have been isolated (observed), and a quarantine has been introduced. If other antiepidemic measures are absent, a vaccination coverage of at least 80% is required.

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Biomed Res Int Year: 2016 Document type: Article Affiliation country: RUSSIA

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Biomed Res Int Year: 2016 Document type: Article Affiliation country: RUSSIA