Evaluation of Targeted Influenza Vaccination Strategies via Population Modeling

Abstract

BackgroundBecause they can generate comparable predictions, mathematical models are ideal tools for evaluating alternative drug or vaccine allocation strategies. To remain credible, however, results must be consistent. Authors of a recent assessment of possible influenza vaccination strategies conclude that older children, adolescents, and young adults are the optimal targets, no matter the objective, and argue for vaccinating them. Authors of two earlier studies concluded, respectively, that optimal targets depend on objectives and cautioned against changing policy. Which should we believe?Methods and FindingsIn matrices whose elements are contacts between persons by age, the main diagonal always predominates, reflecting contacts between contemporaries. Indirect effects (e.g., impacts of vaccinating one group on morbidity or mortality in others) result from off-diagonal elements. Mixing matrices based on periods in proximity with others have greater sub- and super-diagonals, reflecting contacts between parents and children, and other off-diagonal elements (reflecting, e.g., age-independent contacts among co-workers), than those based on face-to-face conversations. To assess the impact of targeted vaccination, we used a time-usage study's mixing matrix and allowed vaccine efficacy to vary with age. And we derived mortality rates either by dividing observed deaths attributed to pneumonia and influenza by average annual cases from a demographically-realistic SEIRS model or by multiplying those rates by ratios of (versus adding to them differences between) pandemic and pre-pandemic mortalities.ConclusionsIn our simulations, vaccinating older children, adolescents, and young adults averts the most cases, but vaccinating either younger children and older adults or young adults averts the most deaths, depending on the age distribution of mortality. These results are consistent with those of the earlier studies.

Modelling mitigation strategies for pandemic (H1N1) 2009

“…Mathematical models can project strategy effectiveness under hypothetical epidemiologic and program scenarios. [6][7][8][9][10][11][12] In the case of pandemic influenza, models have been used to assess the effectiveness of school closure 7 and optimal use of antiviral drug 6,9,10 and vaccination strategies. 8 However, model projections can be sensitive to input parameter values; thus, data uncertainty is an issue.…”

Association of Influenza Vaccination Coverage in Younger Adults With Influenza-Related Illness in the Elderly

“…Surprisingly, for counties with vaccination coverage available for both age groups, only nonelderly adult coverage was associated with influenzarelated illness among the elderly. This result is seemingly at odds with theoretical work suggesting that vaccination of children and their parents (or young adults in general) may be sufficient to protect elders [7][8][9]13]. However, most prior studies have considered near-universal vaccination of children [14,15] or optimal vaccine allocation strategies during pandemic rather than typical influenza seasons [7][8][9].…”

“…Our comparison data for children were limited to infants/ toddlers and adolescents, whereas previous theoretical work has hypothesized that elementary school-aged children may be the main spreaders of influenza [7][8][9]13]. However, additional data (not publicly reported by county or state) would matter only to the extent that immunization patterns for elementary schoolaged children mirrored those of nonelderly adults rather than those for both younger and older children, which we found to be unrelated to adult vaccination coverage.…”

Systematic Review of Strategies to Manage and Allocate Scarce Resources During Mass Casualty Events

“…Improving the evidence base will require a diverse group of policy makers, funders, and non-governmental experts to come together to craft a well-organized and coordinated program of applied research 38 that adheres to appropriate ethical and methodological standards. Glasser, 2010 44 McVernon, 2010 45 Medlock…”