Vaccination against 2009 pandemic H1N1 in a population dynamical model of Vancouver, Canada : timing is everything
Date
2011-12-14
Authors
Conway, Jessica M.
Tuite, Ashleigh R.
Fisman, David N.
Hupert, Nathaniel
Meza, Rafael
Davoudi, Bahman
English, Krista
Van den Driessche, Pauline
Ma, Junling
Journal Title
Journal ISSN
Volume Title
Publisher
BioMed Central
Abstract
Background: Much remains unknown about the effect of timing and prioritization of vaccination against
pandemic (pH1N1) 2009 virus on health outcomes. We adapted a city-level contact network model to study
different campaigns on influenza morbidity and mortality.
Methods: We modeled different distribution strategies initiated between July and November 2009 using a
compartmental epidemic model that includes age structure and transmission network dynamics. The model represents
the Greater Vancouver Regional District, a major North American city and surrounding suburbs with a population of 2
million, and is parameterized using data from the British Columbia Ministry of Health, published studies, and expert
opinion. Outcomes are expressed as the number of infections and deaths averted due to vaccination.
Results: The model output was consistent with provincial surveillance data. Assuming a basic reproduction number =
1.4, an 8-week vaccination campaign initiated 2 weeks before the epidemic onset reduced morbidity and mortality by
79-91% and 80-87%, respectively, compared to no vaccination. Prioritizing children and parents for vaccination may
have reduced transmission compared to actual practice, but the mortality benefit of this strategy appears highly
sensitive to campaign timing. Modeling the actual late October start date resulted in modest reductions in morbidity
and mortality (13-25% and 16-20%, respectively) with little variation by prioritization scheme.
Conclusion: Delays in vaccine production due to technological or logistical barriers may reduce potential benefits
of vaccination for pandemic influenza, and these temporal effects can outweigh any additional theoretical benefits
from population targeting. Careful modeling may provide decision makers with estimates of these effects before
the epidemic peak to guide production goals and inform policy. Integration of real-time surveillance data with
mathematical models holds the promise of enabling public health planners to optimize the community benefits
from proposed interventions before the pandemic peak.
Description
BioMed Central
Keywords
Citation
Conway et al.: Vaccination against 2009 pandemic H1N1 in a population dynamical model of Vancouver, Canada: timing is everything. BMC Public Health 2011 11:932.