TY - JOUR
T1 - Vaccination against 2009 pandemic H1N1 in a population dynamical model of Vancouver, Canada
T2 - Timing is everything
AU - Conway, Jessica M.
AU - Tuite, Ashleigh R.
AU - Fisman, David N.
AU - Hupert, Nathaniel
AU - Meza, Rafael
AU - Davoudi, Bahman
AU - English, Krista
AU - Van Den Driessche, P.
AU - Brauer, Fred
AU - Ma, Junling
AU - Meyers, Lauren Ancel
AU - Smieja, Marek
AU - Greer, Amy
AU - Skowronski, Danuta M.
AU - Buckeridge, David L.
AU - Kwong, Jeffrey C.
AU - Wu, Jianhong
AU - Moghadas, Seyed M.
AU - Coombs, Daniel
AU - Brunham, Robert C.
AU - Pourbohloul, Babak
N1 - Funding Information:
The authors would like to acknowledge the support of the Canadian Institute of Health Research (CIHR) through the grant no. PTL-97126 to the Canadian Consortium for Pandemic Preparedness Modeling (CanPan). This research has been enabled by the use of computing resources provided by WestGrid and Compute/Calcul Canada. We would like to thank Robert Smith from the Population Health, Surveillance and Epidemiology Division, the British Columbia Ministry of Health for providing the physicians’ billing data and summary of the BC Centre for Disease Control Virology Laboratory pH1N1 laboratory confirmation. Authors recognize local health care providers and public health practitioners for their invaluable contribution to pandemic H1N1 surveillance in British Columbia and Travis Hottes and Naveed Janjua of the BC Centre for Disease Control Influenza Team for their analysis and summary of that.
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
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U2 - 10.1186/1471-2458-11-932
DO - 10.1186/1471-2458-11-932
M3 - Article
C2 - 22168242
AN - SCOPUS:83355172202
SN - 1471-2458
VL - 11
JO - BMC Public Health
JF - BMC Public Health
M1 - 932
ER -