- 作者：Luc de Montigny ; Katia Charl ; Aman Verma ; John S. Brownstein ; Paul Le Guerrier ; David L. Buckeridge
- 刊名：American Journal of Preventive Medicine
- 出版年：2013
- 出版时间：November, 2013
- 年：2013
- 卷：45
- 期：5
- 页码：622-628
- 全文大小：207 K
lass=""h4"">Background
In response to the 2009 H1N1 influenza pandemic, Canada undertook the largest vaccination campaign in its history. The effort mobilized thousands of healthcare workers, cost many hundreds of millions of dollars, and vaccinated more than 40 % of the population. Despite the large investment in mass vaccination internationally, little is known about the factors that drive the timing of vaccination uptake.lass=""h4"">Purpose
Data from 2009 were used to investigate three potential determinants of vaccination uptake in Montreal, Canada.
lass=""h4"">Methods
Poisson regression was used to analyze daily vaccination before and after a telephone intervention targeting households in 12 of the city¡¯s 29 health neighborhoods. The effect of an eligibility strategy based on risk groups, and of weather, on uptake was then estimated. Data were analyzed in 2013.
lass=""h4"">Results
Considerable variation in daily mass vaccination was observed, with the peak day (30,204 individuals) accounting for nearly five times the uptake of the slowest day (6298 individuals). No evidence was found that the telephone intervention led to a significant increase in vaccination. Daily vaccination was associated significantly with weather conditions, including mean temperature (relative risk [RR]=1.28, 95 % CI=1.12, 1.46) and heavy precipitation (RR=0.63, 95 % CI=0.45, 0.89), even after accounting for changes to eligibility, which also were associated with increased vaccination.
lass=""h4"">Conclusions
Considerable temporal variation in uptake can occur during mass vaccination efforts. Targeted interventions to increase vaccination should be evaluated further, as a large intervention had no observable effect. Mass vaccination campaigns should, however, attempt to optimize priority sequences and account for weather when estimating vaccine demand.