Variability in transmissibility of the 2009 H1N1 pandemic in Canadian communities
1 Centre for Disease Modelling, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada
2 Modeling and Projection Section, Professional Guidelines and Public Health Practice Division, Centre for Communicable Diseases and Infection Control, Public Health Agency of Canada, 180 Queen Street W., Toronto, ON, M5V 3L7, Canada
3 Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON, M5T 3M7, Canada
4 Public Health Ontario, 480 University Avenue, Toronto, ON, M5G 1V2, Canada
BMC Research Notes 2011, 4:537 doi:10.1186/1756-0500-4-537Published: 13 December 2011
The prevalence and severity of the 2009 H1N1 pandemic appeared to vary significantly across populations and geographic regions. We sought to investigate the variability in transmissibility of H1N1 pandemic in different health regions (including urban centres and remote, isolated communities) in the province of Manitoba, Canada.
The Richards model was used to fit to the daily number of laboratory-confirmed cases and estimate transmissibility (referred to as the basic reproduction number, R0), doubling times, and turning points of outbreaks in both spring and fall waves of the H1N1 pandemic in several health regions.
We observed considerable variation in R0 estimates ranging from 1.55 to 2.24, with confidence intervals ranging from 1.45 to 2.88, for an average generation time of 2.9 days, and shorter doubling times in some remote and isolated communities compared to urban centres, suggesting a more rapid spread of disease in these communities during the first wave. For the second wave, Re, the effective reproduction number, is estimated to be lower for remote and isolated communities; however, outbreaks appear to have been driven by somewhat higher transmissibility in urban centres.
There was considerable geographic variation in transmissibility of the 2009 pandemic outbreaks. While highlighting the importance of estimating R0 for informing health responses, the findings indicate that projecting the transmissibility for large-scale epidemics may not faithfully characterize the early spread of disease in remote and isolated communities.