Potential for a global dynamic of Influenza A (H1N1).
BACKGROUND
Geographical and temporal diffusion patterns of a human pandemic due to Swine Origin Influenza Virus (S-OIV) remain uncertain. The extent to which national and international pandemic preparedness plans and control strategies can slow or stop the process is not known. However, despite preparedness efforts, it appears that, particularly in the USA, Mexico, Canada and the UK, local chains of virus transmission can sustain autonomous dynamics which may lead to the next pandemic. Forecasts of influenza experts usually rely on information related to new circulating strains.


METHODS
We attempted to quantify the possible spread of the pandemic across a network of 52 major cities and to predict the effect of vaccination against the pandemic strain, if available. Predictions are based on simulations from a stochastic SEIR model. Parameters used in the simulations are set to values consistent with recent estimations from the outbreak in Mexico.


RESULTS
We show that a two-wave pandemic dynamic may be observed in Southern hemisphere because of seasonal constraints for a maximum value of the basic reproductive number (R0, max) within a city equal to 1.5 and a mean generation interval (GI) of 2 days. In this case and in the absence of vaccination, attack rates may reach 46% when considering a completely susceptible population. More severe scenarios characterized by higher values of R0, max (2.2) and GI (3.1) yield an attack rate of 77%. By extrapolation, we find that mass vaccination in all countries (i.e. up to 50% of the population) implemented 6 months after the start of the pandemic may reduce the cumulative number of cases by 91% in the case of the low transmissible strain (R0, max = 1.5). This relative reduction is only 44% for R0, max = 2.2 since most of the cases occur in the first 6 months and so before the vaccination campaign.


CONCLUSIONS
Although uncertainties remain about the epidemiological and clinical characteristics of the new influenza strain, this study provides the first analysis of the potential spread of the pandemic and first assessment of the impact of different immunization strategies.
Flahault
Antoine
A
EHESP School of Public Health, Rennes, France. Antoine.Flahault@ehesp.fr
Vergu
Elisabeta
E
Boëlle
Pierre-Yves
PY
D003198:Computer Simulation; D004196:Disease Outbreaks / Q000517:prevention & control*; D014943:Global Health; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype / Q000472:pathogenicity*; D007252:Influenza Vaccines / Q000008:administration & dosage; D007251:Influenza, Human / Q000453:epidemiology* / Q000517:prevention & control; D008954:Models, Biological
D007252:Influenza Vaccines
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