  On 11 June the World Health Organization officially raised the phase of
pandemic alert (with regard to the new H1N1 influenza strain) to level 6. We
use a global structured metapopulation model integrating mobility and
transportation data worldwide in order to estimate the transmission potential
and the relevant model parameters we used the data on the chronology of the
2009 novel influenza A(H1N1). The method is based on the maximum likelihood
analysis of the arrival time distribution generated by the model in 12
countries seeded by Mexico by using 1M computationally simulated epidemics. An
extended chronology including 93 countries worldwide seeded before 18 June was
used to ascertain the seasonality effects. We found the best estimate R0 = 1.75
(95% CI 1.64 to 1.88) for the basic reproductive number. Correlation analysis
allows the selection of the most probable seasonal behavior based on the
observed pattern, leading to the identification of plausible scenarios for the
future unfolding of the pandemic and the estimate of pandemic activity peaks in
the different hemispheres. We provide estimates for the number of
hospitalizations and the attack rate for the next wave as well as an extensive
sensitivity analysis on the disease parameter values. We also studied the
effect of systematic therapeutic use of antiviral drugs on the epidemic
timeline. The analysis shows the potential for an early epidemic peak occurring
in October/November in the Northern hemisphere, likely before large-scale
vaccination campaigns could be carried out. We suggest that the planning of
additional mitigation policies such as systematic antiviral treatments might be
the key to delay the activity peak inorder to restore the effectiveness of the
vaccination programs.

Populations and Evolution;Statistical Mechanics;Physics and Society