Predicting the spread of Influenza A
The joint effort of the two research groups at Indiana University and Institute for Scientific Interchange Foundation in Turin, coordinated by Prof. Alessandro Vespignani, has led to the production of projections of the spread of the ongoing H1N1 Flu epidemic.
By using the data on the chronology of the 2009 novel influenza A(H1N1), in order to estimate the transmission potential and the relevant model parameters, the model generated stochastic realizations of the epidemic evolution worldwide to gather information such as prevalence, morbidity, number of secondary cases etc.
Based on the maximum likelihood analysis of the arrival time distribution generated by the model in 12 countries seeded by Mexico and by using 1 million computationally simulated epidemics, a best estimate R0 = 1.75 (95% confidence interval (CI) 1.64 to 1.88) was found for the basic reproductive number.
US winter projections: mitigation effect of antiviral treatment
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.
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. The baseline results refer to a worst-case scenario in which additional mitigation policies are not considered. We suggest that the planning of additional mitigation policies such as systematic antiviral treatments might be the key to delay the activity peak in order to restore the effectiveness of the vaccination programs.
Read more on:
- D. Balcan, H. Hu, B. Goncalves, P. Bajardi, C. Poletto, J.J. Ramasco, D. Paolotti, N. Perra, M. Tizzoni, W. Van den Broeck, V. Colizza, A. Vespignani “Seasonal transmission potential and activity peaks of the new influenza A(H1N1): a Monte Carlo likelihood analysis based on human mobility“, BMC Medicine 2009 7:45
