Applications of bioinformatics and computational biology to influenza surveillance and vaccine strain selection.

In recent years, collaborations often between mathematical and computational biologists and scientists in the World Health Organization (WHO) global influenza surveillance network, have resulted in a number of mathematical and computational advances including: increasing the resolution at which antigenic surveillance data can be analyzed, providing methods for genetic analysis and prediction, and an increased understanding of the determinants of repeated influenza vaccination. These advances increase the information extracted from influenza surveillance and increase the quantitative data available for the vaccine strain selection process. This mathematical and computational work is possible because of the wealth of information collected over many years by the WHO global influenza surveillance network, and further advances will be greatly facilitated by implementation of the proposed strengthening of virological and epidemiological surveillance in the WHO global agenda on influenza surveillance and control.