The seasonal influenza viruses have caused and will continue to cause significant threat to public health, resulting in about three to five million cases of severe illness, and about 250,000–500,000 deaths worldwide each year. At present, massive vaccination is the most effective way to prevent and control the influenza annual epidem-ics. Unfortu-nately, the timely and accurate selection of vaccine strains is challeng-ing because the influenza virus changes its antigenicity rapidly by either mutation or reassortment.

The research group led by Professor JIANG Taijiao at the Institute of Biophysics, Chinese Academy of Sciences has rich experience in the field of computational modeling of influenza evolution, and has long-term close cooperation with Dr. SHU Yuelong from the Chinese National Influenza Center. Supported by grants from the Major National Earmark Project for Infectious Diseases, the two groups have developed a novel computational method that analyses 12 structural and physiochemical features of the haemagglutinin (HA) antigen to model the antigenic clusters of the strains. This method not only allows them to follow the evolution of H3N2 viruses in China, but also offers an avenue to predict vaccine strains that may be useful in future vaccination programmes.

On Feb. 28, 2012, this work was published online in Nature Communications (http://www.nature.com/ncomms/journal/v3/n2/full/ncomms1710.html), and was recommended as research highlight (http://www.natureasia.com/en/research/index/highlight/id/1689). On March 2, 2012, Xinhua News Agency reported this work under the title “Chinese scientists developed a novel method for influenza vaccine strains recommendations” (http://news.xinhuanet.com/tech/2012-03/02/c_111596488.htm). The novel computational method should benefit the planning of influenza prevention and control for China and across the globe as well.

Figure 1: Automatic vaccine strain recommendations based on the H3N2 viruses monitored in China.