tetano
Editor, Senior Moderator
Vaccine
. 2021 Jan 19;S0264-410X(21)00006-2.
doi: 10.1016/j.vaccine.2021.01.006. Online ahead of print.
In silico prediction of influenza vaccine effectiveness by sequence analysis
Lirong Cao[SUP] 1 [/SUP], Jingzhi Lou[SUP] 2 [/SUP], Shi Zhao[SUP] 3 [/SUP], Renee W Y Chan[SUP] 4 [/SUP], Martin Chan[SUP] 5 [/SUP], William K K Wu[SUP] 6 [/SUP], Marc Ka Chun Chong[SUP] 7 [/SUP], Benny Chung-Ying Zee[SUP] 8 [/SUP], Eng Kiong Yeoh[SUP] 9 [/SUP], Samuel Yeung-Shan Wong[SUP] 10 [/SUP], Paul K S Chan[SUP] 11 [/SUP], Maggie Haitian Wang[SUP] 12 [/SUP]
Affiliations
Abstract
The effectiveness of seasonal influenza vaccines varies with the matching of vaccine strains to circulating strains. Based on the genetic distance of hemagglutinin and neuraminidase gene of the influenza viruses to vaccine strains, we statistically quantified the relationship between the genetic mismatch and vaccine effectiveness (VE) for influenza A/H1N1pdm09, A/H3N2 and B. We also proposed a systematic approach to integrate multiple genes and influenza types for overall VE estimation. Evident linear relationships were identified and validated in independent data. The modelling framework may enable in silico prediction for VE on a real-time basis and inform the influenza vaccine selection strategy.
Keywords: Influenza; Real-time estimation; Vaccine effectiveness.
. 2021 Jan 19;S0264-410X(21)00006-2.
doi: 10.1016/j.vaccine.2021.01.006. Online ahead of print.
In silico prediction of influenza vaccine effectiveness by sequence analysis
Lirong Cao[SUP] 1 [/SUP], Jingzhi Lou[SUP] 2 [/SUP], Shi Zhao[SUP] 3 [/SUP], Renee W Y Chan[SUP] 4 [/SUP], Martin Chan[SUP] 5 [/SUP], William K K Wu[SUP] 6 [/SUP], Marc Ka Chun Chong[SUP] 7 [/SUP], Benny Chung-Ying Zee[SUP] 8 [/SUP], Eng Kiong Yeoh[SUP] 9 [/SUP], Samuel Yeung-Shan Wong[SUP] 10 [/SUP], Paul K S Chan[SUP] 11 [/SUP], Maggie Haitian Wang[SUP] 12 [/SUP]
Affiliations
- PMID: 33483214
- DOI: 10.1016/j.vaccine.2021.01.006
Abstract
The effectiveness of seasonal influenza vaccines varies with the matching of vaccine strains to circulating strains. Based on the genetic distance of hemagglutinin and neuraminidase gene of the influenza viruses to vaccine strains, we statistically quantified the relationship between the genetic mismatch and vaccine effectiveness (VE) for influenza A/H1N1pdm09, A/H3N2 and B. We also proposed a systematic approach to integrate multiple genes and influenza types for overall VE estimation. Evident linear relationships were identified and validated in independent data. The modelling framework may enable in silico prediction for VE on a real-time basis and inform the influenza vaccine selection strategy.
Keywords: Influenza; Real-time estimation; Vaccine effectiveness.