oai:HAL:pasteur-04095291v1
HAL CCSD;Nature Publishing Group
CNRS - Centre national de la recherche scientifique
2022
07-10-2023
International audience; Abstract For >70 years, a 4-fold or greater rise in antibody titer has been used to confirm influenza virus infections in paired sera, despite recognition that this heuristic can lack sensitivity.
Here we analyze with a novel Bayesian model a large cohort of 2353 individuals followed for up to 5 years in Hong Kong to characterize influenza antibody dynamics and develop an algorithm to improve the identification of influenza virus infections.
After infection, we estimate that hemagglutination-inhibiting (HAI) titers were boosted by 16-fold on average and subsequently decrease by 14% per year.
In six epidemics, the infection risks for adults were 3%–19% while the infection risks for children were 1.6–4.4 times higher than that of younger adults.
Every two-fold increase in pre-epidemic HAI titer was associated with 19%–58% protection against infection.
Our inferential framework clarifies the contributions of age and pre-epidemic HAI titers to characterize individual infection risk.
Tsang, Tim, K,Perera, Ranawaka, a P M,Fang, Vicky, J,Wong, Jessica, Y,Shiu, Eunice, Y,So, Hau Chi,Ip, Dennis, K M,Malik Peiris, J, S,Leung, Gabriel, M,Cowling, Benjamin, J,Cauchemez, Simon, 2022, Reconstructing antibody dynamics to estimate the risk of influenza virus infection, HAL CCSD;Nature Publishing Group