Le Groupe de recherche en \u00e9pid\u00e9miologie des zoonoses et sant\u00e9 publique (GREZOSP) a le plaisir de vous inviter \u00e0 une conf\u00e9rence hybride qui aura lieu le lundi 26 janvier 2026.<\/p>\n\n\n\n
Donn\u00e9e par la Dre Amy Hurford, professeure agr\u00e9g\u00e9e \u00e0 l\u2019Universit\u00e9 Memorial de Terre-Neuve-et-Labrador, cette conf\u00e9rence portera sur l\u2019utilisation du taux historique des pand\u00e9mies pour estimer le taux de l\u00e9talit\u00e9 des infections humaines par le virus de la grippe aviaire.<\/p>\n\n\n\n
Using the historical rate of pandemics to estimate the infection fatality ratio of avian influenza virus infections in humans<\/strong><\/p>\n\n\n\n R\u00e9sum\u00e9 de la pr\u00e9sentation (en anglais): <\/strong>Given the recent outbreaks of highly pathogenic avian influenza virus in animals, it is necessary to communicate the risk to humans and to explain the rationale for preventative measures. The risk of HPAI infection to humans is challenging to estimate because many human avian influenza virus (AIV) infections are undetected as they may be asymptomatic, symptomatic but not tested, and as contact tracing is difficult because human-to-human spread is rare. To overcome this challenge, we derive equations that consider the evolutionary mechanisms that give rise to pandemics and are parameterized to be consistent with past records of pandemics. We estimate that worldwide the mean number of human AIV infections is 6,458 (95% confidence interval: [2,737, 21,265]) in an average year, which corresponds to an estimated infection fatality ratio of 32 deaths per 10,000 human AIV infections. The infection fatality ratio informs individual risk as it describes an average person\u2019s mortality risk given AIV infection. Preventing human AIV infections also reduces the chance of evolutionary adaptation of AIV that could lead to a pandemic. We estimate that preventing 20% of animal-to-human influenza spillovers annually would delay pandemic emergence by an average of 9.4 years. Our results correspond to a worldwide average, and we do not model the epidemiological dynamics of AIV spread in animals or human influenza seasons, which is necessary to inform the spatiotemporal components of risk. Our results help justify the implementation of measures to prevent pandemics because we show that individuals that protect themselves from AIV infections also reduce their risk of infection with a highly pathogenic virus. This is work is led by MSc candidate, Joshua Mack (Memorial University), and is in collaboration with Michael WZ Li (PHAC).<\/p>\n\n\n\n Conf\u00e9renci\u00e8re <\/strong><\/p>\n\n\n\n Dre Amy Hurford est biologiste math\u00e9maticienne, avec des nominations conjointes aux d\u00e9partements de biologie, math\u00e9matiques et statistiques, ainsi qu\u2019\u00e0 la Facult\u00e9 de m\u00e9decine. Ses travaux portent sur l\u2019application de la mod\u00e9lisation math\u00e9matique \u00e0 la dynamique des populations, \u00e0 l\u2019\u00e9cologie et \u00e0 l\u2019\u00e9pid\u00e9miologie \u00e9volutive.<\/p>\n\n\n\n