Modelling the species jump : towards assessing the risk of human infection from novel avian influenzas

Tools

Hill, A. A. and Dewé, T. and Kosmider, R. and Von Dobschuetz, S. and Munoz, O. and Hanna, A. and Fusaro, A. and De Nardi, M. and Howard, W. and Stevens, K. and Kelly, L. and Havelaar, A. and Stärk, K. (2015) Modelling the species jump : towards assessing the risk of human infection from novel avian influenzas. Royal Society Open Science, 2 (9). 150173. (https://doi.org/10.1098/rsos.150173)

[thumbnail of Hill-etal-RSOS-2015-Modelling-the-species-jump-towards-assessing-the-risk-of-human-infection]
Preview
 Text. Filename: Hill_etal_RSOS_2015_Modelling_the_species_jump_towards_assessing_the_risk_of_human_infection.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (1MB)| Preview

Abstract

The scientific understanding of the driving factors behind zoonotic and pandemic influenzas is hampered by complex interactions between viruses, animal hosts and humans. This complexity makes identifying influenza viruses of high zoonotic or pandemic risk, before they emerge from animal populations, extremely difficult and uncertain. As a first step towards assessing zoonotic risk of Influenza, we demonstrate a risk assessment framework to assess the relative likelihood of influenza A viruses, circulating in animal populations, making the species jump into humans. The intention is that such a risk assessment framework could assist decisionmakers to compare multiple influenza viruses for zoonotic potential and hence to develop appropriate strain-specific control measures. It also provides a first step towards showing proof of principle for an eventual pandemic risk model. We show that the spatial and temporal epidemiology is as important in assessing the risk of an influenza A species jump as understanding the innate molecular capability of the virus.We also demonstrate data deficiencies that need to be addressed in order to consistently combine both epidemiological and molecular virology data into a risk assessment framework.

ORCID iDs

Hill, A. A., Dewé, T., Kosmider, R., Von Dobschuetz, S., Munoz, O., Hanna, A., Fusaro, A., De Nardi, M., Howard, W., Stevens, K., Kelly, L. ORCID logoORCID: https://orcid.org/0000-0002-2242-0781, Havelaar, A. and Stärk, K.;
CORE (COnnecting REpositories)