Modelling the species jump : towards assessing the risk of human infection from novel avian influenzas
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)
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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: https://orcid.org/0000-0002-2242-0781, Havelaar, A. and Stärk, K.;-
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Item type: Article ID code: 54231 Dates: DateEvent30 September 2015Published1 September 2015Published Online12 August 2015AcceptedSubjects: Science > Mathematics > Probabilities. Mathematical statistics Department: Faculty of Science > Mathematics and Statistics Depositing user: Pure Administrator Date deposited: 09 Sep 2015 09:41 Last modified: 11 Nov 2024 11:10 URI: https://strathprints.strath.ac.uk/id/eprint/54231