Introducing a framework for within-host dynamics and mutations modelling of H5N1 influenza infection in humans (preprint)Link opens in a new window

Daniel Higgins, Joshua Looker, Robert Sunnucks, Jonathan Carruthers, Thomas Finnie, Matt J. Keeling, Edward M. Hill

We present a mechanistic within-host infection model for influenza A(H5N1), novel for its explicit consideration of the biological differences between the upper and lower respiratory tracts. These developments enable us to estimate a distribution of viral lifespans and effective replication rates in human H5N1 influenza cases. We combine our within-host model with a viral mutation model to determine the probability of an infected individual generating a droplet transmissible strain of influenza A(H5N1) through mutation. For three required mutations, we found a peak probability of approximately 10⁻³ that a human case of H5N1 influenza produces at least one virion during the infectious period. Our findings provide insights into the risk of differing infectious pathways of influenza A(H5N1) (namely the avian-human vs the avian-mammal-human routes), demonstrating the three-mutation pathway being a cause of concern in human cases. Additionally, our framework - combining a within-host infection model with a branching process model for viral mutation - is generalisable to other pathogens, allowing mutation probabilities to be more easily ascertained. Our findings are a starting point for further modelling of influenza A(H5N1) and other pathogens where differing tissue susceptibilities and human-to-human transmission is of concern.

Various articles and packages (with Covid-19 Modelling AotearoaLink opens in a new window)

Covid-19 Modelling Aotearoa modelled Covid-19 and its projected impacts from January 2020 until July 2023. We built a cross-organisation, transdisciplinary, dedicated, and committed group of academic researchers and scientists to help Aotearoa New Zealand face the pandemic.

Covid-19 Modelling Aotearoa arose under the leadership of Te Pūnaha Matatini investigators, and was a standalone programme hosted by the University of Auckland from January 2021. Early in the pandemic we were funded by the Ministry of Business, Innovation and Employment, followed by the Department of the Prime Minister and Cabinet, and then Manatū Hauora Ministry of Health.

I was part of the network- and individual-based modelling team that simulated the spread of Covid-19 in Aotearoa New Zealand. We developed a synthetic population of 4.5 million individuals each modelled within a bipartite interaction network representing New Zealand.

Synthetic population and network building Python package (PAINLink opens in a new window)

Novel simulation methods for contagion on a bipartite network Python package (cobinLink opens in a new window)

Published articles and reports can be found on the CMA website.Link opens in a new window