Poster

Re-parameterisation of a mathematical model of AHSV using data from literature

eSMB2020 eSMB2020 Follow 2:30 - 3:30pm EDT, Monday - Wednesday
Share this

Emma L Fairbanks

University of Nottingham
"Re-parameterisation of a mathematical model of AHSV using data from literature"
Midge-borne arboviruses were once restricted to other geographical regions; however due to climate change and increased globalisation these diseases now pose a threat to the UK, with outbreaks having already occurred. African horse sickness virus (AHSV) is endemic in parts of Africa. An outbreak in Spain 1987-1990, which spread to Portugal and Morocco, demonstrated the ability of this virus to spread within Europe. A previously published model suggested an ordinary differential equation model for AHSV in which parameters were derived from three published studies. In order to better inform the model studies documenting experimental infection of equids in vaccination trials were systematically reviewed. As we were interested in modelling emergence of AHSV in a naive population, only experimental infections of control (i.e. naive) animals were considered. Parameters derived from the systematic review were the time until the onset of viraemia, clinical signs and death after experimental infection of a naive equid. The mean latent period of horses was found to be 4.6 days, longer than previously estimated (3.7 days). The infectious periods of dying and surviving hosts were found to be 3.9 and 8.7 days, whereas previous estimations where 4.4 and 6 days, respectively. The host mortality rate was also found to be higher than previous estimations. Model simulations were compared for the previously published models parameters and an updated set of parameter values derived from the systematic review and other literature. The updated parameter values resulted in an increase in the number of host deaths and decrease in the duration of the outbreak. We also observed many more vector infections in simulations using the updated parameters. Sensitivity analysis showed that the host latent period and vector to host ratio had the greatest impact on simulation outputs. The vector parameters in this model were also updated using literature. However, many of these were from studies on american vector species. Therefore, the stages of this work involve fitting a model developed for the vector populations to UK trap data.
eSMB2020
Hosted by eSMB2020 Follow
Virtual conference of the Society for Mathematical Biology, 2020.