|Event Title||First Global Alliance for Research on Avian Diseases (GARAD) Conference|
|Event Date & Time||On Mon, 29 Jun 2015 at 12:05:00 - 12:20:00|
|Venue||Edmond J. Safra Lecture Theatre|
|Abstract Title||Predicting the spread of H5N1 in domestic poultry - a mathematical modelling approach|
|Affiliations||University of Nottingham|
Highly Pathogenic Avian Influenza (HPAI) H5N1 is a highly contagious infection of birds caused by a type A influenza virus. Once infected, symptoms can occur within a few hours with mortality of close to 100% in some poultry species within 48 hours after exposure. HPAI H5N1 has been shown to infect wild waterfowl with species-dependent variation in pathogenicity, with work suggesting that migratory waterfowl may have been implicated in long distance transmission events.
Epidemiological models are often used as policy tools to understand the impact of different control actions on the spread of infectious diseases. Such models rely on external information from virologists, clinicians and veterinary authorities. Once parameterized, models can be used to analyse the role of avian species in disease transmission and to simulate the effect of different intervention scenarios on the overall number of birds lost. In this work, we develop a model to simulate the spread of H5N1 in poultry farms to predict the effectiveness of intervention strategies. This work focuses on the HPAI epidemics that hit Thailand in 2004-2005 and Bangladesh from 2007 to 2011 and resulted in the loss of millions of poultry, dramatically affecting farmers' livelihoods and the poultry production sectors as a whole. Our results for Thailand suggest that unreported infection in the duck population resulted in disease persistence whilst the strategy of combined movement restrictions and culling applied by the Thai authorities was more cost-effective than a policy of vaccination. We also present preliminary modelling results for Bangladesh and analyse the impact of different demographic characteristics upon disease transmission. This work will provide support to policy makers regarding the risk associated with avian influenza outbreaks and preferred control strategies in the event of future epidemics.