Abstract
Within the last 10 years, Denmark has faced an increasing number of Avian Influenza cases in wild birds and outbreaks on poultry farms, emphasizing the need to update national avian influenza prevention and control strategies. Highly Pathogenic Avian Influenza (HPAI) is transmitted over long distances by migratory wild birds, and wild birds can further spread the disease locally via their aggregation in suitable areas. With a coastline of more than 8,000 km, Denmark is an important stopover for migratory birds. Bird species belonging to the order Anseriformes have been the most commonly reported Avian Influenza virus positive species in recent years in Denmark.
This study aims to improve the understanding of HPAI transmission in migratory wild birds by developing a stochastic spatiotemporal epidemiological model. The model will predict HPAI prevalence in selected wild bird species over one year simulated period and identify hotspots and high-risk periods of transmission.
To date we have rasterized Denmark into 10 by 10 km grid cells. We have then combined 5 years of national and citizen science weekly count data on bird populations for five common bird species (two swan species, two geese species and one duck species) in each grid cell and extrapolated to grid cells with unknown counts using geographical and temporal variables and generalized linear mixed model regression. Following this, we built a mechanistic simulation model including three weekly steps; temporal migration of birds, a susceptible-infectious-removed (SIR) model with environmental transmission, and disease transmission due to bird dispersal between grid cells. The model will be parameterized using published data, expert opinions and literature estimates. Calibration and sensitivity analysis of main parameters, such as the infectious period and virus shedding rate of different bird species, will be implemented once the model is complete.
Preliminary results were obtained using model simulations for one iteration. The model outputs identified high-prevalence areas and periods, and the changes in simulated prevalence for the study period was compared to reported HPAI incidence in passively surveyed wild birds. We intend to use the spatio-temporal model to evaluate the risk of HPAI virus transmission and help Danish farmers and veterinary authorities to allocate resources to prevent potential outbreaks.