Summary
Objectives:
The application of epidemic models during the first days following the confirmation
of a virus outbreak should significantly contribute to minimize its costs. Here we
describe the first version of a decision-support system for the calculation of the
airborne spread of a virus and its application to foot-and-mouth disease (FMD). The
goal is to provide geographical maps depicting infection risk for various animal species
to support the national health authorities.
Methods:
The major tool of the decision-support system is a specific epidemic (or atmospheric)
model: A so-called Gaussian dispersion model to calculate 3-dimensional virus plumes.
Additional tools providing input data and visualizing the output are: A veterinary
data base of geo-referenced premises, a geographical information system (GIS), and,
as an external part running at the National Weather Service, a numerical weather prediction
(NWP) model. To demonstrate the features of the decision-support system a pilot study
in Styria, Austria, has been performed simulating an artificial FMD outbreak.
Results:
One result of this simulation experiment is the determination of neighboring premises
at which animals are at risk to be infected. Particular attention has been turned
to cattle, sheep and swine. Using actual hourly NWP data from April 25, 2003, and
a source of ten swine excreting a virus, cattle have been estimated to be at risk
downwind 1,000-12,000 m, sheep 200-1,300 m, and swines 70-330 m.
Conclusions:
A system for real-time risk assessment of the airborne spread of a virus, applied
to FMD, was introduced. Due to the forcing of the Gaussian dispersion model with NWP
data, it is designed to run in both analysis and forecast mode. The system was applied
for the first time during the Austrian real-time exercise on FMD, instructed by the
European Union, in November 2004.
Keywords
Risk assessment - airborne transmission of a virus - Gaussian dispersion model - foot-and-mouth
disease - geographical information systems - veterinary epidemiology