Summary
Geospatial
analysis of disease investigation data improves data standardisation
and validation and enhances pathogen detection. Grid-based surveillance
systems for Newcastle disease in southern California and for bovine
tuberculosis on Molokai Island, Hawaii, demonstrate the importance
of this approach to operational planning. In addition, as shown
by a bovine tuberculosis study in wildlife on Molokai Island, a
lattice grid can be used to develop zonal strategies for disease
regulatory actions. In risk mapping, disease risk distribution is
compared with the distribution of risk factors to identify potential
determinants of risk. This process is being applied to North American
waterfowl migratory routes to identify geographic areas with high
concentrations of migratory waterfowl so that a spatially targeted
sampling strategy for use in surveillance operations can be designed.
Finally, while farm location data are needed to model pathogen spread
through susceptible animal populations, this information is generally
unavailable to analysts and modellers. Recently, a farm location
and animal population simulator application was developed in which
agricultural census data is distributed to create a farm location
dataset representative of an agricultural commodity within a specific
geographic area.
Keywords
Bovine
tuberculosis, Disease surveillance, Geographic information system,
Geospatial analysis, Hawaii, Migratory birds, Newcastle disease,
Risk mapping, Spatial epidemiology, Simulation models, United States
of America, Waterfowl, Wildlife.
|