Geographic information system-based avian influenza surveillance systems for village poultry in Romania.
The analysis of surveillance data facilitates the planning, implementation and evaluation of disease control programmes. Geographic information systems (GIS) have several functions, including input (database functions), analysis (interpolation, cluster detection, identification of spatial risk factors) and output (sampling design, disease risk maps). This paper focuses on visualisation techniques that enable improved design and evaluation of surveillance data. Data generated within a pilot GIS-based surveillance programme for avian influenza in village poultry in the Romanian county of Tulcea is used as an example. The use of kriging helped highlight areas in the country where sampling potentially was sub-optimal, and error maps demonstrated the level of confidence that can be placed in serological surveillance results in different localities. Disease surveillance systems traditionally have not focused on the issues of disease risk and sample size visualisation. Standards need to be developed on how sampling and disease data generated within animal health surveillance systems are analysed and presented. This is particularly important for transboundary diseases such as avian influenza.
Ward
Michael P
MP
Texas A&M University College of Veterinary Medicine and Biomedical Sciences, MS 4458, College Station, TX 77843-4458, United States of America. mward@cvm.tamu.edu