Summary 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.
Keywords
Avian
influenza, Epidemiology, Geographic information system, Romania,
Surveillance.
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