%0 Journal Article
%T Using GIS to create synthetic disease outbreaks
%A Rochelle E Watkins
%A Serryn Eagleson
%A Sam Beckett
%A Graeme Garner
%A Bert Veenendaal
%A Graeme Wright
%A Aileen J Plant
%J BMC Medical Informatics and Decision Making
%D 2007
%I BioMed Central
%R 10.1186/1472-6947-7-4
%X A state-transition model which simulates disease outbreaks in daily time steps using specified disease-specific parameters was developed to model the spread of infectious diseases transmitted by person-to-person contact. The software was developed using the MapBasic programming language for the MapInfo Professional geographic information system environment.The simulation model developed is a generalised and flexible model which utilises the underlying distribution of the population and incorporates patterns of disease spread that can be customised to represent a range of infectious diseases and geographic locations. This model provides a means to explore the ability of outbreak detection algorithms to detect a variety of events across a large number of stochastic replications where the influence of uncertainty can be controlled. The software also allows historical data which is free from known outbreaks to be combined with simulated outbreak data to produce files for algorithm performance assessment.This simulation model provides a flexible method to generate data which may be useful for the evaluation and comparison of outbreak detection algorithm performance.Identifying disease outbreaks early is critical for efficient infectious disease control. Currently, spatial data are collected but often not well utilised in routine infectious disease surveillance. As outbreaks are often characterised by the degree of spatial diffusion of cases, spatio-temporal surveillance algorithms are being developed in a number of countries. These spatio-temporal algorithms aim to facilitate the early detection of disease outbreaks which exhibit spatial clustering [1], such as those associated with person-to-person transmission of disease, or a localised source of infection.As work to develop spatio-temporal algorithms for the early detection of outbreaks of infectious disease continues, the importance of evaluating the performance of these algorithms increases. The evaluation process a
%U http://www.biomedcentral.com/1472-6947/7/4