Mixture Likelihood Ratio Scan Statistic for Disease Outbreak Detection

Details Mixture Likelihood Ratio Scan Statistic for Disease Outbreak Detection Mixture Likelihood Ratio Scan Statistic for Disease Outbreak Detection

2012-01-18

arxiv.org/abs/1201.3937v1

Statistics

Methodology

The research was performed in connection with a technical contest put on by the International Society for Disease Surveillance

Scientific paper

Early detection of disease outbreaks is of paramount importance to implementing intervention strategies to mitigate the severity and duration of the outbreak. We build methodology that utilizes the characteristic profile of disease outbreaks to reduce the time to detection and false positive rate. We model daily counts through a Poisson distribution with additive background plus outbreak components. The outbreak component has a parametric form with unknown underlying parameters. A mixture likelihood ratio scan statistic is developed to maximize parameters over a window in time. This provides an alert statistic with early time to detection and low false positive rate. The methodology is demonstrated on three simulated data sets meant to represent E. coli, Cryptosporidium, and Influenza outbreaks.

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