The functions group identified requirements on outbreak detection and forecasting methods.
Sensitivity analyses can be used to vary the case detection rate and estimate the impact of case detection on outbreak detection performance.
Public health efforts to control and prevent norovirus illness have focused primarily on outbreak detection and control.
Therefore, system coordination to perform pathogen surveillance based on early detection of outbreaks is necessary.
Currently, anomaly detection methods include anomaly detection based on classification, anomaly detection based on the nearest neighbor method, anomaly detection based on clustering, statistical anomaly detection, anomaly detection based on information theory, spectral theory anomaly detection, and so on [1].
Thus validity of disease surveillance and outbreak detection based on laboratory detection is limited.
Although this evaluation used a large proportion of the available historical data, performance evaluation was only based on the detection of 15 outbreaks.
Acute disease outbreaks can often be immediately diagnosed based on the detection of clinical signs by farmers and veterinarians, while chronic and subclinical respiratory disorders are difficult to diagnose.
Seventh, the prevented outbreak costs were based on one single outbreak.
Many metrics for outbreak detection are based on month of outbreak (11, 14, 15, 17, 18, 34), whereas in nosocomial outbreaks greater attention to individual cases is probably warranted given the smaller numbers of patients involved, the possibility of early definitive intervention, and the comorbidities of infected patients.
