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Inclusion of the winter metrics in a conditional manner in the algorithm significantly reduced the number of false outbreak predictions.
The rate of false outbreak predictions at high-cover locations was reduced from 79% to 42% by including only locations with mild Winter Condition (Fig. 5b).
Consequently, the above approaches may result in false outbreak alarms or outbreaks that are overlooked, and subsequently the misuse of hospital resources or a missed opportunity for further case investigation [ 2] or prompt intervention, prevention, and control.
The findings from these models could be used in outbreak prediction models to reduce the number of false outbreak predictions and serve as a basis for additional investigation for case occurrence in other locations.
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The curves display the sensitivity rate on day three of the simulated outbreak in the non-flu season that is achieved for each pre-determined false positive rate.
This study is based on one data set with one type of simulated outbreak (approximately lognormal with varying numbers of days), one type of sequential test (Page's) and one nominal false alarm rate (one false alarm per year).
Italy's false 'Ebola outbreak' is spread by racists and conspiracy nuts.
The most notable improvement is in the precision of cluster locations detected, as DP algorithm tends to output fewer false-positive outbreak cells than the other algorithms.
During the Ebola outbreak false information contributed to the stigmatisation that healthcare workers and vulnerable communities felt.
Sanctions based on fears of an undetected outbreak (false negatives) encourage disclosure by reducing the relative cost of sanctions that follow a reported outbreak.
Previously: The False Widow Spider 'Outbreak' is Tabloid Bullshit.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com