Abstract:
:In England and Wales, a large-scale multiple statistical surveillance system for infectious disease outbreaks has been in operation for nearly two decades. This system uses a robust quasi-Poisson regression algorithm to identify abberrances in weekly counts of isolates reported to the Health Protection Agency. In this paper, we review the performance of the system with a view to reducing the number of false reports, while retaining good power to detect genuine outbreaks. We undertook extensive simulations to evaluate the existing system in a range of contrasting scenarios. We suggest several improvements relating to the treatment of trends, seasonality, re-weighting of baselines and error structure. We validate these results by running the existing and proposed new systems in parallel on real data. We find that the new system greatly reduces the number of alarms while maintaining good overall performance and in some instances increasing the sensitivity.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Noufaily A,Enki DG,Farrington P,Garthwaite P,Andrews N,Charlett Adoi
10.1002/sim.5595subject
Has Abstractpub_date
2013-03-30 00:00:00pages
1206-22issue
7eissn
0277-6715issn
1097-0258journal_volume
32pub_type
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