J Am Med Inform Assoc - Adjusting outbreak detection algorithms for surveillance during epidemic and non-epidemic periods.

Tópicos

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Resumo

Many aberration detection algorithms are used in infectious disease surveillance systems to assist in the early detection of potential outbreaks. In this study, we explored a novel approach to adjusting aberration detection algorithms to account for the impact of seasonality inherent in some surveillance data. By using surveillance data for hand-foot-and-mouth disease in Shandong province, China, we evaluated the use of seasonally-adjusted alerting thresholds with three aberration detection methods (C1, C2, and C3). We found that the optimal thresholds of C1, C2, and C3 varied between the epidemic and non-epidemic seasons of hand-foot-and-mouth disease, and the application of seasonally adjusted thresholds improved the performance of outbreak detection by maintaining the same sensitivity and timeliness while decreasing by nearly half the false alert rate during the non-epidemic season. Our preliminary findings suggest a general approach to improving aberration detection for outbreaks of infectious disease with seasonally variable incidence.

Resumo Limpo

mani aberr detect algorithm use infecti diseas surveil system assist earli detect potenti outbreak studi explor novel approach adjust aberr detect algorithm account impact season inher surveil data use surveil data handfootandmouth diseas shandong provinc china evalu use seasonallyadjust alert threshold three aberr detect method c c c found optim threshold c c c vari epidem nonepidem season handfootandmouth diseas applic season adjust threshold improv perform outbreak detect maintain sensit timeli decreas near half fals alert rate nonepidem season preliminari find suggest general approach improv aberr detect outbreak infecti diseas season variabl incid

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