A Simulation-Based Study on the Comparison of Statistical and Time Series Forecasting Methods for Early Detection of Infectious Disease Outbreaks

International Journal of Environmental Research and Public Health
Eunjoo YangKeun Ho Ryu

Abstract

Early detection of infectious disease outbreaks is one of the important and significant issues in syndromic surveillance systems. It helps to provide a rapid epidemiological response and reduce morbidity and mortality. In order to upgrade the current system at the Korea Centers for Disease Control and Prevention (KCDC), a comparative study of state-of-the-art techniques is required. We compared four different temporal outbreak detection algorithms: the CUmulative SUM (CUSUM), the Early Aberration Reporting System (EARS), the autoregressive integrated moving average (ARIMA), and the Holt-Winters algorithm. The comparison was performed based on not only 42 different time series generated taking into account trends, seasonality, and randomly occurring outbreaks, but also real-world daily and weekly data related to diarrhea infection. The algorithms were evaluated using different metrics. These were namely, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1 score, symmetric mean absolute percent error (sMAPE), root-mean-square error (RMSE), and mean absolute deviation (MAD). Although the comparison results showed better performance for the EARS C3 method with respect to the other algorith...Continue Reading

References

Aug 12, 1999·Statistics in Medicine·G RossiM Marchi
Jan 25, 2003·BMC Medical Informatics and Decision Making·Ben Y Reis, Kenneth D Mandl
Mar 6, 2007·Statistics in Medicine·Howard S BurkomGalit Shmueli
Feb 2, 2008·Statistics in Medicine·Ronald D FrickerDavid A Dunfee
Sep 4, 2012·Statistics in Medicine·Angela NoufailyAndré Charlett

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Citations

Aug 15, 2018·International Journal of Environmental Research and Public Health·Xueli WangGexin Xiao
Mar 17, 2020·BMC Infectious Diseases·Xinyu FangChangjun Bao

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Software Mentioned

R surveillance package
EARS
CUSUM
ARIMA
R

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