Journal
PLOS ONE
Volume 8, Issue 8, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0071803
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Funding
- Research and Promotion of Key Technology on Health Emergency Preparation and Dispositions [201202006]
- National Key Science and Technology Project on Infectious Disease Surveillance Technique Platform of China [2012ZX10004-201]
- Development of Early Warning Systems for Dengue Fever Based on Socio-ecological Factors [NHMRC APP1002608]
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We evaluated a novel strategy to improve the performance of outbreak detection algorithms, namely setting the alerting threshold separately in each region according to the disease incidence in that region. By using data on hand, foot and mouth disease in Shandong province, China, we evaluated the impact of disease incidence on the performance of outbreak detection algorithms (EARS-C1, C2 and C3). Compared to applying the same algorithm and threshold to the whole region, setting the optimal threshold in each region according to the level of disease incidence (i.e., high, middle, and low) enhanced sensitivity (C1: from 94.4% to 99.1%, C2: from 93.5% to 95.4%, C3: from 91.7% to 95.4%) and reduced the number of alert signals (the percentage of reduction is C1:4.3%, C2:11.9%, C3:10.3%). Our findings illustrate a general method for improving the accuracy of detection algorithms that is potentially applicable broadly to other diseases and regions.
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