August 19, 2013PLoS ONEOpen Access

Improving the Performance of Outbreak Detection Algorithms by Classifying the Levels of Disease Incidence

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Why the study?

Does setting alerting thresholds according to regional disease incidence improve the performance of outbreak detection algorithms for HFMD?

Population

138,593 cases and 108 outbreaks of hand, foot and mouth disease reported between January and December 2009…

Comparison

Setting the optimal alerting threshold for… vs Applying the same algorithm and optimal…

Design

Other

Authors

HZHonglong ZhangHuazhong University of Science and Technology SLShengjie LaiUniversity of Southampton LWLiping WangHunan University of Traditional Chinese Medicine

Discussion

Member takes

Implication

May support incidence-stratified thresholds to cut HFMD alerts without delaying detection; leaves open prospective validation in other surveillance systems.

Structured PICO

Does setting alerting thresholds according to regional disease incidence improve the performance of outbreak detection algorithms for HFMD?

Population

138,593 cases and 108 outbreaks of hand, foot and mouth disease (HFMD) reported between January and December 2009 across 142 counties in Shandong province, China.

Intervention

Setting the optimal alerting threshold for outbreak detection algorithms (EARS-C1, C2, and C3) separately in each region according to the level of disease incidence (high, middle, and low).

Comparator

Applying the same algorithm and optimal threshold to the whole region.

Outcome

Sensitivity, specificity, and time to detection (TTD) of the outbreak detection algorithms.surrogate

Optimizing surveillance alert thresholds by regional disease incidence categories improves the sensitivity and specificity of outbreak detection algorithms compared to using a single threshold across all regions.

Limitations

Used only one disease as an example, so results may not generalize to other diseases with a low incidence.
Did not consider other factors such as differences in population, case report timeliness and completeness, seasonality, and weekend effects.

Cite This Study

Zhang et al. (2013) studied this question.

synapsesocial.com/papers/6a7fdfb04fa3c9b321b9afae https://doi.org/10.1371/journal.pone.0071803

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Implication

May support incidence-stratified thresholds to cut HFMD alerts without delaying detection; leaves open prospective validation in other surveillance systems.

Improving the Performance of Outbreak Detection Algorithms by Classifying the Levels of Disease Incidence

Discussion

Member takes

Implication

Structured PICO

Limitations

Cite This Study

Improving the Performance of Outbreak Detection Algorithms by Classifying the Levels of Disease Incidence

Discussion

Member takes

Implication

Structured PICO

Limitations

Cite This Study

Also Consider

Also Consider