Using deep ensemble for influenza-like illness consultation rate prediction

2021 ◽  
Vol 117 ◽  
pp. 369-386
Author(s):  
Endah Kristiani ◽  
Yuan-An Chen ◽  
Chao-Tung Yang ◽  
Chin-Yin Huang ◽  
Yu-Tse Tsan ◽  
...  
Keyword(s):  
Consultation Rate ◽  
Influenza Like Illness ◽  
Rate Prediction

The validity of emergency department influenza-like illness (ILI) for laboratory-confirmed influenza in children

2011 ◽  
Vol 4 (0) ◽  
Author(s):  
Carla Rodriguez ◽  
Janet Baseman ◽  
Danielle Zerr ◽  
Janet Englund ◽  
Ian Painter ◽  
...  
Keyword(s):  
Emergency Department ◽  
Influenza Like Illness

Case definition for real-time surveillance of influenza-like illness

2011 ◽  
Vol 4 (0) ◽  
Author(s):  
Dino Rumoro ◽  
Shital Shah ◽  
Julio Silva ◽  
Marilyn Hallock ◽  
Gillian Gibbs ◽  
...  
Keyword(s):  
Real Time ◽  
Case Definition ◽  
Influenza Like Illness

Derivation of New Surveillance System for Influenza-like Illness Using Claims Data 2014-2018 in Korea (Preprint)

2020 ◽  
Author(s):  
HeeKyung Choi ◽  
Won Suk Choi ◽  
Euna Han
Keyword(s):  
Surveillance System ◽  
Claims Data ◽  
Health Concern ◽  
Influenza Surveillance ◽  
Utilization Review ◽  
Surveillance Systems ◽  
Influenza Like Illness ◽  
System P ◽  
National Patient ◽  
Antitussive Agents

BACKGROUND Influenza is an important public health concern. A national surveillance system that easily and rapidly detects influenza epidemics is lacking. OBJECTIVE We assumed that the rate of influenza-like illness (ILI) related-claims is similar to the current ILI surveillance system. METHODS We used the Health Insurance Review and Assessment Service-National Patient Samples (HIRA-NPS), 2014-2018. We defined ILI-related claims as outpatient claims that contain both antipyretic and antitussive agents and calculated the weekly rate of ILI-related claims. We compared ILI-related claims and weekly ILI rates from clinical sentinel surveillance data. RESULTS We observed a strong correlation between the two surveillance systems each season. The absolute thresholds for the four-years were 84.64 and 86.19 cases claims per 1,000 claims for claims data and 12.27 and 16.82 per 1,000 patients for sentinel data (Figure 5). Both the claims and sentinel data surpassed the epidemic thresholds each season. The peak epidemic in the claims data was reached one to two weeks later than in the sentinel data. The epidemic patterns were more similar in the 2016-2017 and 2017-2018 seasons than the 2014-2015 and 2015-2016 seasons. CONCLUSIONS Based on hospital reports, ILI-related claims rates were similar to the ILI surveillance system. ILI claims data can be loaded to a drug utilization review system in Korea to make an influenza surveillance system.

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