Author
Listed:
- Yunzhou Fan
- Ying Wang
- Hongbo Jiang
- Wenwen Yang
- Miao Yu
- Weirong Yan
- Vinod K Diwan
- Biao Xu
- Hengjin Dong
- Lars Palm
- Shaofa Nie
Abstract
Background: Syndromic surveillance promotes the early detection of diseases outbreaks. Although syndromic surveillance has increased in developing countries, performance on outbreak detection, particularly in cases of multi-stream surveillance, has scarcely been evaluated in rural areas. Objective: This study introduces a temporal simulation model based on healthcare-seeking behaviors to evaluate the performance of multi-stream syndromic surveillance for influenza-like illness. Methods: Data were obtained in six towns of rural Hubei Province, China, from April 2012 to June 2013. A Susceptible-Exposed-Infectious-Recovered model generated 27 scenarios of simulated influenza A (H1N1) outbreaks, which were converted into corresponding simulated syndromic datasets through the healthcare-behaviors model. We then superimposed converted syndromic datasets onto the baselines obtained to create the testing datasets. Outbreak performance of single-stream surveillance of clinic visit, frequency of over the counter drug purchases, school absenteeism, and multi-stream surveillance of their combinations were evaluated using receiver operating characteristic curves and activity monitoring operation curves. Results: In the six towns examined, clinic visit surveillance and school absenteeism surveillance exhibited superior performances of outbreak detection than over the counter drug purchase frequency surveillance; the performance of multi-stream surveillance was preferable to signal-stream surveillance, particularly at low specificity (Sp
Suggested Citation
Yunzhou Fan & Ying Wang & Hongbo Jiang & Wenwen Yang & Miao Yu & Weirong Yan & Vinod K Diwan & Biao Xu & Hengjin Dong & Lars Palm & Shaofa Nie, 2014.
"Evaluation of Outbreak Detection Performance Using Multi-Stream Syndromic Surveillance for Influenza-Like Illness in Rural Hubei Province, China: A Temporal Simulation Model Based on Healthcare-Seekin,"
PLOS ONE, Public Library of Science, vol. 9(11), pages 1-13, November.
Handle:
RePEc:plo:pone00:0112255
DOI: 10.1371/journal.pone.0112255
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