Bayesian spatiotemporal modeling with sliding windows to correct reporting delays for real-time dengue surveillance in Thailand

Bayesian spatiotemporal modeling with sliding windows to correct reporting delays for real-time dengue surveillance in Thailand

Abstract Background The ability to produce timely and accurate estimation of dengue cases can significantly impact disease control programs. A key challenge for dengue control in Thailand is the systematic delay in reporting at different levels in the surveillance system. Efficient and reliable surv...

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Bibliographic Details
Main Authors: Chawarat Rotejanaprasert, Nattwut Ekapirat, Darin Areechokchai, Richard J. Maude
Format: Article
Language:English
Published: BMC 2020-03-01
Series:International Journal of Health Geographics
Subjects:
Real time
Dengue
Surveillance
Delay
Bayesian
Spatiotemporal
Online Access:http://link.springer.com/article/10.1186/s12942-020-00199-0

Internet

http://link.springer.com/article/10.1186/s12942-020-00199-0

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