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A modelling approach for correcting reporting delays in disease surveillance data

Bastos, L. S., Economou, T., Gomes, M. F.C., Villela, D. A.M., Coelho, F. C., Cruz, O. G., Stoner, O. , Bailey, T. and Codeço, C. T. (2019) A modelling approach for correcting reporting delays in disease surveillance data. Statistics in Medicine, 38(22), pp. 4363-4377. (doi: 10.1002/sim.8303) (PMID:31292995) (PMCID:PMC6900153)

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Abstract

One difficulty for real-time tracking of epidemics is related to reporting delay. The reporting delay may be due to laboratory confirmation, logistical problems, infrastructure difficulties, and so on. The ability to correct the available information as quickly as possible is crucial, in terms of decision making such as issuing warnings to the public and local authorities. A Bayesian hierarchical modelling approach is proposed as a flexible way of correcting the reporting delays and to quantify the associated uncertainty. Implementation of the model is fast due to the use of the integrated nested Laplace approximation. The approach is illustrated on dengue fever incidence data in Rio de Janeiro, and severe acute respiratory infection data in the state of Paraná, Brazil.

Item Type:Articles
Additional Information:The authors would like to thank Marilia Carvalho for her support and comments. LSB, TE, and TB were partially funded by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) under grant 88881.068124/2014-01.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Stoner, Dr Oliver
Authors: Bastos, L. S., Economou, T., Gomes, M. F.C., Villela, D. A.M., Coelho, F. C., Cruz, O. G., Stoner, O., Bailey, T., and Codeço, C. T.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Statistics in Medicine
Publisher:Wiley
ISSN:0277-6715
ISSN (Online):1097-0258
Published Online:10 July 2019
Copyright Holders:Copyright © 2019 The Authors
First Published:First published in Statistics in Medicine 38(22): 4363-4377
Publisher Policy:Reproduced under a Creative Commons License
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