Abstract
Disease outbreaks need to be detected in a timely manner for effective disease control. For disease surveillance, conventional statistical process control charts are often included in public health surveillance systems, without taking into account the complicated structure of the disease incidence data and/or additional covariate information. This chapter presents a novel prospective disease surveillance system, named BCEWMA (Biosurveillance via Covariate-Assisted Exponentially Weighted Moving Average Control Chart), which can accommodate seasonality and arbitrary distribution of disease incidence data. Methodologically, BCEWMA is based on the widely used exponentially weighted moving average control chart, incorporating useful information in covariates. This new surveillance system is applied to two real disease incidence datasets: one regarding the hand, foot and mouth disease in Sichuan province of China and the other about the influenza-like-illness in Florida. These real-data examples show the reliability and effectiveness of BCEWMA in disease outbreak detection.
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Yang, K., Qiu, P. (2020). BCEWMA: A New and Effective Biosurveillance System for Disease Outbreak Detection. In: Chen, X., Chen, (.DG. (eds) Statistical Methods for Global Health and Epidemiology. ICSA Book Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-35260-8_14
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DOI: https://doi.org/10.1007/978-3-030-35260-8_14
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