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March 31, 2015Biometrics19 citations

Statistical monitoring of the hand, foot and mouth disease in China

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JZJingnan ZhangYKYicheng KangYYYang Yang

Structured PICO

P
Population
Hand, Foot, and Mouth Disease (HFMD) surveillance data collected during 2008-2009 in China
I
Intervention
Three-step statistical procedure using nonparametric longitudinal data and time series analysis methods followed by a statistical process control (SPC) chart
O
Outcome
Detection of increasing trend of disease incidence rate

A novel three-step statistical process control procedure effectively detects early outbreaks of Hand, Foot, and Mouth Disease using complex surveillance data.

Abstract

In a period starting around 2007, the Hand, Foot, and Mouth Disease (HFMD) became wide-spreading in China, and the Chinese public health was seriously threatened. To prevent the outbreak of infectious diseases like HFMD, effective disease surveillance systems would be especially helpful to give signals of disease outbreaks as early as possible. Statistical process control (SPC) charts provide a major statistical tool in industrial quality control for detecting product defectives in a timely manner. In recent years, SPC charts have been used for disease surveillance. However, disease surveillance data often have much more complicated structures, compared to the data collected from industrial production lines. Major challenges, including lack of in-control data, complex seasonal effects, and spatio-temporal correlations, make the surveillance data difficult to handle. In this article, we propose a three-step procedure for analyzing disease surveillance data, and our procedure is demonstrated using the HFMD data collected during 2008-2009 in China. Our method uses nonparametric longitudinal data and time series analysis methods to eliminate the possible impact of seasonality and temporal correlation before the disease incidence data are sequentially monitored by a SPC chart. At both national and provincial levels, our proposed method can effectively detect the increasing trend of disease incidence rate before the disease becomes wide-spreading.

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Cite This Study

Zhang et al. (2015) studied this question.

synapsesocial.com/papers/6a6f5ef5fe4101aa97dfc3d2https://doi.org/10.1111/biom.12301
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