Abstract
BackgroundNorovirus is a common virus that causes acute gastroenteritis worldwide, but a monitoring system for norovirus is unavailable in China.ObjectiveWe aimed to identify norovirus epidemics through Internet surveillance and construct an appropriate model to predict potential norovirus infections.MethodsThe norovirus-related data of a selected outbreak in Jiaxing Municipality, Zhejiang Province of China, in 2014 were collected from immediate epidemiological investigation, and the Internet search volume, as indicated by the Baidu Index, was acquired from the Baidu search engine. All correlated search keywords in relation to norovirus were captured, screened, and composited to establish the composite Baidu Index at different time lags by Spearman rank correlation. The optimal model was chosen and possibly predicted maps in Zhejiang Province were presented by ArcGIS software.ResultsThe combination of two vital keywords at a time lag of 1 day was ultimately identified as optimal (ρ=.924, P<.001). The exponential curve model was constructed to fit the trend of this epidemic, suggesting that a one-unit increase in the mean composite Baidu Index contributed to an increase of norovirus infections by 2.15 times during the outbreak. In addition to Jiaxing Municipality, Hangzhou Municipality might have had some potential epidemics in the study time from the predicted model.ConclusionsAlthough there are limitations with early warning and unavoidable biases, Internet surveillance may be still useful for the monitoring of norovirus epidemics when a monitoring system is unavailable.
Highlights
Acute gastroenteritis, inflammation of the gastrointestinal tract, is defined as the sudden onset of diarrhea, with or without signs of nausea, vomiting, fever, or abdominal pain [1,2]
Epidemiological Characteristics of the Norovirus Outbreak. This epidemic was first reported in Haiyan, followed by Haining, within the Jiaxing Municipality in Zhejiang Province of China
We used Internet-based surveillance to identify the association between possible norovirus case number and the fluctuant retrieval index of norovirus-related keywords from the Baidu search engine, and explored an optimal model with specific time lag for the prediction of norovirus epidemics
Summary
Inflammation of the gastrointestinal tract, is defined as the sudden onset of diarrhea, with or without signs of nausea, vomiting, fever, or abdominal pain [1,2]. A single-stranded RNA virus of the Caliciviridae family, is a leading cause of infectious acute gastroenteritis worldwide across all age groups, in health care and community settings [3,4]. Norovirus infection is viewed as a self-limited illness, it might be still responsible for severe dehydration, and even potential death, in children and the elderly population [7,8,9]. No obvious evidence supports the idea of there being a specific reservoir, and only the scattered speculation from available literature viewed immunocompromised individuals, elderly, and malnourished hosts as potential norovirus reservoirs [13]. Norovirus is a common virus that causes acute gastroenteritis worldwide, but a monitoring system for norovirus is unavailable in China
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