ArticleJournal of medical Internet research2017
Identifying Potential Norovirus Epidemics in China via Internet Surveillance.
Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.
- Using internet-based query and climate data to predict climate-sensitive infectious disease risks: a systematic review of epidemiological evidence.International journal of biometeorology · 2021Pooled it
- The Application of Internet-Based Sources for Public Health Surveillance (Infoveillance): Systematic Review.Journal of medical Internet research · 2020Pooled it
- Deep learning models for hepatitis E incidence prediction leveraging Baidu index.BMC public health · 2024Article
- Increasing public concern on insomnia during the COVID-19 outbreak in China: An info-demiology study.Heliyon · 2022Article
- Bridging the Gap in End Tuberculosis Targets in the Elderly Population in Eastern China: Observational Study From 2015 to 2020.JMIR public health and surveillance · 2022Observational
- Short-Term Impacts of Meteorology, Air Pollution, and Internet Search Data on Viral Diarrhea Infection among Children in Jilin Province, China.International journal of environmental research and public health · 2021Article
- Forecasting Teleconsultation Demand Using an Ensemble CNN Attention-Based BILSTM Model with Additional Variables.Healthcare (Basel, Switzerland) · 2021Article
- Norovirus outbreak in a natural playground: A One Health approach.Zoonoses and public health · 2020Article
- Mathematical Modeling of COVID-19 Control and Prevention Based on Immigration Population Data in China: Model Development and Validation.JMIR public health and surveillance · 2020Article
- Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China.Scientific reports · 2020Article
- Article
- Integrating Smart Health in the US Health Care System: Infodemiology Study of Asthma Monitoring in the Google Era.JMIR public health and surveillance · 2018Article
- Article
- Social media posts and online search behaviour as early-warning system for MRSA outbreaks.Antimicrobial resistance and infection control · 2018Article
Corrections and comments
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
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