ArticleScientific reports2019
Avian Influenza A (H7N9) and related Internet search query data in China.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
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Who cites it
24 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.
- Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic.Journal of epidemiology and global health · 2024Pooled it
- Learning from pandemics: Feature selection and clustering for robust digital disease nowcasting.PloS one · 2026Article
- Discussion of the public interest in arthroscopy based on the Baidu index and its implications for nursing care.World journal of orthopedics · 2025Article
- Analysis of COVID-19 outbreak in Hubei province based on Tencent's location big data.Frontiers in public health · 2023Article
- Using geospatial social media data for infectious disease studies: a systematic review.International journal of digital earth · 2023Article
- Predicting pulmonary tuberculosis incidence in China using Baidu search index: an ARIMAX model approach.Environmental health and preventive medicine · 2023Article
- Seasonal Variation for Plantar Fasciitis: Evidence from Google Trends Search Query Data.Healthcare (Basel, Switzerland) · 2022Article
- Accurate Forecasting of Emergency Department Arrivals With Internet Search Index and Machine Learning Models: Model Development and Performance Evaluation.JMIR medical informatics · 2022Article
- Public Social Media Discussions on Agricultural Product Safety Incidents: Chinese African Swine Fever Debate on Weibo.Frontiers in psychology · 2022Article
- Online searching trend on Covid-19 using Google trend: infodemiological study in Malaysia.International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management · 2022Article
- Forecast of the COVID-19 Epidemic Based on RF-BOA-LightGBM.Healthcare (Basel, Switzerland) · 2021Article
- Role of Participatory Health Informatics in Detecting and Managing Pandemics: Literature Review.Yearbook of medical informatics · 2021Review
- Health Communication in COVID-19 Era: Experiences from the Italian VaccinarSì Network Websites.International journal of environmental research and public health · 2021Article
- Estimation of Asthma Symptom Onset Using Internet Search Queries: Lag-Time Series Analysis.JMIR public health and surveillance · 2021Article
- Detecting Topic and Sentiment Trends in Physician Rating Websites: Analysis of Online Reviews Using 3-Wave Datasets.International journal of environmental research and public health · 2021Article
- Effects of COVID-Induced Public Anxiety on European Stock Markets: Evidence From a Fear-Based Algorithmic Trading System.Frontiers in psychology · 2021Article
- Promoting Public Engagement during the COVID-19 Crisis: How Effective Is the Wuhan Local Government's Information Release?International journal of environmental research and public health · 2020Article
- Online Public Attention During the Early Days of the COVID-19 Pandemic: Infoveillance Study Based on Baidu Index.JMIR public health and surveillance · 2020Article
- Grappling With the COVID-19 Health Crisis: Content Analysis of Communication Strategies and Their Effects on Public Engagement on Social Media.Journal of medical Internet research · 2020Article
- Live poultry market closure and avian influenza A (H7N9) infection in cities of China, 2013-2017: an ecological study.BMC infectious diseases · 2020Article
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Authors and funding
6 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of Internet-based systems for infectious disease surveillance has been increasingly explored in recent years. However, few studies have used Internet search query or social media data to monitor spatial and temporal trends of avian influenza in China. This study investigated the potential of using search query and social media data in detecting and monitoring avian influenza A (H7N9) cases in humans in China. We collected weekly data on laboratory-confirmed H7N9 cases in humans, as well as H7N9-related Baidu Search Index (BSI) and Weibo Posting Index (WPI) data in China from 2013 to 2017, to explore the spatial and temporal trends of H7N9 cases and H7N9-related Internet search queries. Our findings showed a positive relationship of H7N9 cases with BSI and WPI search queries spatially and temporally. The outbreak threshold time and peak time of H7N9-related BSI and WPI searches preceded H7N9 cases in most years. Seasonal autoregressive integrated moving average (SARIMA) models with BSI (β = 0.008, p < 0.001) and WPI (β = 0.002, p = 0.036) were used to predict the number of H7N9 cases. Regression tree model analysis showed that the average H7N9 cases increased by over 2.4-fold (26.8/11) when BSI for H7N9 was > = 11524. Both BSI and WPI data could be used as indicators to develop an early warning system for H7N9 outbreaks in the future.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.