ArticlePLoS neglected tropical diseases2017
Dengue Baidu Search Index data can improve the prediction of local dengue epidemic: A case study in Guangzhou, China.
Article in PLoS neglected tropical diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 4 of them syntheses that pooled it.
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Who cites it
38 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- 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
- Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review.PLoS neglected tropical diseases · 2022Pooled it
- 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
- Evaluating the effects of control interventions and estimating the inapparent infections for dengue outbreak in Hangzhou, China.PloS one · 2019Trial
- An ARIMAX model integrating Baidu index for improved hand, foot, and mouth disease incidence prediction.Scientific reports · 2026Article
- Early warning of hepatitis B epidemics in Henan Province, China, from 2014 to 2023 based on Baidu Index and Bayesian Structural Time Series model.Archives of public health = Archives belges de sante publique · 2026Article
- Early prediction of the outbreak risk of dengue fever in Ba Ria-Vung Tau province, Vietnam: An analysis based on Google trends and statistical models.Infectious Disease Modelling · 2025Article
- Outdoor Artificial Light at Night and Insomnia-Related Social Media Posts.JAMA network open · 2024Article
- Anti-social behaviour and economic decision-making: Panel experimental evidence in the wake of COVID-19.Journal of economic behavior & organization · 2023Article
- Predicting COVID-19 using lioness optimization algorithm and graph convolution network.Soft computing · 2023Article
- Predicting pulmonary tuberculosis incidence in China using Baidu search index: an ARIMAX model approach.Environmental health and preventive medicine · 2023Article
- Collaboration between meteorology and public health: Predicting the dengue epidemic in Guangzhou, China, by meteorological parameters.Frontiers in cellular and infection microbiology · 2022Article
- Online public attention toward allergic rhinitis in Wuhan, China: Infodemiology study using Baidu index and meteorological data.Frontiers in public health · 2022Article
- Internet search data with spatiotemporal analysis in infectious disease surveillance: Challenges and perspectives.Frontiers in public health · 2022Article
- The impacts of precipitation patterns on dengue epidemics in Guangzhou city.International journal of biometeorology · 2021Article
- Early warning systems (EWSs) for chikungunya, dengue, malaria, yellow fever, and Zika outbreaks: What is the evidence? A scoping review.PLoS neglected tropical diseases · 2021Article
- Using Search Trends to Analyze Web-Based Interest in Lower Urinary Tract Symptoms-Related Inquiries, Diagnoses, and Treatments in Mainland China: Infodemiology Study of Baidu Index Data.Journal of medical Internet research · 2021Article
- Predicting seasonal influenza using supermarket retail records.PLoS computational biology · 2021Article
- Estimation of Asthma Symptom Onset Using Internet Search Queries: Lag-Time Series Analysis.JMIR public health and surveillance · 2021Article
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14 authors.
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Abstract
backgroundDengue fever (DF) in Guangzhou, Guangdong province in China is an important public health issue. The problem was highlighted in 2014 by a large, unprecedented outbreak. In order to respond in a more timely manner and hence better control such potential outbreaks in the future, this study develops an early warning model that integrates internet-based query data into traditional surveillance data. METHODOLOGY AND PRINCIPAL
findingsA Dengue Baidu Search Index (DBSI) was collected from the Baidu website for developing a predictive model of dengue fever in combination with meteorological and demographic factors. Generalized additive models (GAM) with or without DBSI were established. The generalized cross validation (GCV) score and deviance explained indexes, intraclass correlation coefficient (ICC) and root mean squared error (RMSE), were respectively applied to measure the fitness and the prediction capability of the models. Our results show that the DBSI with one-week lag has a positive linear relationship with the local DF occurrence, and the model with DBSI (ICC:0.94 and RMSE:59.86) has a better prediction capability than the model without DBSI (ICC:0.72 and RMSE:203.29).
conclusionsOur study suggests that a DSBI combined with traditional disease surveillance and meteorological data can improve the dengue early warning system in Guangzhou.
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