ArticleScientific reports2020
Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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29 citing papers in PubMed, 54 citations in OpenAlex.
- Forecasting seasonal allergic rhinitis through integrated analysis of social media and online drug sales data.The World Allergy Organization journal · 2026Article
- 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
- Discussion of the public interest in arthroscopy based on the Baidu index and its implications for nursing care.World journal of orthopedics · 2025Article
- Public concerns analysis and early warning of Mpox based on network data platforms-taking Baidu and WeChat as example.Frontiers in public health · 2025Article
- Deep learning models for hepatitis E incidence prediction leveraging Baidu index.BMC public health · 2024Article
- Predictive analysis and correlational exploration of public and academic attention in secondary vocational education.Heliyon · 2024Article
- The influencing mechanism of scenic spot online attention and tourists' purchase behavior: an AISAS model based investigation.Frontiers in psychology · 2024Article
- Early Warning and Prediction of Scarlet Fever in China Using the Baidu Search Index and Autoregressive Integrated Moving Average With Explanatory Variable (ARIMAX) Model: Time Series Analysis.Journal of medical Internet research · 2023Article
- Article
- Using Baidu Index Data to Improve Chickenpox Surveillance in Yunnan, China: Infodemiology Study.Journal of medical Internet research · 2023Article
- The Effects of Online Health Information-Seeking Behavior on Sexually Transmitted Disease in China: Infodemiology Study of the Internet Search Queries.Journal of medical Internet research · 2023Article
- Predicting COVID-19 using lioness optimization algorithm and graph convolution network.Soft computing · 2023Article
- Influenza surveillance with Baidu index and attention-based long short-term memory model.PloS one · 2023Article
- Using the Baidu index to predict trends in the incidence of tuberculosis in Jiangsu Province, China.Frontiers in public health · 2023Article
- Brucellosis: epidemiology, pathogenesis, diagnosis and treatment-a comprehensive review.Annals of medicine · 2023Review
- Impact of the COVID-19 Pandemic on Meal Gathering in China.International journal of environmental research and public health · 2022Article
- The research on TBATS and ELM models for prediction of human brucellosis cases in mainland China: a time series study.BMC infectious diseases · 2022Article
- Incidence of pulmonary tuberculosis under the regular COVID-19 epidemic prevention and control in China.BMC infectious diseases · 2022Article
- Human brucellosis: Widespread information deficiency hinders an understanding of global disease frequency.PLoS neglected tropical diseases · 2022Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reporting on brucellosis, a relatively rare infectious disease caused by Brucella, is often delayed or incomplete in traditional disease surveillance systems in China. Internet search engine data related to brucellosis can provide an economical and efficient complement to a conventional surveillance system because people tend to seek brucellosis-related health information from Baidu, the largest search engine in China. In this study, brucellosis incidence data reported by the CDC of China and Baidu index data were gathered to evaluate the relationship between them. We applied an autoregressive integrated moving average (ARIMA) model and an ARIMA model with Baidu search index data as the external variable (ARIMAX) to predict the incidence of brucellosis. The two models based on brucellosis incidence data were then compared, and the ARIMAX model performed better in all the measurements we applied. Our results illustrate that Baidu index data can enhance the traditional surveillance system to monitor and predict brucellosis epidemics in China.
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