ArticleScientific reports2018
Using the Baidu Search Index to Predict the Incidence of HIV/AIDS in China.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 50 citations in OpenAlex.
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- Deep learning models for hepatitis E incidence prediction leveraging Baidu index.BMC public health · 2024Article
- 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
- Anti-social behaviour and economic decision-making: Panel experimental evidence in the wake of COVID-19.Journal of economic behavior & organization · 2023Article
- Predicting pulmonary tuberculosis incidence in China using Baidu search index: an ARIMAX model approach.Environmental health and preventive medicine · 2023Article
- Multi-Clinical Factors Combined with an Artificial Intelligence Algorithm Diagnosis Model for HIV-Infected People with Bloodstream Infection.Infection and drug resistance · 2023Article
- Using the Baidu index to predict trends in the incidence of tuberculosis in Jiangsu Province, China.Frontiers in public health · 2023Article
- Increasing public concern on insomnia during the COVID-19 outbreak in China: An info-demiology study.Heliyon · 2022Article
- Using the Baidu index to understand Chinese interest in thyroid related diseases.Scientific reports · 2022Article
- Detecting epidemiological relevance of adenoid hypertrophy, rhinosinusitis, and allergic rhinitis through an Internet search.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2022Article
- Online public attention toward allergic rhinitis in Wuhan, China: Infodemiology study using Baidu index and meteorological data.Frontiers in public health · 2022Article
- Enhancing Influenza Epidemics Forecasting Accuracy in China with Both Official and Unofficial Online News Articles, 2019-2020.International journal of environmental research and public health · 2021Article
- Turn to the Internet First? Using Online Medical Behavioral Data to Forecast COVID-19 Epidemic Trend.Information processing & management · 2021Article
- Using Baidu search values to monitor and predict the confirmed cases of COVID-19 in China: - evidence from Baidu index.BMC infectious diseases · 2021Article
- Search trends and prediction of human brucellosis using Baidu index data from 2011 to 2018 in China.Scientific reports · 2020Article
- Article
- Prediction of hepatitis E using machine learning models.PloS one · 2020Article
- An Extensive Search Trends-Based Analysis of Public Attention on Social Media in the Early Outbreak of COVID-19 in China.Risk management and healthcare policy · 2020Article
Corrections and comments
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Authors and funding
14 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Based on a panel of 30 provinces and a timeframe from January 2009 to December 2013, we estimate the association between monthly human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) incidence and the relevant Internet search query volumes in Baidu, the most widely used search engine among the Chinese. The pooled mean group (PMG) model show that the Baidu search index (BSI) positively predicts the increase in HIV/AIDS incidence, with a 1% increase in BSI associated with a 2.1% increase in HIV/AIDS incidence on average. This study proposes a promising method to estimate and forecast the incidence of HIV/AIDS, a type of infectious disease that is culturally sensitive and highly unevenly distributed in China; the method can be taken as a complement to a traditional HIV/AIDS surveillance system.
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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.