ArticleInformation processing & management2021
Turn to the Internet First? Using Online Medical Behavioral Data to Forecast COVID-19 Epidemic Trend.
Article in Information processing & management, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Changes to Public Health Surveillance Methods Due to the COVID-19 Pandemic: Scoping Review.JMIR public health and surveillance · 2024Article
- The predation relationship between online medical search and online medical consultation-empirical research based on Baidu platform data.Frontiers in public health · 2024Article
- Delay in seeking health care from community residents during a time with low prevalence of COVID-19: A cross-sectional national survey in China.Frontiers in public health · 2023Article
- Understanding Physicians' Motivation to Provide Healthcare Service Online in the Digital Age.International journal of environmental research and public health · 2022Article
- An easy numeric data augmentation method for early-stage COVID-19 tweets exploration of participatory dynamics of public attention and news coverage.Information processing & management · 2022Article
- A data-driven hybrid ensemble AI model for COVID-19 infection forecast using multiple neural networks and reinforced learning.Computers in biology and medicine · 2022Article
- Patient Activeness During Online Medical Consultation in China: Multilevel Analysis.Journal of medical Internet research · 2022Article
- Optimism and pessimism analysis using deep learning on COVID-19 related twitter conversations.Information processing & management · 2022Article
- Internet search data with spatiotemporal analysis in infectious disease surveillance: Challenges and perspectives.Frontiers in public health · 2022Article
- The Impact of Health Information Privacy Concerns on Engagement and Payment Behaviors in Online Health Communities.Frontiers in psychology · 2022Article
- Risk assessment model and application of COVID-19 virus transmission in closed environments at sea.Sustainable cities and society · 2021Article
- Article
- Monitoring Depression Trends on Twitter During the COVID-19 Pandemic: Observational Study.JMIR infodemiologyArticle
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The surveillance and forecast of newly confirmed cases are important to mobilize medical resources and facilitate policymaking during a public health emergency. Digital surveillance using data available online has increasingly become a trend with the advancement of the Internet. In this study, we assessed the predictive value of multiple online medical behavioral data, including online medical consultation (OMC), online medical appointment (OMA), and online medical search (OMS) for the regional outbreak of coronavirus disease 2019 in Shenzhen, China during January 1, 2020 to March 5, 2020. Multivariate vector autoregression models were used for the prediction. The results identified a novel predictor, OMC, which can forecast the disease trend up to 2 days ahead of the official reports of confirmed cases from the local health department. OMS data had relatively weaker predictive power than OMC in our model, and OMA data failed to predict the confirmed cases. This study highlights the importance of OMC data and has implication in providing evidence-based guidelines for local authorities to evaluate risks and allocate resources during the pandemic.
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