ArticlePeerJ2018
Forecasting influenza epidemics by integrating internet search queries and traditional surveillance data with the support vector machine regression model in Liaoning, from 2011 to 2015.
Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed.
- A Deep Learning Framework for Using Search Engine Data to Predict Influenza-Like Illness and Distinguish Epidemic and Nonepidemic Seasons: Multifeature Time Series Analysis.Journal of medical Internet research · 2025Article
- A novel graph neural network based approach for influenza-like illness nowcasting: exploring the interplay of temporal, geographical, and functional spatial features.BMC public health · 2025Article
- Mapping the Characteristics of Respiratory Infectious Disease Epidemics in China Based on the Baidu Index from November 2022 to January 2023.China CDC weekly · 2024Article
- Exploring the Lagged Correlation Between Baidu Index and Influenza-Like Illness - China, 2014-2019.China CDC weekly · 2024Article
- A Predictive Model of the Start of Annual Influenza Epidemics.Microorganisms · 2024Article
- Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models.BMC public health · 2024Article
- The prediction of influenza-like illness using national influenza surveillance data and Baidu query data.BMC public health · 2024Article
- Influenza surveillance with Baidu index and attention-based long short-term memory model.PloS one · 2023Article
- Influenza surveillance systems using traditional and alternative sources of data: A scoping review.Influenza and other respiratory viruses · 2022Article
- Epidemiological trend in scarlet fever incidence in China during the COVID-19 pandemic: A time series analysis.Frontiers in public health · 2022Article
- Disaster and Pandemic Management Using Machine Learning: A Survey.IEEE internet of things journal · 2021Article
- Comparative analysis of machine learning approaches to analyze and predict the COVID-19 outbreak.PeerJ. Computer science · 2021Article
- Estimating the Long-Term Epidemiological Trends and Seasonality of Hemorrhagic Fever with Renal Syndrome in China.Infection and drug resistance · 2021Article
- Predictive Nomogram for the Prediction of Early Recurrence of Colorectal Cancer.International journal of general medicine · 2021Article
- Multi-step ahead meningitis case forecasting based on decomposition and multi-objective optimization methods.Journal of biomedical informatics · 2020Article
- Applying Machine Learning Models with An Ensemble Approach for Accurate Real-Time Influenza Forecasting in Taiwan: Development and Validation Study.Journal of medical Internet research · 2020Article
- A systematic review on integration mechanisms in human and animal health surveillance systems with a view to addressing global health security threats.One health outlook · 2020Review
- Estimating the Prevalence and Mortality of Coronavirus Disease 2019 (COVID-19) in the USA, the UK, Russia, and India.Infection and drug resistance · 2020Article
- Forecasting dengue and influenza incidences using a sparse representation of Google trends, electronic health records, and time series data.PLoS computational biology · 2019Article
- Comparative evaluation of time series models for predicting influenza outbreaks: application of influenza-like illness data from sentinel sites of healthcare centers in Iran.BMC research notes · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInfluenza epidemics pose significant social and economic challenges in China. Internet search query data have been identified as a valuable source for the detection of emerging influenza epidemics. However, the selection of the search queries and the adoption of prediction methods are crucial challenges when it comes to improving predictions. The purpose of this study was to explore the application of the Support Vector Machine (SVM) regression model in merging search engine query data and traditional influenza data.
methodsThe official monthly reported number of influenza cases in Liaoning province in China was acquired from the China National Scientific Data Center for Public Health from January 2011 to December 2015. Based on Baidu Index, a publicly available search engine database, search queries potentially related to influenza over the corresponding period were identified. An SVM regression model was built to be used for predictions, and the choice of three parameters (
resultsIn total, 17 search queries related to influenza were generated through the initial query selection approach and were adopted to construct the SVM regression model, including nine queries in the same month, three queries at a lag of one month, one query at a lag of two months and four queries at a lag of three months. The SVM model performed well when with the parameters (
conclusionsThe results demonstrated the feasibility of using internet search engine query data as the complementary data source for influenza surveillance and the efficiency of SVM regression model in tracking the influenza epidemics in Liaoning.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.