ArticleScientific reports2019
Predicting seasonal influenza epidemics using cross-hemisphere influenza surveillance data and local internet query data.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline 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
- Influenza-Like Illness Forecasting Using Multisource Data: Comparative Deep Learning Study.JMIR medical informatics · 2026Article
- Developing a Research Network of Early Warning Systems for Infectious Diseases Transmission Between China and Australia.China CDC weekly · 2024Article
- Predicting seasonal influenza outbreaks with regime shift-informed dynamics for improved public health preparedness.Scientific reports · 2024Article
- Does the Australian influenza season predict the Canadian influenza season? A qualitative comparison of seasons, 2014-2020.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2023Article
- Praemonitus praemunitus: can we forecast and prepare for future viral disease outbreaks?FEMS microbiology reviews · 2023Review
- Preparing for the Next Influenza Season: Monitoring the Emergence and Spread of Antiviral Resistance.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
- Detecting Elevated Air Pollution Levels by Monitoring Web Search Queries: Algorithm Development and Validation.JMIR formative research · 2022Article
- Developing spatio-temporal approach to predict economic dynamics based on online news.Scientific reports · 2022Article
- Economics of attention: The gender-based bing communication study on depression.SSM - population health · 2022Article
- A potential tool for predicting epidemic trends and outbreaks of scrub typhus based on Internet search big data analysis in Yunnan Province, China.Frontiers in public health · 2022Article
- A novel data-driven methodology for influenza outbreak detection and prediction.Scientific reports · 2021Article
- 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
- Declining interest in clinical imaging during the COVID-19 pandemic: An analysis of Google Trends data.Clinical imaging · 2021Article
- Cardiovascular-related health behaviors and lifestyle during the COVID-19 pandemic: An infodemiology study.American journal of preventive cardiology · 2021Article
- Survey data and human computation for improved flu tracking.Nature communications · 2021Article
- Weather Variability and COVID-19 Transmission: A Review of Recent Research.International journal of environmental research and public health · 2021Review
- Ontology-driven aspect-based sentiment analysis classification: An infodemiological case study regarding infectious diseases in Latin America.Future generations computer systems : FGCS · 2020Article
- Surveillance of early stage COVID-19 clusters using search query logs and mobile device-based location information.Scientific reports · 2020Article
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4 authors.
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Abstract
Can early warning systems be developed to predict influenza epidemics? Using Australian influenza surveillance and local internet search query data, this study investigated whether seasonal influenza epidemics in China, the US and the UK can be predicted using empirical time series analysis. Weekly national number of respiratory cases positive for influenza virus infection that were reported to the FluNet surveillance system in Australia, China, the US and the UK were obtained from World Health Organization FluNet surveillance between week 1, 2010, and week 9, 2018. We collected combined search query data for the US and the UK from Google Trends, and for China from Baidu Index. A multivariate seasonal autoregressive integrated moving average model was developed to track influenza epidemics using Australian influenza and local search data. Parameter estimates for this model were generally consistent with the observed values. The inclusion of search metrics improved the performance of the model with high correlation coefficients (China = 0.96, the US = 0.97, the UK = 0.96, p < 0.01) and low Maximum Absolute Percent Error (MAPE) values (China = 16.76, the US = 96.97, the UK = 125.42). This study demonstrates the feasibility of combining (Australia) influenza and local search query data to predict influenza epidemics a different (northern hemisphere) scales.
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