ArticleScientific reports2021
Forecasting influenza-like illness trends in Cameroon using Google Search Data.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.
What it found
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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
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The use of artificial intelligence based modelling techniques in One Health-related infectious disease studies in Sub-Saharan Africa: a review.Frontiers in artificial intelligence · 2026Pooled it
- The Characteristics, Uses, and Biases of Studies Related to Malignancies Using Google Trends: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Temporal epidemiology and multi-source forecasting of hemorrhagic fever with renal syndrome and leptospirosis in mainland China: An interpretable machine learning study.Preventive medicine reports · 2026Article
- Scoping review of artificial intelligence via mobile technology and social media for health in Africa.Nature communications · 2025Article
- Natural Language Processing Technologies for Public Health in Africa: Scoping Review.Journal of medical Internet research · 2025Article
- Public interest in online searching of asthma information: insights from a Google trends analysis.BMC pulmonary medicine · 2025Article
- Better data sets won't solve the problem - we need AI for Africa to be developed in Africa.Nature · 2024Article
- Prediction of influenza outbreaks in Fuzhou, China: comparative analysis of forecasting models.BMC public health · 2024Article
- Integrating Internet multisource big data to predict the occurrence and development of COVID-19 cryptic transmission.NPJ digital medicine · 2022Article
- From Outbreak to Near Disappearance: How Did Non-pharmaceutical Interventions Against COVID-19 Affect the Transmission of Influenza Virus?Frontiers in public health · 2022Article
- Monitoring Information-Seeking Patterns and Obesity Prevalence in Africa With Internet Search Data: Observational Study.JMIR public health and surveillance · 2021Observational
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Although acute respiratory infections are a leading cause of mortality in sub-Saharan Africa, surveillance of diseases such as influenza is mostly neglected. Evaluating the usefulness of influenza-like illness (ILI) surveillance systems and developing approaches for forecasting future trends is important for pandemic preparedness. We applied and compared a range of robust statistical and machine learning models including random forest (RF) regression, support vector machines (SVM) regression, multivariable linear regression and ARIMA models to forecast 2012 to 2018 trends of reported ILI cases in Cameroon, using Google searches for influenza symptoms, treatments, natural or traditional remedies as well as, infectious diseases with a high burden (i.e., AIDS, malaria, tuberculosis). The R
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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.