SynthesisJournal of epidemiology and global health2024
Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic.
Synthesis in Journal of epidemiology and global health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Granulomatous amoebic encephalitis: pathogenesis, diagnostic advances, therapeutic challenges, and emerging treatment strategies.Medical microbiology and immunology · 2026Review
- Review
- Respiratory virus surveillance in the post-pandemic era: challenges and opportunities for dashboard-based public health action.BMC proceedings · 2026Article
- Transforming Public Health Practice with Artificial Intelligence: A Framework-Driven Approach.Healthcare (Basel, Switzerland) · 2026Article
- Evolving Landscape of Emerging Virus Diagnosis: Challenges and Innovations.Molecular biotechnology · 2026Review
- Feasibility of AI-driven disease surveillance systems at international airports in sub-Saharan Africa: a narrative review.Frontiers in public health · 2026Review
- Public Search Behavior and Tuberculosis Cases in Indonesia 2019-2023: An Infodemiology Study Using Google Trends .F1000Research · 2026Article
- Integrating systems thinking for analyzing and designing national early warning surveillance for animal health: a perspective from Tanzania.Frontiers in veterinary science · 2026Article
- AI-Driven Smart Cockpit: Monitoring of Sudden Illnesses, Health Risk Intervention, and Future Prospects.Sensors (Basel, Switzerland) · 2025Review
- Infectious Disease Surveillance in the Era of Big Data and AI: Opportunities and Pitfalls.Cureus · 2025Review
- Machine Learning Prediction of Multidrug Resistance in Swine-DerivedVeterinary sciences · 2025Article
- Global infectious disease early warning models: An updated review and lessons from the COVID-19 pandemic.Infectious Disease Modelling · 2025Review
- Country-Specific Data and Priorities for Pertussis in Latin America: Recent Findings From the Global Pertussis Initiative.Open forum infectious diseases · 2025Review
- AI-driven epidemic intelligence: the future of outbreak detection and response.Frontiers in artificial intelligence · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The last decade has seen major advances and growth in internet-based surveillance for infectious diseases through advanced computational capacity, growing adoption of smart devices, increased availability of Artificial Intelligence (AI), alongside environmental pressures including climate and land use change contributing to increased threat and spread of pandemics and emerging infectious diseases. With the increasing burden of infectious diseases and the COVID-19 pandemic, the need for developing novel technologies and integrating internet-based data approaches to improving infectious disease surveillance is greater than ever. In this systematic review, we searched the scientific literature for research on internet-based or digital surveillance for influenza, dengue fever and COVID-19 from 2013 to 2023. We have provided an overview of recent internet-based surveillance research for emerging infectious diseases (EID), describing changes in the digital landscape, with recommendations for future research directed at public health policymakers, healthcare providers, and government health departments to enhance traditional surveillance for detecting, monitoring, reporting, and responding to influenza, dengue, and COVID-19.
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.