ReviewInfectious Disease Modelling2025
Global infectious disease early warning models: An updated review and lessons from the COVID-19 pandemic.
Review in Infectious Disease Modelling, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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.
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Who cites it
12 citing papers in PubMed.
- Quantitative risk assessment of avian influenza: A scoping review.Infectious Disease Modelling · 2026Review
- Development of Two Multienzyme Isothermal Rapid Amplification Techniques for the Rapid Visual Detection of Micropterus salmoides rhabdovirus.Journal of fish diseases · 2026Article
- Multisource Early Warning Framework Integrating Regional Pathogen Surveillance and Baidu Index Data for Respiratory Infectious Disease Prediction in Beijing: Retrospective Time-Series Modeling Study.JMIR formative research · 2026Article
- Mechanistic Understanding of Pandemic Dynamics: A Multiscale Algorithmic Framework.Life (Basel, Switzerland) · 2026Article
- Efficient reporting delay calibration in spatial metapopulation models for reconstructing cross-regional epidemic dynamics.Biosafety and health · 2026Article
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- Article
- Next-generation viral detection through AI-enhanced nanotechnology: advances, challenges, and future directions.Frontiers in molecular biosciences · 2026Article
- Reflections on predictive modeling for infectious diseases.Frontiers in public health · 2026Article
- Probability-Based Early Warning for Seasonal Influenza in China: Model Development Study.JMIR medical informatics · 2025Article
- Is Ghana Prepared for Another Arboviral Outbreak? Evaluating the 2024 Dengue Fever Outbreak in the Context of Past Yellow Fever, Influenza, and COVID-19 Outbreaks.Tropical medicine and infectious disease · 2025Review
- Leveraging Google search data for predictive surveillance of Mpox: Toward active outbreak prevention.Digital healthArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An early warning model for infectious diseases is a crucial tool for timely monitoring, prevention, and control of disease outbreaks. The integration of diverse multi-source data using big data and artificial intelligence techniques has emerged as a key approach in advancing these early warning models. This paper presents a comprehensive review of widely utilized early warning models for infectious diseases around the globe. Unlike previous review studies, this review encompasses newly developed approaches such as the combined model and Hawkes model after the COVID-19 pandemic, providing a thorough evaluation of their current application status and development prospects for the first time. These models not only rely on conventional surveillance data but also incorporate information from various sources. We aim to provide valuable insights for enhancing global infectious disease surveillance and early warning systems, as well as informing future research in this field, by summarizing the underlying modeling concepts, algorithms, and application scenarios of each model.
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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.