SynthesisBMC public health2024
Reviewing the progress of infectious disease early warning systems and planning for the future.
Synthesis in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 3 of them syntheses that pooled it.
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
16 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Challenges and Strategies for the Development and Implementation of Climate-Informed Early Warning Systems for Vector-Borne Diseases: A Systematic Review.Tropical medicine & international health : TM & IH · 2026Pooled it
- Applications and challenges of biomarker-based predictive models in proactive health management.Frontiers in public health · 2025Pooled it
- Artificial intelligence in early warning systems for infectious disease surveillance: a systematic review.Frontiers in public health · 2025Pooled it
- Review
- Electronic Health Records and Their Role in the Surveillance of Infectious Disease.Mayo Clinic proceedings. Digital health · 2026Review
- Emerging and re-emerging vector-borne and other zoonotic RNA viruses: pathogenesis, climate-driven dynamics, and strategies for global control.Frontiers in microbiology · 2026Review
- Global region-specific influenza early warning by establishing an epidemic intensity threshold system: a modeling study.Frontiers in public health · 2026Article
- WHO priority pathogens, ESKAPE bacteria, and antimicrobial resistance surveillance in household wastewater, Gombe, Nigeria.Access microbiology · 2026Article
- Reflections on predictive modeling for infectious diseases.Frontiers in public health · 2026Article
- The potential of wastewater monitoring as a novel surveillance tool for early warning ofEmerging microbes & infections · 2025Article
- Hierarchical signal amplification for regional infectious disease risk assessment: A multidimensional approach from urban China.Infectious Disease Modelling · 2025Article
- Hotspots and Trends in Research on Early Warning of Infectious Diseases: A Bibliometric Analysis Using CiteSpace.Healthcare (Basel, Switzerland) · 2025Article
- Effectiveness of a 2-dose varicella vaccination program in Changzhou, China, during the transitional period (2017-2022): a registry-based case-cohort study.BMC public health · 2025Article
- Article
- Incidence of acute hemorrhagic conjunctivitis in Chongqing: a forecasting study based on mathematical models.Frontiers in public health · 2025Article
- Advancing One Health implementation and technological innovation in China: a technology assessment approach.Science in One Health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
backgroundPast reviews of infectious disease early warning systems have encountered some limitations, such as a focus on specific diseases or regions in certain studies and constraints imposed by time delays in others. This study conducts a comprehensive analysis of infectious disease early warning systems, with a particular emphasis on assessing the development of these systems in the recent five years (2019 to 2023). The goal is to provide insights for future related research.
methodsA comprehensive retrospective review was undertaken, utilizing data sourced from four prominent databases: WanFang Data, China National Knowledge Infrastructure (CNKI), Web of Science, and PubMed. Following a meticulous classification process, a total of 49 articles aligning with our inclusion criteria were identified. To streamline the data collection and organization process, standardized extraction forms were employed, and data were efficiently organized using Microsoft Excel spreadsheet.
resultsThis study uncovered various warning systems, including health departments, hospitals, social media platforms, statistical bureaus, meteorological departments, and wastewater monitoring systems. Drawbacks of traditional manual and statistical models included slow responsiveness and a surge in suspected cases. In contrast, hospital-based systems utilizing blockchain and smart contract technologies efficiently shared patient data, facilitating precise disease identification. Social media systems harnessed sentiment analysis for outbreak prediction, while statistical bureau systems integrated economic and population data for a novel perspective. Meteorological systems served as valuable complements, particularly for locally transmitted diseases. Wastewater monitoring systems added support by detecting crucial biological markers.
conclusionThis article conducts an in-depth analysis of infectious disease early warning systems, including systems based on various data sources. Future efforts should integrate new technologies, along with healthcare and social data, to enhance the capabilities of early warning and prediction.
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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.