ArticleChina CDC weekly2024
Drawing on the Development Experiences of Infectious Disease Surveillance Systems Around the World.
Article in China CDC weekly, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis 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
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in early warning systems for infectious disease surveillance: a systematic review.Frontiers in public health · 2025Pooled it
- An Open-Source Data Driven Hybrid Modeling System for Infectious Disease Surveillance and Early Warning.China CDC weekly · 2026Article
- Review
- Integrated surveillance and early warning system of emerging infectious diseases in China at community level: current status, gaps and perspectives.Science in One Health · 2025Review
- Integrated health surveillance and early warning systems in China under the One Health perspective: progress and challenges.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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
High-quality infectious disease surveillance systems are foundational to infectious disease prevention and control. Current major infectious disease surveillance systems globally can be categorized as either indicator-based, which are more specific, or event-based, which are more timely. Modern surveillance systems commonly utilize multi-source data, strengthened information sharing, advanced technology, and improved early warning accuracy and sensitivity. International experience may provide valuable insights for China. China's existing infectious disease surveillance systems require urgent enhancements to monitor emerging infectious diseases and improve the integration and learning capabilities of early warning models. Methods such as establishing multi-stage surveillance systems, promoting cross-sectoral and cross-provincial data sharing, applying advanced technologies like artificial intelligence, and cultivating professional talent should be adopted to enhance the development of intelligent and multipoint-triggered infectious disease surveillance systems in China.
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.