ArticleNPJ digital medicine2021
Using digital surveillance tools for near real-time mapping of the risk of infectious disease spread.
Article in NPJ digital medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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
25 citing papers in PubMed.
- Co-designing a public health data analytics platform.Nature medicine · 2025Article
- Bracing the artificial intelligence technology in viral infectious disease control.Infectious medicine · 2025Article
- Application of a Digital Injury-Surveillance Platform.JAMA network open · 2025Article
- The triple integration of data, users and policies required for successful climate health solutions.NPJ digital medicine · 2025Article
- The role of artificial intelligence and machine learning in predicting and combating antimicrobial resistance.Computational and structural biotechnology journal · 2025Review
- Strengthening Outbreak Detection in Africa to Achieve the 7-1-7 Global Framework: Challenges and Opportunities.Public health reviews · 2025Review
- Modelling the drivers of outbreak communication in online media news for improved event-based surveillance.PloS one · 2025Article
- Technological trends in epidemic intelligence for infectious disease surveillance: a systematic literature review.PeerJ. Computer science · 2025Article
- AI Horizons in Indian Healthcare: A Vision for Transformation and Equity.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine · 2024Article
- A GPT-based EHR modeling system for unsupervised novel disease detection.Journal of biomedical informatics · 2024Article
- Global Mpox spread due to increased air travel.Geospatial health · 2024Article
- Tumor Immunotherapy-Related Information on Internet-Based Videos Commonly Used by the Chinese Population: Content Quality Analysis.JMIR formative research · 2024Article
- Knowledge attributes of public health management information systems used in health emergencies: a scoping review.Frontiers in public health · 2024Article
- Prehospital Cardiac Arrest Should be Considered When Evaluating Coronavirus Disease 2019 Mortality in the United States.Methods of information in medicine · 2023Article
- Risk averse reproduction numbers improve resurgence detection.PLoS computational biology · 2023Article
- Editorial: Infectious Disease Surveillance Using Artificial Intelligence (AI) and its Role in Epidemic and Pandemic Preparedness.Medical science monitor : international medical journal of experimental and clinical research · 2023Article
- Predicting food crises using news streams.Science advances · 2023Article
- Artificial intelligence in public health: the potential of epidemic early warning systems.The Journal of international medical research · 2023Review
- Retrospective evaluation of real-time estimates of global COVID-19 transmission trends and mortality forecasts.PloS one · 2023Article
- Dissemination of information in event-based surveillance, a case study of Avian Influenza.PloS one · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
Data from digital disease surveillance tools such as ProMED and HealthMap can complement the field surveillance during ongoing outbreaks. Our aim was to investigate the use of data collected through ProMED and HealthMap in real-time outbreak analysis. We developed a flexible statistical model to quantify spatial heterogeneity in the risk of spread of an outbreak and to forecast short term incidence trends. The model was applied retrospectively to data collected by ProMED and HealthMap during the 2013-2016 West African Ebola epidemic and for comparison, to WHO data. Using ProMED and HealthMap data, the model was able to robustly quantify the risk of disease spread 1-4 weeks in advance and for countries at risk of case importations, quantify where this risk comes from. Our study highlights that ProMED and HealthMap data could be used in real-time to quantify the spatial heterogeneity in risk of spread of an outbreak.
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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.