ArticleEPJ data science2015
Enhancing disease surveillance with novel data streams: challenges and opportunities.
Article in EPJ data science, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 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
85 citing papers in PubMed, 1 synthesis or guideline pooled it.
- What can internet users' behaviours reveal about the mental health impacts of the COVID-19 pandemic? A systematic review.Public health · 2021Pooled it
- Implementation of AESOP early-warning system for respiratory disease: a pilot and validation study using routinely collected data in Amazonas, Brazil.Lancet regional health. Americas · 2026Article
- Comprehensive age-period-cohort analysis of global pancreatitis burden and socioeconomic disparities (1990-2021).BMC gastroenterology · 2025Article
- Estimating behavioural relaxation induced by COVID-19 vaccines in the first months of their rollout.PLoS computational biology · 2025Article
- Modeling Intraday Aedes-human exposure dynamics enhances dengue risk prediction.Scientific reports · 2025Article
- Pharmacovigilance in the Age of Legalized Cannabis: Using Social Media to Monitor Drug-Drug Interactions Between Immunosuppressants and Cannabis-Derived Products.Drug safety · 2025Article
- Harnessing Telehealth: Improving Epidemic Prediction and Response.American journal of public health · 2024Article
- A Novel Approach for the Early Detection of Medical Resource Demand Surges During Health Care Emergencies: Infodemiology Study of Tweets.JMIR formative research · 2024Article
- Modern technologies and solutions to enhance surveillance and response systems for emerging zoonotic diseases.Science in One Health · 2024Review
- Operationalizing cultural adaptation to climate change: contemporary examples from United States agriculture.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Predicting the dengue cluster outbreak dynamics in Yogyakarta, Indonesia: a modelling study.The Lancet regional health. Southeast Asia · 2023Article
- Mpox Panic, Infodemic, and Stigmatization of the Two-Spirit, Lesbian, Gay, Bisexual, Transgender, Queer or Questioning, Intersex, Asexual Community: Geospatial Analysis, Topic Modeling, and Sentiment Analysis of a Large, Multilingual Social Media Database.Journal of medical Internet research · 2023Article
- Mining Google Trends data for nowcasting and forecasting colorectal cancer (CRC) prevalence.PeerJ. Computer science · 2023Article
- Crime, inequality and public health: a survey of emerging trends in urban data science.Frontiers in big data · 2023Review
- State-Level COVID-19 Symptom Searches and Case Data: Quantitative Analysis of Political Affiliation as a Predictor for Lag Time Using Google Trends and Centers for Disease Control and Prevention Data.JMIR formative research · 2022Article
- Dynamic downscaling and daily nowcasting from influenza surveillance data.Statistics in medicine · 2022Article
- Spatial aggregation choice in the era of digital and administrative surveillance data.PLOS digital health · 2022Article
- Exploring the Relationship among Human Activities, COVID-19 Morbidity, and At-Risk Areas Using Location-Based Social Media Data: Knowledge about the Early Pandemic Stage in Wuhan.International journal of environmental research and public health · 2022Article
- Addressing the socioeconomic divide in computational modeling for infectious diseases.Nature communications · 2022Article
- The Volume and Tone of Twitter Posts About Cannabis Use During Pregnancy: Protocol for a Scoping Review.JMIR research protocols · 2022Article
25 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
36 authors.
Funding
Abstract
Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions: What are the opportunities for using NDS and what are the minimal tests of validity and utility that must be applied when using NDS? Identifying these opportunities will necessitate the involvement of public health authorities and an appreciation of the diversity of objectives and scales across agencies at different levels (local, state, national, international). We present the case that clearly articulating surveillance objectives and systematically evaluating NDS and comparing the performance of NDS to existing surveillance data and alternative NDS data is critical and has not sufficiently been addressed in many applications of NDS currently in the literature.
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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.