ReviewThe Journal of infectious diseases2016
Mind the Scales: Harnessing Spatial Big Data for Infectious Disease Surveillance and Inference.
Review in The Journal of infectious diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 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
31 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Ethical issues raised by artificial intelligence and big data in population health: a scoping review.Frontiers in sociology · 2025Pooled it
- Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic.Journal of epidemiology and global health · 2024Pooled it
- Article
- From infectious diseases to chronic diseases: the paradigm shift of spatial epidemiology in disease prevention and control.Frontiers in public health · 2025Review
- Spatial distribution and determinants of childhood vaccination refusal in the United States.Vaccine · 2023Article
- A novel textual track-data-based approach for estimating individual infection risk of COVID-19.Risk analysis : an official publication of the Society for Risk Analysis · 2023Article
- Using geospatial social media data for infectious disease studies: a systematic review.International journal of digital earth · 2023Article
- 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
- Spatiotemporal data mining: a survey on challenges and open problems.Artificial intelligence review · 2022Article
- Internet search data with spatiotemporal analysis in infectious disease surveillance: Challenges and perspectives.Frontiers in public health · 2022Article
- Using big data for evaluating development outcomes: A systematic map.Campbell systematic reviews · 2021Article
- The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic.Transactions in GIS : TG · 2021Article
- The impact of fear and anxiety of Covid-19 on life satisfaction: Psychological distress and sleep disturbance as mediators.Personality and individual differences · 2021Article
- Welcome to the revolution: COVID-19 and the democratization of spatial-temporal data.Patterns (New York, N.Y.) · 2021Review
- Harnessing Social Media in the Modelling of Pandemics-Challenges and Opportunities.Bulletin of mathematical biology · 2021Article
- Transmission and control pressure analysis of the COVID-19 epidemic situation using multisource spatio-temporal big data.PloS one · 2021Article
- Data-Driven Surveillance: Effective Collection, Integration, and Interpretation of Data to Support Decision Making.Frontiers in veterinary science · 2021Article
- The duration of travel impacts the spatial dynamics of infectious diseases.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- A call for an ethical framework when using social media data for artificial intelligence applications in public health research.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Spatial big data have the velocity, volume, and variety of big data sources and contain additional geographic information. Digital data sources, such as medical claims, mobile phone call data records, and geographically tagged tweets, have entered infectious diseases epidemiology as novel sources of data to complement traditional infectious disease surveillance. In this work, we provide examples of how spatial big data have been used thus far in epidemiological analyses and describe opportunities for these sources to improve disease-mitigation strategies and public health coordination. In addition, we consider the technical, practical, and ethical challenges with the use of spatial big data in infectious disease surveillance and inference. Finally, we discuss the implications of the rising use of spatial big data in epidemiology to health risk communication, and public health policy recommendations and coordination across scales.
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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.