ReviewEmerging infectious diseases2019
Using Big Data to Monitor the Introduction and Spread of Chikungunya, Europe, 2017.
Review in Emerging infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Data Sources and Their Impact on People's Health: A Systematic Review of Systematic Reviews.Frontiers in public health · 2021Pooled it
- Cluster of imported chikungunya virus infections in travelers returning from Seychelles to Berlin, December 2025-April 2026.New microbes and new infections · 2026Article
- Viral emergence and pandemic preparedness in a One Health framework.Nature reviews. Microbiology · 2026Review
- Public health consequences of global climate change. A narrative review.Frontiers in cellular and infection microbiology · 2026Review
- Predictability of infectious disease outbreak severity: Chikungunya as a case study.Science advances · 2025Article
- The Hsf1-sHsp cascade has pan-antiviral activity in mosquito cells.Communications biology · 2025Article
- The Role of Big Data in Developing Innovative Predictive Learning Models for Neglected Tropical Diseases within the New Generation of the Evidence-Based Medicine Pyramid.Le infezioni in medicina · 2025Review
- Use of Digital Tools in Arbovirus Surveillance: Scoping Review.Journal of medical Internet research · 2024Article
- Novel Porcine Getah Virus from Diarrheal Piglets in Jiangxi Province, China: Prevalence, Genome Sequence, and Pathogenicity.Animals : an open access journal from MDPI · 2024Article
- Digital epidemiology: harnessing big data for early detection and monitoring of viral outbreaks.Infection prevention in practice · 2024Review
- A nowcast model to predict outdoor flea activity in real time for the contiguous United States.Parasites & vectors · 2024Article
- Decision-support tools to build climate resilience against emerging infectious diseases in Europe and beyond.The Lancet regional health. Europe · 2023Review
- Predicting the dengue cluster outbreak dynamics in Yogyakarta, Indonesia: a modelling study.The Lancet regional health. Southeast Asia · 2023Article
- Reflections on major epidemics in history reported by online English news media and literature: interaction between epidemics and social conditions.Frontiers in public health · 2023Article
- Constructing big data prevention and control model for public health emergencies in China: A grounded theory study.Frontiers in public health · 2023Article
- The 2022 Europe report of the Lancet Countdown on health and climate change: towards a climate resilient future.The Lancet. Public health · 2022Review
- Building Public Health Surveillance 3.0: Emerging Timely Measures of Physical, Economic, and Social Environmental Conditions Affecting Health.American journal of public health · 2022Review
- Epitweetr: Early warning of public health threats using Twitter data.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2022Article
- Best Practices on Big Data Analytics to Address Sex-Specific Biases in Our Understanding of the Etiology, Diagnosis, and Prognosis of Diseases.Annual review of biomedical data science · 2022Review
- Climate Change and Cascading Risks from Infectious Disease.Infectious diseases and therapy · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With regard to fully harvesting the potential of big data, public health lags behind other fields. To determine this potential, we applied big data (air passenger volume from international areas with active chikungunya transmission, Twitter data, and vectorial capacity estimates of Aedes albopictus mosquitoes) to the 2017 chikungunya outbreaks in Europe to assess the risks for virus transmission, virus importation, and short-range dispersion from the outbreak foci. We found that indicators based on voluminous and velocious data can help identify virus dispersion from outbreak foci and that vector abundance and vectorial capacity estimates can provide information on local climate suitability for mosquitoborne outbreaks. In contrast, more established indicators based on Wikipedia and Google Trends search strings were less timely. We found that a combination of novel and disparate datasets can be used in real time to prevent and control emerging and reemerging infectious diseases.
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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.