ReviewInternational journal of environmental research and public health2020
Big Data Analytics in the Fight against Major Public Health Incidents (Including COVID-19): A Conceptual Framework.
Review in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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
26 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- AI in Medical Questionnaires: Scoping ReviewJournal of medical Internet research · 2025Pooled it
- The collateral damage of COVID-19 to cardiovascular services: a meta-analysis.European heart journal · 2022Pooled it
- Demonstrating a Social Intelligence Analysis Framework for Loneliness: Infodemiology Approach.Online journal of public health informatics · 2026Article
- Factors associated with COVID-19 booster dose uptake in the Jazan region, Saudi Arabia: insights for policy improvement during pandemics.Frontiers in public health · 2026Article
- An optimized public opinion communication system in social media networks based on K-means cluster analysis.Heliyon · 2024Article
- Understanding public response: Government communication during the COVID-19 crisis through the eyes of the Swiss public.PEC innovation · 2024Article
- Multimodal approach to public health interventions using EGG and mobile health technologies.Frontiers in public health · 2024Article
- A Strategy Formulation Framework for Efficient Screening during the Early Stage of a Pandemic.Tropical medicine and infectious disease · 2023Article
- The COVID-19 related stress and social network addiction among Chinese college students: A moderated mediation model.PloS one · 2023Article
- A Systematic Literature Review and Future Perspectives for Handling Big Data Analytics in COVID-19 Diagnosis.New generation computing · 2023Article
- The Recovery of China's Industrial Parks in the First Wave of COVID-19.International journal of environmental research and public health · 2022Article
- Data analytics during pandemics: a transportation and location planning perspective.Annals of operations research · 2022Article
- The medical and societal impact of big data analytics and artificial intelligence applications in combating pandemics: A review focused on Covid-19.Social science & medicine (1982) · 2022Review
- Spatial Dynamics and Multiscale Regression Modelling of Population Level Indicators for COVID-19 Spread in Malaysia.International journal of environmental research and public health · 2022Article
- Big data analytics and COVID-19: investigating the relationship between government policies and cases in Poland, Turkey and South Korea.Health policy and planning · 2022Article
- Analysis of network public opinion on COVID-19 epidemic based on the WSR theory.Frontiers in public health · 2022Article
- How Duty-Free Policy Influences Travel Intention: Mediating Role of Perceived Value and Moderating Roles of COVID-19 Severity and Counterfactual Thinking.Frontiers in psychology · 2022Article
- Research on emergency management of global public health emergencies driven by digital technology: A bibliometric analysis.Frontiers in public health · 2022Article
- Understanding terror states of online users in the context of COVID-19: An application of Terror Management Theory.Computers in human behavior · 2021Article
- Theorising the Microfoundations of analytics empowerment capability for humanitarian service systems.Annals of operations research · 2021Article
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
Major public health incidents such as COVID-19 typically have characteristics of being sudden, uncertain, and hazardous. If a government can effectively accumulate big data from various sources and use appropriate analytical methods, it may quickly respond to achieve optimal public health decisions, thereby ameliorating negative impacts from a public health incident and more quickly restoring normality. Although there are many reports and studies examining how to use big data for epidemic prevention, there is still a lack of an effective review and framework of the application of big data in the fight against major public health incidents such as COVID-19, which would be a helpful reference for governments. This paper provides clear information on the characteristics of COVID-19, as well as key big data resources, big data for the visualization of pandemic prevention and control, close contact screening, online public opinion monitoring, virus host analysis, and pandemic forecast evaluation. A framework is provided as a multidimensional reference for the effective use of big data analytics technology to prevent and control epidemics (or pandemics). The challenges and suggestions with respect to applying big data for fighting COVID-19 are also discussed.
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.