ArticleScientific reports2017
A new method for assessing the risk of infectious disease outbreak.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Determinants of multimodal fake review generation in China's E-commerce platforms.Scientific reports · 2024Article
- Predictors on outcomes of cardiovascular disease of male patients in Malaysia using Bayesian network analysis.BMJ open · 2023Article
- A Bayesian network-based approach for identifying risk factors and predicting ischemic stroke in infective endocarditis patients.Frontiers in cardiovascular medicine · 2023Article
- Perspectives on nano-nutraceuticals to manage pre and post COVID-19 infections.Biotechnology reports (Amsterdam, Netherlands) · 2022Article
- Novel miniaturized fluorescence loop-mediated isothermal amplification detection system for rapid on-site virus detection.Frontiers in bioengineering and biotechnology · 2022Article
- Risk factors and a Bayesian network model to predict ischemic stroke in patients with dilated cardiomyopathy.Frontiers in neuroscience · 2022Article
- Global mapping of epidemic risk assessment toolkits: A scoping review for COVID-19 and future epidemics preparedness implications.PloS one · 2022Article
- A perspective on early detection systems models for COVID-19 spreading.Biochemical and biophysical research communications · 2021Article
- Known and Unknown Transboundary Infectious Diseases as Hybrid Threats.Frontiers in public health · 2021Article
- COVID-19: A Global Challenge with Old History, Epidemiology and Progress So Far.Molecules (Basel, Switzerland) · 2020Review
- Automated Classification of Online Sources for Infectious Disease Occurrences Using Machine-Learning-Based Natural Language Processing Approaches.International journal of environmental research and public health · 2020Article
- Article
- Developments in Transduction, Connectivity and AI/Machine Learning for Point-of-Care Testing.Sensors (Basel, Switzerland) · 2019Article
- Application of tabu search-based Bayesian networks in exploring related factors of liver cirrhosis complicated with hepatic encephalopathy and disease identification.Scientific reports · 2019Article
- Prevalence of hyperlipidemia in Shanxi Province, China and application of Bayesian networks to analyse its related factors.Scientific reports · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over the past few years, emergent threats posed by infectious diseases and bioterrorism have become public health concerns that have increased the need for prompt disease outbreak warnings. In most of the existing disease surveillance systems, disease outbreak risk is assessed by the detection of disease outbreaks. However, this is a retrospective approach that impacts the timeliness of the warning. Some disease surveillance systems can predict the probabilities of infectious disease outbreaks in advance by determining the relationship between a disease outbreak and the risk factors. However, this process depends on the availability of risk factor data. In this article, we propose a Bayesian belief network (BBN) method to assess disease outbreak risks at different spatial scales based on cases or virus detection rates. Our experimental results show that this method is more accurate than traditional methods and can make uncertainty estimates, even when some data are unavailable.
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