ArticleBMC infectious diseases2022
A novel method to detect the early warning signal of COVID-19 transmission.
Article in BMC infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Harnessing artificial intelligence for enhanced public health surveillance: a narrative review.Frontiers in public health · 2025Review
- An early warning indicator trained on stochastic disease-spreading models with different noises.Journal of the Royal Society, Interface · 2024Article
- Application of early warning signs to physiological contexts: a comparison of multivariate indices in patients on long-term hemodialysis.Frontiers in network physiology · 2024Article
- Article
- The potential of resilience indicators to anticipate infectious disease outbreaks, a systematic review and guide.PLOS global public health · 2023Article
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Authors and funding
3 authors.
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Abstract
backgroundInfectious illness outbreaks, particularly the corona-virus disease 2019 (COVID-19) pandemics in recent years, have wreaked havoc on human society, and the growing number of infected patients has put a strain on medical facilities. It's necessary to forecast early warning signals of potential outbreaks of COVID-19, which would facilitate the health ministry to take some suitable control measures timely to prevent or slow the spread of COVID-19. However, since the intricacy of COVID-19 transmission, which connects biological and social systems, it is a difficult task to predict outbreaks of COVID-19 epidemics timely.
resultsIn this work, we developed a new model-free approach, called, the landscape network entropy based on Auto-Reservoir Neural Network (ARNN-LNE), for quantitative analysis of COVID-19 propagation, by mining dynamic information from regional networks and short-term high-dimensional time-series data. Through this approach, we successfully identified the early warning signals in six nations or areas based on historical data of COVID-19 infections.
conclusionBased on the newly published data on new COVID-19 disease, the ARNN-LNE method can give early warning signals for the outbreak of COVID-19. It's worth noting that ARNN-LNE only relies on small samples data. Thus, it has great application potential for monitoring outbreaks of infectious diseases.
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