ArticlePloS one2021
A hybrid approach to forecast the COVID-19 epidemic trend.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- The grading detection model for fingered citron slices (citrus medica 'fingered') based on YOLOv8-FCS.Frontiers in plant science · 2024Article
- Multimodal approach to public health interventions using EGG and mobile health technologies.Frontiers in public health · 2024Article
- YOLOv7-Plum: Advancing Plum Fruit Detection in Natural Environments with Deep Learning.Plants (Basel, Switzerland) · 2023Article
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- Determining the rate of infectious disease testing through contagion potential.PLOS global public health · 2023Article
- Unstructured road extraction and roadside fruit recognition in grape orchards based on a synchronous detection algorithm.Frontiers in plant science · 2023Article
- Prediction of COVID-19 Data Using Hybrid Modeling Approaches.Frontiers in public health · 2022Article
- YOLO-P: An efficient method for pear fast detection in complex orchard picking environment.Frontiers in plant science · 2022Article
- Lexicon and attention-based named entity recognition for kiwifruit diseases and pests: A Deep learning approach.Frontiers in plant science · 2022Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Studying the progress and trend of the novel coronavirus pneumonia (COVID-19) transmission mode will help effectively curb its spread. Some commonly used infectious disease prediction models are introduced. The hybrid model is proposed, which overcomes the disadvantages of the logistic model's inability to predict the number of confirmed diagnoses and the drawbacks of too many tuning parameters of the SEIR (Susceptible, Exposed, Infectious, Recovered) model. The realization and superiority of the prediction of the proposed model are proven through experiments. At the same time, the influence of different initial values of the parameters that need to be debugged on the hybrid model is further studied, and the mean error is used to quantify the prediction effect. By forecasting epidemic size and peak time and simulating the effects of public health interventions, this paper aims to clarify the transmission dynamics of COVID-19 and recommend operation suggestions to slow down the epidemic. It is suggested that the quick detection of cases, sufficient implementation of quarantine and public self-protection behaviours are critical to slow down the epidemic.
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