ArticlePloS one2014
Application of a novel grey self-memory coupling model to forecast the incidence rates of two notifiable diseases in China: dysentery and gonorrhea.
Article in PloS one, 2014. 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.
- Research of Combined ES-BP Model in Predicting Syphilis Incidence 1982-2020 in Mainland China.Iranian journal of public health · 2023Article
- Article
- Early Warning of Infectious Diseases in Hospitals Based on Multi-Self-Regression Deep Neural Network.Journal of healthcare engineering · 2022Article
- Short-term prediction of COVID-19 spread using grey rolling model optimized by particle swarm optimization.Applied soft computing · 2021Article
- A novel grey model based on traditional Richards model and its application in COVID-19.Chaos, solitons, and fractals · 2021Article
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4 authors.
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Abstract
objectiveIn this study, a novel grey self-memory coupling model was developed to forecast the incidence rates of two notifiable infectious diseases (dysentery and gonorrhea); the effectiveness and applicability of this model was assessed based on its ability to predict the epidemiological trend of infectious diseases in China.
methodsThe linear model, the conventional GM(1,1) model and the GM(1,1) model with self-memory principle (SMGM(1,1) model) were used to predict the incidence rates of the two notifiable infectious diseases based on statistical incidence data. Both simulation accuracy and prediction accuracy were assessed to compare the predictive performances of the three models. The best-fit model was applied to predict future incidence rates.
resultsSimulation results show that the SMGM(1,1) model can take full advantage of the systematic multi-time historical data and possesses superior predictive performance compared with the linear model and the conventional GM(1,1) model. By applying the novel SMGM(1,1) model, we obtained the possible incidence rates of the two representative notifiable infectious diseases in China.
conclusionThe disadvantages of the conventional grey prediction model, such as sensitivity to initial value, can be overcome by the self-memory principle. The novel grey self-memory coupling model can predict the incidence rates of infectious diseases more accurately than the conventional model, and may provide useful references for making decisions involving infectious disease prevention and control.
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