The Application of the Grey Disaster Model to Forecast Epidemic Peaks of Typhoid and Paratyphoid Fever in China

Abstract

ObjectiveThe objectives of this study were to forecast epidemic peaks of typhoid and paratyphoid fever in China using the grey disaster model, to evaluate its feasibility of predicting the epidemic tendency of notifiable diseases.MethodsAccording to epidemiological features, the GM(1,1) model and DGM model were used to build the grey disaster model based on the incidence data of typhoid and paratyphoid fever collected from the China Health Statistical Yearbook. Model fitting accuracy test was used to evaluate the performance of these two models. Then, the next catastrophe date was predicted by the better model.ResultsThe simulation results showed that DGM model was better than GM(1,1) model in our data set. Using the DGM model, we predicted the next epidemic peak time will occur between 2023 to 2025.ConclusionThe grey disaster model can predict the typhoid and paratyphoid fever epidemic time precisely, which may provide valuable information for disease prevention and control.

The Rapid Assessment and Early Warning Models for COVID-19

“…The principle aim is to establish a suitable mathematical model based on the dynamic characteristics of infectious disease transmission, and to conduct qualitative as well as quantitative analysis and computer simulations of the transmission process. Currently, the models used for forecasting and warning at home and abroad mainly include the time series model, the linear regression model, the grey dynamics model, the artificial neural network model, the Markov model, the Bayesian model and the Complex network model (Jennings et al 2008;Zhu et al 2011;Wesolowski and Suchacz 2012;Aghdam et al 2013;Shen et al 2013). Practice has proved that in public health emergencies, it is important to establish suitable prediction models to change passive prevention into active prevention.…”

Estimation of COVID-19 spread curves integrating global data and borrowing information

“…These models are based on assumptions related to S (susceptible), E (exposed), I (infected), and R (remove) categories of the population. Time series based prediction models such as ARIMA, Grey Model, Markov Chain models have been used to describe dependence structure over of the disease spread over time (Hu et al, 2006;Reza Yaesoubi, 2011;Rushton et al, 2006;Shen X, 2013;Zhirui He, 2018). On the other hand, statistical models, so-called phenomenological models, which follow certain laws of epidemiology (Clayton and Hills, 2013;Thompson et al, 2006) are widely used in real-time forecasting for infection trajectory or size of epidemics in early stages of pandemic (Fineberg and Wilson, 2009;Hsieh, 2009;Pell et al, 2018).…”

Immigration trends’ impacts on state vocational rehabilitation agency minority application rates: An empirical forecast model demonstration study

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“…The Grey Model (GM) is based on the grey system theory and has been widely applied in economics and financial areas (Kayacan, Ulutas, & Kaynak, 2010;Li et al, 2007;L. Liu, Wang, Liu, & Li, 2014), public health and biostatistics (Feng & Zhang, 2012;Jin et al, 2008;Shen et al, 2013), engineering (Kang & Zhao, 2012) as well as other specialties.…”