Monitoring the SARS Epidemic in China: A Time Series Analysis
Dejian Lai
Abstract
In this article, we studied three types of time series analysis methods in modeling and forecasting the severe acute respiratory syndrome (SARS) epidemic in mainland China. The first model was a Box-Jenkins model, autoregressive model with order 1 (AR(1)). The second model was a random walk (ARIMA(0,1,0)) model on the log transformed daily reported SARS cases and the third one was a combination of growth curve fitting and autoregressive moving average model, ARMA(1,1). We applied all these three methods to monitor the dynamic of SARS in China based on the daily probable new cases reported by the Ministry of Health of China.
Topics & Concepts
Autoregressive integrated moving averageAutoregressive modelTime seriesMainland ChinaStatisticsAutoregressive–moving-average modelChinaEconometricsMoving averageSeries (stratigraphy)Christian ministryAkaike information criterionBox–JenkinsSTAR modelSETARMathematicsGeographyPolitical scienceArchaeologyPaleontologyBiologyLawCOVID-19 epidemiological studiesSARS-CoV-2 and COVID-19 ResearchCOVID-19 Pandemic Impacts