Abstract
Hemorrhagic fever with renal syndrome (HFRS) is one of the most common infectious diseases globally. With the most reported cases in the world, the epidemic characteristics are still remained unclear in China. This paper utilized the seasonal-trend decomposition (STL) method to analyze the periodicity and seasonality of the HFRS data, and used the exponential smoothing model (ETS) model to predict incidence cases from July to December 2016 by using the data from January 2006 to June 2016. Analytic results demonstrated a favorable trend of HFRS in China, and with obvious periodicity and seasonality, the peak of the annual reported cases in winter concentrated on November to January of the following year, and reported in May and June also constituted another peak in summer. Eventually, the ETS (M, N and A) model was adopted for fitting and forecasting, and the fitting results indicated high accuracy (Mean absolute percentage error (MAPE) = 13.12%). The forecasting results also demonstrated a gradual decreasing trend from July to December 2016, suggesting that control measures for hemorrhagic fever were effective in China. The STL model could be well performed in the seasonal analysis of HFRS in China, and ETS could be effectively used in the time series analysis of HFRS in China.
Highlights
IntroductionIn China, scholars analysed the annual report data of HFRS in China through the time series model[8]; and some characteristics could be found from the annual data; there were still some unclear problems regarding some trends within the year, such as the specific variation trend of each year
We summarized the monthly reported cases in each year to analyze the overall annual variation trend from 2006 to 2015 in China, the results of which revealed that HFRS in China has been continuously from 2006 to 2015, and the variation trend could be divided into three sections; incidence cases remarkably decreased from 16129 to 9203 from 2006 to 2009, with the percent change of −42.94%; it rose to 13918 to year 2012, with the percent change of 51.23% relative to that in 2009; and with a following decrease from 2012 to 2016, with the percent change of 61.64%
HFRS is a kind of highly fatal infectious disease with murine being the major source of infection, and HFRS has caused severe influence worldwide[19]
Summary
In China, scholars analysed the annual report data of HFRS in China through the time series model[8]; and some characteristics could be found from the annual data; there were still some unclear problems regarding some trends within the year, such as the specific variation trend of each year. Little literature analyses the variation characteristics of HFRS within a year or determines the variation characteristics in recent years, as well as the periodical variation within the yearly data through the monthly data, and the determination of these conditions is of essential importance to the seasonal distribution of the control resources every year. In order to further determine these questions, we adopted the Seasonal-trend decomposition (STL) and exponential smoothing model (ETS) methods to analyse the monthly data from the National Heath and Family Planning Commission Reports, and analysed some specific conditions of the periodicity and seasonality of the monthly data
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