Spatio-Temporal Simulation and Prediction of Hemorrhagic Fever with Renal Syndrome (HFRS) in Mainland China

  • Youlin Zhao
Keywords: Hemorrhagic Fever with Renal Syndrome (HFRS), Spatio-temporal Distribution, Trend Prediction

Abstract

Hemorrhagic Fever with Renal Syndrome (HFRS) causes a large number of deaths in mainland China. It is
therefore necessary and important to better understand and predict outbreaks of HFRS. Data consisting of
clustering patterns for annual HFRS incidence in mainland China is collected and analyzed using global spatial
autocorrelation method. Based on the spatial distribution characteristics and the general clustering patterns of
HFRS incidence in mainland China, Spatio-Temporal Auto Regressive and Moving Average model (STARMA)
was employed to generate the spatial and temporal distribution pattern of HFRS epidemics. Three provinces
with different distribution patterns were selected to verify the accuracy of the conducted models. A spatial
distribution map was constructed, which indicated that HFRS incidence in mainland China has gradually shifted
from northern and northeastern regions to the central region of China. HFRS outbreaks demonstrate a clustering
pattern in most of the years from 2005 to 2014. STARMA model used in this paper is a reliable method of
selection to make simulations and predictions for HFRS epidemics. Methods and solutions suggested in this
paper may contribute to the prevention and control of HFRS epidemics in mainland China and serve as a
reference for epidemics with similar spatial and temporal characteristics.

Published
2019-09-15