Exploring the spatiotemporal distribution of measles in China and predicting the level of measles risk in each province
Year: 2018
Type: conference-paper
Abstract: Objective To explore the spatiotemporal distribution of national measles epidemic from 1950 to 2014 and establish a model to predict the measles epidemic hot spots in the next five years. Methods Using national measles monitoring data from 1950 to 2014, a geographic information database is established. Firstly, the basic statistical analysis is done by using Matlab software. Then GeoDa 1.4.6 geographic information software is used to draw the risk level of measles in each province. Finally, the gray Verhulst model of measles risk level in each province is set up by Gtms3.0 software to predict the risk level of measles in the next five years. Results The basic statistical results indicate that there is a certain periodicity in the time dimension, and the local extremum also shows a downward trend. The provinces with the highest incidence of measles in the past 20 years are Tibet and Qinghai. The analysis of gray Verhulst model shows that the risk indices of Beijing and Chongqing respectively will reach 18.65 and 10.88 in the next five years, far exceeding the national average incidence of measles 1.96. This requires the relevant departments of these two provinces to focus more on the prevention and control. Conclusions The incidence of measles has declined overall, but it still needs to be highly regarded. Using the Verhulst model can effectively predict the risk of measles in each province, and help the relevant departments to control the measles epidemic.
Authors: Wang Tan, Rencong Nie, Qianqian Yang, Xiang Gao
Institution: Ocean University of China
Language: English
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W2883491645