Selected article for: "previous study and transmission dynamic"
Author: Guo, Zuiyuan; Xiao, Dan; Li, Dongli; Wang, Xiuhong; Wang, Yayu; Yan, Tiecheng; Wang, Zhiqi
Title: Predicting and Evaluating the Epidemic Trend of Ebola Virus Disease in the 2014-2015 Outbreak and the Effects of Intervention Measures
  • Document date: 2016_4_6
    • ID: 1amm2hh8_2
    Snippet: Understanding the epidemiological distribution and transmission pattern of EVD during the African outbreak will contribute to improve scientific understanding and to allow the development of more effective control and prevention measures. Other scholars have already analyzed the epidemiological distribution and performance of clinical centers [3, 5, 13] , providing valuable information for better understanding the EVD outbreak. However, there is .....
    Document: Understanding the epidemiological distribution and transmission pattern of EVD during the African outbreak will contribute to improve scientific understanding and to allow the development of more effective control and prevention measures. Other scholars have already analyzed the epidemiological distribution and performance of clinical centers [3, 5, 13] , providing valuable information for better understanding the EVD outbreak. However, there is no recognized mathematical model that describes the process of EVD transmission, and that can be used to evaluate the effect of prevention measures. This lack of a model might hinder the process of controlling the disease. A dynamic transmission model of an infectious disease can be constructed by using the patterns of disease occurrence and transmission, and the relationships between the disease and social factors. Such a model is used to analyze the dynamic characteristics of disease transmission quantitatively, to indicate transmission patterns, and to predict the epidemiological trends of the disease. Dynamic transmission models have been constructed successfully for SARS (severe acute respiratory syndrome), AIDS (acquired immune deficiency syndrome), and malaria to analyze transmission patterns, predict epidemiological trends, and evaluate the effect of intervention measures [14] [15] [16] [17] [18] . These models have provided important evidence for the scientific control and prevention of these diseases. In a previous study, researchers constructed an SEIR (susceptible, exposed, infective, removed) model to analyze the 1995 EVD outbreak in the Congo. The constructed model was well fitted and demonstrated to be effective for prediction [19] , indicating that a dynamic transmission model can be applied to the analysis of EVD outbreaks. However, the transmission patterns of infectious diseases are affected by many factors and can be variable across different time periods and regions. Therefore, the 1995 outbreak model may not be applicable to the 2014 outbreak, and it is necessary to construct an updated model based on the 2014-2015 transmission patterns and the factors that might influence spread.

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