Predicting and Evaluating the Epidemic Trend of Ebola Virus Disease in the 2014-2015 Outbreak and the Effects of Intervention Measures

Guo, Zuiyuan; Xiao, Dan; Li, Dongli; Wang, Xiuhong; Wang, Yayu; Yan, Tiecheng; Wang, Zhiqi

An accurate analysis of the transmission pattern of the 2014 EVD epidemic provides a basis for implementing control and prevention measures. In this study, we constructed a dynamic transmission model to predict the epidemic trend of EVD and evaluated the effects of control and prevention measures. The key parameter in the model was the infection rate for patients in the free environment (β I ). This parameter was influenced by a patient's sphere of activity, the virulence of the virus, and the proportion of susceptible people in the total population. Fluctuations in β I may cause the results of the model to vary. Thus, it is important to fit an infection rate that approximates real values closely. Here, we found that the distribution of β I was approximated by a gamma distribution, rather than by an exponential distribution as an earlier study reported [22] . This discrepancy may be due to differences in the nature of the EVD epidemics modeled. In the 2014 epidemic, most of the early EVD cases were located in the sparsely populated rural areas, and the patients had a limited sphere of activity. When the disease spread to urban areas, patients came into contact with more susceptible individuals, causing the β I value to increase. Subsequently, isolation measures for EVD cases and improvements in public efforts at self-protection reduced the number of close contacts between EVD patients and the susceptible population, ultimately reducing the β I value.