Statistical Modeling And Analysis Of Important Parameters Based On 2014- 2015 Ebola Epidemic Data

The study of WHO shows that infectious diseases are the number one killer of mankind, and continue to threaten human life and health. SARS that outbreak in 2003 to the human and the economy has brought great harm and loss. Because infectious diseases cannot take the form of experiment to research, therefore, we require more analysis of theory and research for the infectious diseases’ the route of transmission, the mechanism of dissemination and popular rule. Infectious Disease Dynamics is a method of analysis that quantitative research for the popular rule of infectious diseases.The paper use the maximum likelihood estimates to analysis and study the epidemic of West African Ebola virus in overall, Guinea, Sierra Leone and Liberia by three types of Dynamic Model for Diseases(SIR model, SEIR model and SEIHFR model), respectively, based on 2014-2015 West African Ebola virus data. According to the programs by R, we obtain the estimates of important parameters and fitting curves of accumulated Ebola patients. By comparison, The SEIHFR model that increased hospitalization and burial of the two states more been in line with the propagation mechanisms and the popular rule of Ebola virus.In conclusion, Before the implementation of measures, the basic reproductive number 0 is greater than 1 in all cases, indicating that the epidemic outbreak have always maintained and form the endemic; After the implementation of measures, the control coefficient k in all cases is greater than 0, so that the effective reproductive number e() decreases exponentially, and reduced to 1. In SEIHFR model, the effective reproductive number has dropped to unity in Dec 25, 2014, Nov 19, 2014, Nov 29, 2014 and Oct 23, 2014 in the epidemic of overall, Guinea, Sierra Leone and Liberia, respectively. This shows that the epidemic of Ebola virus has been effectively curbed under the measures of government in SEIHFR model. We can also find in the fitting curve, SEIHFR model is more applicable to analysis in All, Guinea and Liberia epidemic; for the epidemic in Sierra Leone, the effect will be better in SIR model.