Parameters Estimation in Stochastic Epidemic Models

African Mathematics Seminar

TITLE:  Parameters Estimation in Stochastic Epidemic Models
SPEAKER:  Denis Ndanguza, University of Rwanda
TIME: 3:00PM Nairobi (GMT+3)

TIME in some well-known cities*:
15:00 (Nairobi, Dar es salaam, Addis Ababa, Kampala, Istanbul, Moscow)
14:00 (Kigali, Cairo, Khartoum, Johannesburg, Maputo, Berlin, Stockholm)
13:00 (Lagos, Rabat, Yaoundé, London))
12:00 (Accra, Dakar)
20:00 (Hong Kong, Shanghai)
21:00 (Tokyo, Seoul)
08:00 (New York, Seoul)


Parameter estimation is a very difficult problem, especially for large systems. In this talk, a deterministic Ebola model is formulated and converted into a stochastic differential equations. In order to estimate the model parameter values, we use the extended Kalman filter technique as the filtering method and sum of square of errors to compute an approximation of the likelihood. From the obtained likelihood function, the maximum likelihood and MCMC methods for parameters estimation are then used. These parameter estimates provide useful information on quantities of epidemiological interest. Finally, we investigate whether an estimate obtained from a biased study differs systematically from the true source population of the study