Mathematical models of immune responses following vaccination with application to Brucella infection

For many years bovine brucellosis was a zoonosis endemic in large parts of the world. While it is still endemic in some parts, such as the Middle East or India, several countries such as Australia and Canada have successfully eradicated brucellosis in cattle by applying vaccines, improving the hygienic standards in cattle breeding, and slaughtering or quarantining infected animals. The large economical impact of bovine brucellosis and its virulence for humans, coming in direct contact to fluid discharges from infected animals, makes the eradication of bovine brucellosis important to achieve. To achieve this goal several vaccines have been developed in the past decades. Today the two most commonly used vaccines are Brucella abortus vaccine strain 19 and strain RB51. Both vaccines have been shown to be effective, but the mechanisms of immune responses following vaccination with either of the vaccines are not understood yet. In this thesis we analyze the immunological data obtained through vaccination with the two strains using mathematical modeling. We first design a measure that allows us to separate the subjects into good and bad responders. Then we investigate differences in the immune responses following vaccination with strain 19 or strain RB51 and boosting with strain RB51. We develop a mathematical model of immune responses that accounts for formation of antagonistic pro and anti-inflammatory and memory cells. We show that different characteristics of pro-inflammatory cell development and activity have an impact on the number of memory cells obtained after vaccination.