Bridging immunology and within-host ecology in malaria infection

Linking proximate mechanisms of immune responses to host health and parasite burden is key to predicting individual infection outcome. However, existing mathematical models fall short as they leave out mechanistic details of host responses. My work bridges the gap between mechanistic immunology and infection ecology by incorporating a process-based description of host responses into a dynamical model of within-host malaria ecology. I will fit the models I have been developing to time-series data of rodent malaria infections obtained experimentally from several strains of mice and malaria parasites. Using this approach, I will propose plausible regulatory hypotheses of host responses and provide quantitative predictions about innate immunity and recovery from anaemia. TO BE CONT’D

Faculty Supervisor:

Nicole Mideo

Student:

Partner:

Stanford University

Discipline:

Life Sciences

Sector:

Education

University:

University of Toronto

Program: