Use of an optimality model to solve the immunological puzzle of concomitant infection

Immunological data indicate that different subsets of T-helper cells work best against different types of infection. Concomitant infection of a host may thus impose either conflicting or synergistic immune response requirements, depending upon the extent to which the component optimal immune responses differ. Drawing upon empirically-determined optimal responses to single-species infections, an optimality model is here used to generate testable hypotheses for optimal responses to concomitant infection. The model is based upon the principle that the joint immune response will minimize divergence from each of the optima for single-species infections, but that it will also be weighted by the importance of mounting the correct response against each infectious organism. The model thus predicts a weighted average response as the optimal response to concomitant infection. Data on concomitant infection of murine hosts by the parasites Schistosoma mansoni and Toxoplasma gondii will provide the first test of the optimality model. If the weighted average hypothesis holds true, then there are no emergent immunological properties of concomitant infections and we may be able to understand immune responses to concomitant infection directly via our understanding of single-species infections.