Objectives: Several parallel hypotheses have been proposed to explain the mechanisms of efficacy of pertussis vaccines. In-host mathematical models, that leverage available data and knowledge of biological mechanisms, are well suited to discriminate between these hypotheses.
Methods: We developed a within-host mathematical model of pertussis infection in naïve or immunized individuals that represents the most relevant mechanistic interactions between the bacteria and the host immune system. Different versions of this model were constructed to investigate the relative impact of T cell polarization and specific antibodies on infection clearance. Curation of approximately 250 scientific sources was performed to design the model’s equations. Quantitative data from 6 articles were extracted and used to calibrate the model, including bacterial load evolution in challenged baboons with 4 distinct immunization states [1].
Results: After calibration, the model versions can reproduce bacterial load evolution in the 4 immunization scenarios. Simulations performed with the model suggest that the antibody response is probably not the only driver of immune protection and that anti-PRN antibodies are essential for the protection conferred by acellular vaccine, which would explain the emergence of PRN deficient B. pertussis strains. The model also predicts that the highest increase in vaccine efficacy would be granted by an increase in anti-PRN antibodies or an increase in Th1 or Th17 polarization.
Conclusions: Such in-host mathematical models could play an important role in the development of new pertussis vaccines by giving insights on the best candidates before their entry into clinical trials.
Citations: [1] J. M. Warfel, L. I. Zimmerman, T. J. Merkel, Acellular pertussis vaccines protect against disease but fail to prevent infection and transmission in a nonhuman primate model. Proc. Natl. Acad. Sci. U.S.A. 111 (2013), pp. 787–792.
