Modeling the effects of strain diversity and mechanisms of strain competition on the potential performance of new tuberculosis vaccines

Abstract

While bacillus Calmette-Guérin vaccination plays an important role in reducing the morbidity of tuberculosis (TB) infection during childhood, new tuberculosis vaccines are necessary to disrupt the transmission of disease and improve global control of this pathogen. Growing evidence of the presence of meaningful Mycobacterium tuberculosis strain diversity, coupled with the possibility that new vaccines may differentially protect against infection or disease with circulating M. tuberculosis strains, suggest that these vaccines may have complicated effects on disease dynamics. We use a mathematical model to explore the potential effects of strain diversity on the performance of vaccines and find that vaccines offer great promise for improving tuberculosis control, but the expected benefits of mass vaccination will be eroded if strain replacement with M. tuberculosis variants that are not effectively targeted by vaccines occurs. Determining the likelihood of strain replacement will require additional knowledge of the strain specificities of current vaccine candidates, and an improved understanding of the mechanisms of strain interaction, which are responsible for maintaining the diversity of M. tuberculosis within communities.

Fig. 1.

Model structures (A) Superinfection model: Individuals are assigned to unvaccinated (S) or vaccinated (S_v) groups upon entry into population and may be infected with either strain 1 or strain 2. Individuals with latent infection (L) and active disease (I) are indexed by strain type (1 or 2) and vaccination status (vaccinated individuals designated by _v). In this version of the model, reinfection of individuals with latent infections can result in strain replacement (dotted arrows). State transitions are as described in the text and by the system of equations presented in the SI Appendix. (B) Coinfection model: In this variant of the model, reinfection of those in the latent state may result in a state of mixed strain coinfection (L₁₂ and L_12v).

Fig. 2.

Effects of preexposure vaccines in superinfection model. The equilibrium effects of vaccination on total TB prevalence under the three different mechanisms of strain interaction (A, mechanism 1; B, mechanism 2; and C, mechanism 3). These figures show the results of 10,000 simulations with parameters drawn randomly from uniformly distributed ranges listed in Table S1. Red points indicate simulations in which only strain 2 persists after vaccination, blue points indicate simulations in which only strain 1 persists after vaccination, and green points indicate simulations in which both strain 1 and strain 2 persist after vaccination. Vaccine impact is a function of coverage and efficacy and is calculated according to the equation in the text. R2/R1 indicates the relative reproductive number of strain 2 compared to strain 1. Panels D, E, and F show the relative abundance of strain 2 before and after vaccination under the same three mechanisms of strain interaction.