Modeling rotavirus strain dynamics in developed countries to understand the potential impact of vaccination on genotype distributions

Abstract

Understanding how immunity shapes the dynamics of multistrain pathogens is essential in determining the selective pressures imposed by vaccines. There is currently much interest in elucidating the strain dynamics of rotavirus to determine whether vaccination may lead to the replacement of vaccine-type strains. In developed countries, G1P[8] strains constitute the majority of rotavirus infections most years, but occasionally other genotypes dominate for reasons that are not well understood. We developed a mathematical model to examine the interaction of five common rotavirus genotypes. We explored a range of estimates for the relative strength of homotypic vs. heterotypic immunity and compared model predictions against observed genotype patterns from six countries. We then incorporated vaccination in the model to examine its impact on rotavirus incidence and the distribution of strains. Our model can explain the coexistence and cyclical pattern in the distribution of genotypes observed in most developed countries. The predicted frequency of cycling depends on the relative strength of homotypic vs. heterotypic immunity. Vaccination that provides strong protection against G1 and weaker protection against other strains will likely lead to an increase in the relative prevalence of non-G1 strains, whereas a vaccine that provides equally strong immunity against all strains may promote the continued predominance of G1. Overall, however, disease incidence is expected to be substantially reduced under both scenarios and remain below prevaccination levels despite the possible emergence of new strains. Better understanding of homotypic vs. heterotypic immunity, both natural and vaccine-induced, will be critical in predicting the impact of vaccination.

Fig. 1.

Analysis of genotype oscillations observed in six countries. (A) Genotype distributions (percentage of typeable rotavirus-positive samples) for G1–G4 and G9, as described in refs. –. (B) Fourier analysis of cyclical patterns for each of the five genotypes. Fourier amplitudes for each genotype are plotted on a log scale for periods ranging from 2 to 12 y. Asterisks represent significant signals according to bootstrap analysis.

Fig. 2.

Model-predicted patterns for different strengths of homotypic and heterotypic immunity. The colorbars indicate (A) the dominant period of oscillations for G1 strains (as indicated by the maximum Fourier amplitude) and (B) the mean proportion of severe diarrhea cases due to G1 strains over an 80-y period, for relative risks of second infection with homotypic strains ranging from 0.01 to 0.5 (and relative infectiousness ranging from 0.1 to 0.5) and relative risks of second infection with heterotypic strains ranging from 0.5 to 1.0 (with corresponding relative infectiousness).

Fig. 3.

Model-predicted genotype distributions and incidence of severe rotavirus diarrhea. The proportion of cases in a given year attributable to each genotype (Left), the weekly incidence of severe rotavirus diarrhea (Center), and the mean genotype distributions for years 21–40 (Right) are plotted for the following situations: (A) prevaccination, (B) 50% coverage with a vaccine that provides strong protection against G1 and weaker protection against other genotypes, (C) 80% coverage with such a vaccine, (D) 50% coverage with a vaccine that provides strong protection against all genotypes, and (E) 80% coverage with such a vaccine. Vaccination is introduced in year 10 in B–E. The results represent single realizations of a model allowing for fadeout and stochastic reintroduction of genotypes.

Fig. 4.

Model-predicted genotype distributions and incidence of severe rotavirus diarrhea after the emergence of a new strain after vaccination. The proportion of cases in a given year attributable to each genotype (Left) and the weekly incidence of severe rotavirus diarrhea (Right) are plotted for 50% coverage with (A) a vaccine that provides strong protection against G1 and weaker heterotypic immunity to other genotypes, including the new strain (scenario 1), (B) a vaccine targeting G1 that provides no immunity to the new strain (scenario 2), (C) a vaccine that provides strong immunity against G1–G4 but only weak immunity to the new strain (scenario 3), and (D) a vaccine providing strong immunity against G1–G4 and no immunity to the new strain (scenario 4). Vaccination is introduced in year 10, and the new strain is introduced in year 15. The results represent single realizations of a model allowing for fadeout and stochastic reintroduction of genotypes.