Severe diseases arising as sequelae of superficial skin and throat infections with group A Streptococcus (GAS) are important causes of morbidity and mortality worldwide. The observed high level of heterogeneity in GAS prevalence across various temporal and spatial settings suggests potentially complex dynamics of population transmission. One of the most visible indicators of heterogeneity is the different prevalence of skin and throat infections across populations.
Sustained control of GAS infections in settings of poverty has failed, and an effective vaccine may be the most practical long-term strategy to reduce the burden of GAS-related disease. Research into GAS vaccines has been ongoing for many decades, and there are a number of vaccine candidates currently at various stages of development. Those based on the M-protein, the major virulence factor of GAS, include multivalent vaccines targeting the variable N-terminal of the M-protein, and vaccines that contain antigens from the conserved C-repeat region. It is anticipated that these vaccines will provide varying levels of protection across populations depending on the match between circulating and vaccine strains.
We have developed a compartmental model of GAS transmission incorporating skin and throat infection separately and allowing for interaction between the two. To address the many uncertainties that exist around GAS transmission and immunity, we used the Metropolis-Hastings algorithm with informative priors to sample parameter space and simulate our model. We conducted three separate explorations to match epidemiologic attributes observed in population settings with different combinations of skin and throat infection prevalence: 1) throat < 10%, skin 30–60%; and 2) throat 5–20%, skin 5–10%; and 3) throat 5–20%, skin 30–60%; where throat infections may be either symptomatic or asymptomatic.
Early analysis of parameter distributions capable of producing these different combinations of skin and throat infection prevalence has shown interesting patterns for further investigation. While some model parameters are similar across the population settings, others such as the duration of infection, show strong tendencies for differences between populations. We are in the process of considering the plausibility of parameter variation across population settings, which may be driven by clinical, molecular and behavioural characteristics. Once we have ascertained the robustness of our parameter distributions, we will simulate vaccination in the model. To represent the variation in mechanism of vaccine candidates currently under development, we will allow for vaccines to act in different ways in the model, such as having reduced impact on skin infection compared to throat infection. We will use the model to determine the importance of the vaccine mechanism in driving likely impact across population settings.