Revisiting the impact of Schistosoma mansoni regulating mechanisms on transmission dynamics using SchiSTOP, a novel...

The transmission cycle of Schistosoma is remarkably complex, including sexual reproduction in human hosts and asexual reproduction in the intermediate host (freshwater snails). Patterns of rapid recrudescence after treatment and stable low transmission are often observed, hampering the achievement of control targets. Current mathematical models commonly assume regulation of transmission to occur at worm level through density-dependent egg production. However, conclusive evidence on this regulating mechanism is weak, especially for S. mansoni. In this study, we explore the interplay of different regulating mechanisms and their ability to explain observed patterns in S. mansoni epidemiology.

We developed SchiSTOP: a hybrid stochastic agent-based and deterministic modelling framework for S. mansoni transmission in an age-structured human population. We implemented different models with regulating mechanisms at: i) worm-level (density-dependent egg production), ii) human-level (anti-reinfection immunity), and iii) snail-level (density-dependent snail dynamics). Additionally, we considered two functional choices for the age-specific relative exposure to infection. We assessed the ability of each model to reproduce observed epidemiological patterns pre- and post-control, and compared successful models in their predictions of the impact of school-based and community-wide treatment. Simulations confirmed that assuming at least one regulating mechanism is required to reproduce a stable endemic equilibrium. Snail-level regulation was necessary to explain stable low transmission, while models combining snail- and human-level regulation with an age-exposure function informed with water contact data were successful in reproducing a rapid rebound after treatment. However, the predicted probability of reaching the control targets varied largely across models.

The choice of regulating mechanisms in schistosomiasis modelling largely determines the expected impact of control interventions. Overall, this work suggests that reaching the control targets solely through mass drug administration may be more challenging than currently thought. We highlight the importance of regulating mechanisms to be included in transmission models used for policy.