State and parameter estimation for a class of schistosomiasis models.

Area of Science:

• Epidemiology
• Mathematical Biology
• Public Health

Background:

• Schistosomiasis remains a significant global health concern, necessitating accurate transmission parameter estimation.
• Control strategies rely on understanding snail-human transmission dynamics and snail infection proportions.

Purpose of the Study:

• To develop a general framework for estimating schistosomiasis transmission parameters and infected snail proportions.
• To provide tools for optimizing schistosomiasis control strategies through accurate data-driven insights.

Main Methods:

• Utilized a homogeneous version of the MacDonald's model for schistosomiasis dynamics.
• Designed an auxiliary dynamical system (observer) for exponential convergence to schistosomiasis model solutions.
• Extended the framework to a heterogeneous model incorporating multiple human groups and freshwater habitats.

Main Results:

• Successfully derived estimations for the snail-human transmission rate.
• Developed a method to estimate the proportion of infected snails in each habitat using human worm burden data.
• The framework enables mapping of infection hotspots for targeted interventions.

Conclusions:

• The developed framework offers a robust approach to estimating key schistosomiasis transmission parameters.
• This method provides crucial data for implementing effective, geographically targeted control strategies.
• The findings support enhanced efforts in molluscicide application and mass drug administration for schistosomiasis elimination.