Network-compartmental modeling for assessing core drivers of fascioliasis dissemination in definitive hosts

Fascioliasis is a neglected zoonotic disease caused by Fasciola species, affecting livestock and humans worldwide and imposing substantial economic and public health burdens. Conventional compartmental models commonly assume homogeneous mixing and therefore may not adequately represent the heterogeneous contact patterns characteristic of smallholder farming systems. This study develops a network-informed multi-host compartmental model that integrates a Watts–Strogatz small-world contact network with effective exposure coefficients representing local and long-range connectivity among cattle, humans, snails, and environmental metacercariae. The framework incorporates short-range transmission within local communities and long-range transmission between geographically separated farming communities. Analytical results establish the basic reproduction number ( \(R_0\) ), demonstrate global asymptotic stability of the disease-free equilibrium when \(R_0<1\) , and provide a Jacobian-based criterion for local asymptotic stability of the endemic equilibrium. Numerical simulations characterize the temporal dynamics of infection and quantify the effects of treatment, environmental sanitation, network connectivity, and local exposure structure on transmission. Increased network connectivity and long-range interactions facilitate wider spatial dissemination, whereas reductions in transmission and environmental contamination suppress infection. The results demonstrate that incorporating network structure into fascioliasis transmission models provides a more realistic representation of heterogeneous contact processes and offers a quantitative framework for evaluating targeted control strategies in interconnected livestock and human communities.