Epidemiological Modeling of Zoonotic Diseases in Rural Ecosystems

Abstract

Zoonotic diseases account for approximately 60% of all known human infectious diseases. This study develops and validates a multi-host epidemiological modelling framework integrating stochastic SEIR models, agent-based simulation, and spatially explicit network analysis to characterise transmission dynamics of Brucellosis (Brucella abortus), Leptospirosis (Leptospira interrogans), and Q-Fever (Coxiella burnetii) across rural agropastoral landscapes of Estonia, Italy, and Spain. Field surveillance data from 3,847 livestock, 412 wildlife samples, and 284 human seroprevalence records collected over five years (2019-2024) parameterised and validated the models. Basic reproduction number (R0) estimates ranged from 1.84 to 3.47. Sensitivity analysis identified livestock vaccination coverage and wildlife-livestock contact reduction as the two highest-impact interventions, together capable of reducing R0 below 1.0 in 89% of modelled scenarios. Spatiotemporal risk mapping identified 14 high-risk transmission hotspots across the three countries providing actionable targeting for surveillance and intervention resources under One Health frameworks.