🏗️ Conceptual Overview For many pathogens, infectiousness is not constant over the course of illness. Viral load, symptom severity, and contact behavior often vary markedly between early, peak, and late stages of infection. The Differential Infectivity (Stage-Structured) SEIR Model extends the classical SEIR framework by dividing the infectious period into multiple sequential stages, each with … Read more
Mob-Cov is a stochastic, spatially explicit Agent-Based Model (ABM) developed to analyze COVID-19 transmission under hierarchical geographical mobility patterns. The model represents human movement through nested spatial containers—ranging from rooms and buildings to cities and countries—capturing how multiscale mobility structures shape epidemic diffusion. By embedding stochastic infection processes within realistic mobility hierarchies, Mob-Cov provides a … Read more
Complex network models constitute a core methodology in modern spatial epidemiology, explicitly relaxing the classical assumption of homogeneous mixing. Instead of assuming uniform contact among individuals, these models represent populations as collections of interconnected entities whose interactions govern disease transmission. This approach is particularly essential for infectious diseases such as COVID-19, where heterogeneity in contact … Read more
The SIDARTHE model is an eight-compartment epidemiological model developed to capture the spread of COVID-19 in Italy during early 2020. It extends the classic SIR approach by distinguishing detected vs. undetected infections and different severity levels. In SIDARTHE, individuals progress through stages from susceptible to various infected states (asymptomatic, symptomatic, severe) and eventually to outcomes … Read more