🧬 Overview and Conceptual Motivation In infectious disease modeling, the choice of the incidence function fundamentally shapes how transmission risk is represented. The Frequency-Dependent Incidence SIR model, also known as the Standard Incidence model, is designed for settings in which the number of contacts an individual makes per unit time is independent of total population … Read more
🧭 Overview Hybrid epidemiological models represent a major methodological advancement by explicitly coupling Agent-Based Models (ABMs) with Partial Differential Equation (PDE) frameworks. This approach addresses a central limitation in large-scale epidemic modeling: ABMs provide realistic, individual-level resolution but become computationally prohibitive at scale, while PDEs efficiently describe continuous spatial spread but lack behavioral granularity. Hybrid … Read more
🧭 Overview The Compartment–Agent Mixed Model (CAMM) is a stochastic epidemiological modeling framework designed to overcome the computational limitations of large-scale Agent-Based Models while preserving essential stochastic behavior. CAMM provides a hybrid paradigm that combines the mathematical clarity and efficiency of classical compartmental models with the flexibility of agent-based simulation. Instead of modeling every individual … Read more
🧭 Overview The HYDREMATS (Hydrology, Entomology, and Malaria Transmission Simulation) model is a spatially explicit Agent-Based Model designed to simulate malaria vector dynamics, particularly for Anopheles mosquito species, at the village scale. Its defining characteristic is the tight yet modular coupling of a distributed hydrology model with a mosquito agent-based model, allowing environmental physics to … Read more
🧭 Overview The MOMA (Model Of Mosquito Aedes) is a spatially explicit Agent-Based Simulation Model designed to investigate the population dynamics of the female Aedes aegypti mosquito, the principal vector of Dengue virus. The model represents mosquitoes as individual agents interacting with a heterogeneous environment, allowing localized biological processes and spatial constraints to collectively generate … 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
Trajectory Network modeling is an advanced approach at the intersection of spatial epidemiology, network science, and human mobility analysis. It focuses on epidemic spreading driven by explicit individual movement paths—such as pedestrian trajectories, commuting routes, or vehicular flows—rather than assuming static contacts or homogeneous mixing. By transforming raw trajectory data into dynamic networks, this framework … Read more
Dynamic Network Models are a central class of tools in mathematical epidemiology for studying infectious disease spread in populations characterized by heterogeneous and time-varying contact patterns. Unlike classical compartmental models that assume homogeneous mixing, these models explicitly represent individuals and their evolving interactions, making them particularly effective for identifying the source of an epidemic and … Read more
The Bidirectional Mobility Model, when implemented as an Agent-Based Model (ABM), is designed to capture the dynamic spatial spread of infectious diseases driven by the movement of individuals between discrete, geographically distinct locations, such as neighborhoods, cities, or regions. In this framework, the population is represented as a collection of agents, each possessing both a … Read more
Multilayer Network Agent-Based Models (ABMs) represent a major advance in epidemiological modeling by explicitly recognizing that individuals simultaneously participate in multiple, distinct contact environments, such as households, workplaces, schools, and the broader community. In this framework, the population is modeled as a single set of agents, while interactions are represented through several superimposed network layers, … Read more