models

Various tools for investigate the data in this data portal or models

👥 The Age-Structured SIR Model: Demographics in Disease Dynamics

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📉 Conceptual Overview Infectious disease transmission rarely occurs in a homogeneous population. Real epidemics are shaped by age-specific biological susceptibility, social behavior, and contact patterns. The Age-Structured SIR Model explicitly incorporates these heterogeneities by partitioning the population into discrete age cohorts and coupling them through age-dependent contact rates. This framework is fundamental for designing targeted … Read more

📊 The Age-of-Infection Model: Precision in Epidemic Modeling

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📈 Overview and Conceptual Motivation In classical epidemiology, it is often assumed that all infected individuals are equally infectious throughout their infectious period. The Age-of-Infection (also called Infection-Age) Model relaxes this assumption by explicitly recognizing that both infectiousness and removal depend on the time elapsed since infection. This framework is essential for diseases in which … Read more

🌡️ Climate-Sensitive Mechanistic Models: The Core of Vector-Borne Disease Forecasting

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Mechanistic (process-based) epidemiological models derived from the Ross–MacDonald framework form the backbone of vector-borne disease forecasting. These models explicitly encode biological and ecological processes and allow climatic drivers—particularly temperature (T) and precipitation (P)—to directly modulate transmission dynamics. By embedding climate-dependent functions into transmission, survival, and incubation processes, these models provide a principled framework for projecting … Read more

🔬 Synergistic Spatial Modeling: Coupling PDEs and ABMs for Viral Dynamics

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🧭 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

🔬 Stochastic Efficiency: The Compartment–Agent Mixed Model (CAMM)

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🧭 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

🐼 Pandaesim: Stochastic Simulation for Age-Structured Epidemic Dynamics

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🧭 Overview Pandaesim is an epidemic spreading simulator designed to analyze complex infectious disease dynamics using stochastic or deterministic age-structured compartmental models embedded within a meta-population framework. It was developed to study large-scale epidemics such as COVID-19, where age-specific susceptibility, contact behavior, and spatial movement strongly influence transmission patterns. By combining age stratification with an … Read more

💧 Hydrology Meets Epidemiology: The HYDREMATS Vector Model

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🧭 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

🦟 MOMA: A Spatially Explicit Agent-Based Model for Aedes aegypti Population Dynamics

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🧭 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: Hierarchical Mobility Meets Epidemic Dynamics 📈

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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 Networks in Epidemiology: Tracking Epidemic Spread through Human Mobility

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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