UTLDR

UTLDR simulates infectious disease transmission and evaluates public health interventions, including lockdowns, testing, contact tracing, and "what if" scenarios relevant to SARS-CoV-2.

Key Features:

• Agent-Based Modeling: Uses an agent-based approach to simulate autonomous agents with population stratification by age, gender, geographical location, and mobility patterns.
• Scenario Simulation: Generates hypothetical epidemic scenarios that combine multiple public interventions (lockdowns, testing, contact tracing) to assess their interactions and effects.
• Generic Framework: Provides a disease-agnostic modeling framework applicable across different infectious diseases, emphasizing qualitative assessment of public health restrictions over precise forecasting.

Scientific Applications:

• Public Health Planning: Evaluates potential outcomes of intervention strategies to inform policy decisions.
• Epidemiological Research: Studies interactions between population characteristics and intervention measures to analyze disease spread dynamics.
• Educational Uses: Illustrates principles of epidemic modeling and the effects of public health interventions for teaching purposes.

Methodology:

Agent-based modeling that simulates actions and interactions of autonomous agents with detailed population stratification and configurable intervention scenarios.