ModInterv

ModInterv applies growth models and mathematical modeling techniques to analyze epidemic time-series data and generate location-specific projections for monitoring and predicting outbreak progression, including COVID-19.

Key Features:

• Growth models: Employs growth models to fit epidemic time-series data and characterize outbreak evolution.
• Location-specific analysis: Supports analysis at country, state, and city levels, explicitly including countries worldwide and states and cities within the USA and Brazil.
• Projections and analyses: Generates projections and analytical outputs from inputted location-specific epidemic data.

Scientific Applications:

• Epidemiological research: Provides fitted growth-model outputs and time-series analyses to support study of epidemic dynamics.
• Public health decision-making: Produces projections and trend analyses to inform technical committees and government authorities about epidemic progression.
• Adaptability to other epidemics: Applies the same growth-model methodology to diseases beyond COVID-19 for monitoring and projection purposes.

Methodology:

Applies mathematical growth-modeling techniques to fit location-specific epidemic time-series data and generate projections and analytical outputs.