epiMOX

epiMOX analyzes COVID-19 epidemic data in Italy to visualize trends, compute epidemic indicators (including infection rates, recovery patterns, and outbreak hotspots), and generate near-term forecasts using the SUIHTER (Susceptible-Undetected-Infectious-Hospitalized-Treated-Recovered) compartmental model.

Key Features:

• Data Visualization: Visualizes historical and current COVID-19 epidemic trends in Italy.
• Critical Epidemic Indicators: Computes indicators such as infection rates, recovery patterns, and outbreak hotspots to support interpretation of epidemic trajectories.
• Predictive Modeling with SUIHTER: Uses the SUIHTER compartmental model (Susceptible-Undetected-Infectious-Hospitalized-Treated-Recovered) to produce near-term forecasts of epidemic evolution.

Scientific Applications:

• Epidemiological Research: Enables analysis of COVID-19 spread and assessment of containment measures and interventions in Italy.
• Public Health Policy Development: Provides indicators and forecasts to inform public health decision-making and response planning.
• Educational Use: Illustrates the integration of epidemic data analysis and compartmental modeling for training in epidemiology and bioinformatics.

Methodology:

Analyzes historical and current epidemic data and integrates them with the SUIHTER compartmental model to produce retrospective analyses and near-term forecasts.