COVIDSpread

COVIDSpread predicts short-term COVID-19 spread by integrating real-time epidemiological data with advanced time series models that capture non-linear dynamics.

Key Features:

• Real-Time Data Integration: Ingests and updates analyses with real-time COVID-19 epidemiological data streams.
• Advanced Time Series Modeling: Implements time series statistical models capable of capturing non-linear patterns for improved short-term predictions of virus spread.
• Customizable Model Development: Enables development and comparison of multiple predictive models across specified time windows and differing assumptions.

Scientific Applications:

• Short-Term Forecasting: Produces short-term predictions of COVID-19 spread to assess near-term epidemic trends.
• Scenario Analysis and Hypothesis Testing: Supports scenario-based analyses and hypothesis testing via customizable model configurations.
• Public Health Decision Support: Provides actionable insights to inform response strategies, resource allocation, and policy development.

Methodology:

The methodology integrates real-time COVID-19 data streams with time series statistical methods that capture non-linearities, supports development and comparison of multiple models across different temporal segments and assumptions, and incorporates real-time data visualization.