COVID-TRACK

COVID-TRACK analyzes COVID-19 testing rates, incidence, hospitalizations, and deaths across US states and countries worldwide to enable comparative time-series assessment of pandemic trends.

Key Features:

• Time-series visualization: Graphical displays enable simultaneous assessment and comparison of time trends in testing, incidence, hospitalizations, and deaths.
• Data integration: Combines testing, incidence, hospitalization, and death data to provide a multi-modal view of epidemic trajectory.
• Adjustments for reporting biases: Accounts for variable testing rates and reporting delays by integrating multiple metrics.
• Transformations: Supports per capita calculations, log scale adjustments, and moving averages for normalization and smoothing.
• Geographic comparison: Enables comparative analysis across states within the USA and countries worldwide.
• Implementation: Implemented as a Python-based web application for computational analysis and visualization.

Scientific Applications:

• Surveillance and monitoring: Monitor and compare epidemic trajectories across regions using integrated metrics and time-series plots.
• Bias-aware trend detection: Detect true infectious surges by combining testing, incidence, hospitalization, and death data and applying transformations.
• Policy evaluation: Evaluate the impact of mitigation strategies across jurisdictions through comparative time-series analyses.
• Public health planning: Inform public health response and strategic decision-making by summarizing regional trends and normalized metrics.

Methodology:

Implemented in Python as a web application; generates graphical time-series displays and integrates testing, incidence, hospitalization, and death data using per capita calculations, log scale adjustments, and moving averages for comparative analysis across US states and countries.