2019nCoVAS

2019nCoVAS analyzes SARS-CoV-2 genomic data, predicts epidemic transmission trends, and evaluates population psychological stress associated with the COVID-19 pandemic.

Key Features:

• Epidemic Transmission Prediction: Applies computational and statistical models to forecast COVID-19 transmission dynamics using epidemiological data.
• LAUP Genome Analysis: Performs Lineage-Associated Underrepresented Permutation (LAUP) analysis to investigate mutation patterns and lineage diversification in SARS-CoV-2 genomes.
• Psychological Stress Evaluation: Assesses public psychological stress during the COVID-19 pandemic using a specialized emotional dictionary developed for COVID-19-related contexts.

Scientific Applications:

• Epidemiological Modeling: Supports prediction of SARS-CoV-2 transmission patterns for outbreak analysis and intervention planning.
• Viral Genomics: Enables investigation of SARS-CoV-2 mutation dynamics and lineage evolution using genome sequence analysis.
• Public Health Psychology: Facilitates assessment of psychological stress responses associated with the COVID-19 pandemic.

Methodology:

The platform applies statistical transmission prediction models to epidemiological data, performs Lineage-Associated Underrepresented Permutation (LAUP) analysis on SARS-CoV-2 genome sequences, and evaluates psychological stress using a COVID-19–specific emotional dictionary applied to text-based data.