HYPER

HYPER optimizes pooled testing strategies to increase the efficiency of SARS-CoV-2 (COVID-19) screening through hypergraph factorizations.

Key Features:

• Hypergraph Factorization: Uses hypergraph factorizations to design pooling strategies that maximize use of limited resources such as reagents and samples while maintaining detection sensitivity.
• Efficiency and Flexibility: Adapts pooling designs to varying resource constraints to improve testing throughput across different scenarios.
• Simplicity in Design: Produces simple pooling designs applicable across different testing environments.
• Theoretical and Empirical Validation: Provides theoretical characterizations within a general statistical model and evaluates performance via realistic simulations incorporating epidemic spread dynamics and within-host viral kinetics.
• Performance Benchmarking: Compares against other group testing methods and demonstrates competitive or superior performance in resource-constrained settings.

Scientific Applications:

• Large-scale SARS-CoV-2 screening: Enables pooled-specimen testing to screen larger populations with fewer tests under reagent and sample constraints.
• Evaluation of group testing strategies: Allows assessment of pooling designs using simulations of epidemic spread dynamics and within-host viral kinetics.

Methodology:

Designs pooling strategies by hypergraph factorizations, applies theoretical characterization within a general statistical model, and evaluates strategies using realistic simulations that incorporate epidemic spread dynamics and within-host viral kinetics.