serocalculator

serocalculator estimates seroincidence rates from cross-sectional serological data using a likelihood-based framework that incorporates antibody decay models, biological variability, and measurement noise under Poisson infection processes.

Key Features:

• Likelihood-based estimation: Estimates seroincidence rates using a statistical framework that models antibody decay, biological variability, and measurement noise.
• Multiple biomarker support: Enables overall and stratified seroincidence estimation using single or multiple biomarkers.
• Three-input architecture: Requires a pre-estimated seroresponse model for post-infection antibody waning, noise parameters for biological and assay-related variability, and quantitative antibody responses from a cross-sectional serosurvey.
• Computational efficiency: Provides computationally efficient estimation for population-level incidence analysis.

Scientific Applications:

• Population-level transmission dynamics: Estimates the rate of new infections in populations to understand pathogen transmission dynamics when clinical surveillance is not feasible or reliable.
• Public health surveillance: Informs public health action by providing seroincidence estimates from cross-sectional serological surveys.
• Stratified epidemiological analysis: Supports stratified seroincidence estimation for subpopulation comparisons.

Methodology:

serocalculator uses a likelihood-based framework incorporating modeled antibody decay, biological variability, and measurement noise to estimate seroincidence rates under Poisson infection processes from cross-sectional serological data.