A novel surveillance-based method for estimating the waning of immunity following natural infection

Quantifying the durability of natural immunity is essential for understanding infectious disease dynamics and informing public health strategies. Existing methods typically require detailed longitudinal data rarely available in real-world settings. This study introduces a novel surveillance-based approach to estimate immune waning using routine testing data, providing a practical complement to data-intensive designs.

Mathematical modeling.

The method estimates protection against reinfection as a function of time since prior infection and was applied to national SARS-CoV-2 testing data from Qatar to evaluate the durability of immunity following pre-omicron and omicron infections against homologous reinfection. Waning curves were fitted using Gompertz functions and validated against published estimates.

Application of the method demonstrated distinct patterns in the durability of natural immunity. Pre-omicron infections were associated with strong and sustained protection against reinfection, with minimal evidence of waning over the follow-up period. In contrast, protection following omicron infection, while initially high, declined rapidly in the ensuing months and was largely diminished within approximately one year. The estimated waning immunity curves closely aligned with published estimates, supporting the validity of the introduced approach.

This method offers a practical and adaptable approach for estimating waning immunity, suitable for use across different settings and infectious pathogens.