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Updated: Aug 1, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Sample size calculations for pathogen variant surveillance in the presence of biological and systematic biases
Shirlee Wohl1, Elizabeth C Lee2, Bethany L DiPrete3
1Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA; Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA.
Abstract:
Tracking the emergence and spread of pathogen variants is an important component of monitoring infectious disease outbreaks. To that end, accurately estimating the number and prevalence of pathogen variants in a population requires carefully designed surveillance programs. However, current approaches to calculating the number of pathogen samples needed for effective surveillance often do not account for the various processes that can bias which infections are detected and which samples are ultimately characterized as a specific variant. In this article, we introduce a framework that accounts for the logistical and epidemiological processes that may bias variant characterization, and we demonstrate how to use this framework (implemented in a publicly available tool) to calculate the number of sequences needed for surveillance. Our framework is designed to be easy to use while also flexible enough to be adapted to various pathogens and surveillance scenarios.
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