Substantiation for the choice of sample size calculation methods for effective monitoring of relevant pathogens within genomic epidemiological surveillance

Introduction. Continuous monitoring of the epidemiological situation is one of the key elements of a country's biological safety. The development and increasing accessibility of high-throughput sequencing technologies have led to the incorporation of genomic data into public health decision-making systems, known as genomic epidemiological surveillance. Effective implementation of genomic epidemiological surveillance for circulating pathogens requires finding a balance between data generation speed, estimation accuracy, and rational use of resources. Consequently, there is a need to develop evidence-based strategies for biological sample selection. Aim: To justify the choice of methods for calculating the minimum sufficient sample size for sequencing depending on the objectives of epidemiological surveillance. Materials and methods. This study presents a comparative analysis of two approaches to genomic monitoring: routine surveillance and targeted sentinel surveillance. The choice of statistical approaches for calculating the minimum sufficient sample size for each objective is justified, with specific examples that allow determining the required sequencing volume taking into account the current epidemiological situation and the prevalence of pathogen variants in the population. Results. The study presents sample size calculation results depending on the objective: establishing the proportion of existing variants for routine surveillance, or detecting rare variants within sentinel surveillance at a predetermined prevalence threshold for a rare/new variant with a specified probability. For routine surveillance, the sample size was calculated based on the requirement for estimation precision of proportions (margin of error 5%) at a confidence level of 95%. For sentinel surveillance, the sample size was calculated under the condition that the probability of missing a variant (not detecting a single case) does not exceed 5%. The statistical results are presented in the form of graphs and calculation tables. Conclusion. The proposed methods for calculating sample sizes for genomic monitoring depending on the objective can serve as a practical tool for epidemiological surveillance, increasing its efficiency. The use of these calculation methods will make it possible to obtain mathematically sound results regarding the genotypes of circulating pathogens and their degree of representation in the population.