Work

Optimal capacity sharing for global genomic surveillance

Year: 2023

Type: article

Abstract: Recent technological advances and substantial cost reductions have made the genomic surveillance of pathogens during pandemics feasible. Our paper focuses on full genome sequencing as a tool that can serve two goals: the estimation of variant prevalences, and the identification of new variants. Assuming that capacity constraints limit the number of samples that can be sequenced, we solve for the optimal distribution of these capacities among countries. Our results show that if the principal goal of sequencing is prevalence estimation, then the optimal capacity distribution is less than proportional to the weights (e.g., sizes) of countries. If, however, the main aim of sequencing is the detection of new variants, capacities should be allocated to countries or regions that have the most infections. Applying our results to the sequencing of SARS-CoV-2 in 2021, we provide a comparison between the observed and a suggested optimal capacity distribution worldwide and in the EU. We believe that following such quantifiable guidance will increase the efficiency of genomic surveillance for pandemics.

Source: Epidemics

DOI: 10.1016/j.epidem.2023.100690

Authors: Zsombor Z. Méder, Robert Somogyi

Institutions: Leiden University, Budapest University of Technology and Economics, Institute of Economics, ELTE Centre for Economic and Regional Studies

Language: English

Topic: COVID-19 epidemiological studies

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,860