Genomic surveillance at scale is required to detect newly emerging strains at an early timepoint

Abstract

AbstractGenomic surveillance in the setting of the coronavirus disease 2019 (COVID-19) pandemic has the potential to identify emerging SARS-CoV-2 strains that may be more transmissible, virulent, evade detection by standard diagnostic tests, or vaccine escapes. The rapid spread of the SARS-CoV-2 B.1.1.7 strain from southern England to other parts of the country and globe is a clear example of the impact of such strains. Early discovery of the B.1.1.7 strain was enabled through the proactive COVID-19 Genomics UK (COG-UK) program and the UK’s commitment to genomic surveillance, sequencing about 10% of positive samples.1 In order to enact more aggressive public health measures to minimize the spread of such strains, genomic surveillance needs to be of sufficient scale to detect early emergence and expansion in the broader virus population. By modeling common performance characteristics of available diagnostic and sequencing tests, we developed a model that assesses the sampling required to detect emerging strains when they are less than 1% of all strains in a population. This model demonstrates that 5% sampling of all positive tests allows the detection of emerging strains when they are a prevalence of 0.1% to 1.0%. While each country will determine their risk tolerance for the emergence of novel strains, as vaccines are distributed and we work to end the pandemic and prevent future SARS-CoV-2 outbreaks, genomic surveillance will be an integral part of success.