Guiding the design of SARS-CoV-2 genomic surveillance by estimating the resolution of outbreak detection

Abstract

Genomic surveillance of SARS-CoV-2 has been essential to inform public health response to outbreaks. The high incidence of infection has resulted in a smaller proportion of cases undergoing whole genome sequencing due to finite resources. We present a framework for estimating the impact of reduced depths of genomic surveillance on the resolution of outbreaks, based on a clustering approach using pairwise genetic and temporal distances. We apply the framework to simulated outbreak data to show that outbreaks are detected less frequently when fewer cases are subjected to whole genome sequencing. The impact of sequencing fewer cases depends on the size of the outbreaks, and on the genetic and temporal similarity of the index cases of the outbreaks. We also apply the framework to an outbreak of the SARS-CoV-2 Delta variant in New South Wales, Australia. We find that the detection of clusters in the outbreak would have been delayed if fewer cases had been sequenced. Existing recommendations for genomic surveillance estimate the minimum number of cases to sequence in order to detect and monitor new virus variants, assuming representative sampling of cases. Our method instead measures the resolution of clustering, which is important for genomic epidemiology, and accommodates sampling biases.

Advancing pathogen genomics in resource-limited settings

“…Within each country and context, pathogen prioritization for genomic surveillance should also be informed by the epidemiological, biological, and clinical characteristics of pathogens and associated diseases. 18 , 19 Epidemiological parameters include measures of local disease burden, such as national prevalence, geographic distribution, and risk-group characterization; population levels of natural and vaccine-derived immunity; and pathogen-specific risks of local transmission, such as human-to-human transmission or zoonotic spillover. Important biological and clinical characteristics may include the rate of genetic mutations and the consequences of new variants with respect to pathogenicity, transmission, immune escape, and drug resistance (DR).…”