Post by Nadica (She/Her) on Jul 26, 2024 3:12:16 GMT
Combining individual and wastewater whole genome sequencing improves SARS-CoV-2 surveillance - Preprint Posted July 22, 2024
ABSTRACT
Background Robust methods to track pathogens support public health surveillance. Both wastewater (WW) and individual whole genome sequencing (WGS) are used to assess viral variant diversity and spread. However, their relative performance and the information provided by each approach have not been sufficiently quantified. Therefore, we conducted a comparative evaluation using extensive individual and wastewater longitudinal SARS-CoV-2 WGS datasets in Northern Ireland (NI).
Methods WGS of SARS-CoV-2 was performed on >4k WW samples and >23k individuals across NI from 14th November 2021 to 11th March 2023. SARS-CoV-2 RNA was amplified using the ARTIC nCov-2019 protocol and sequenced on an Illumina MiSeq. Wastewater data were analysed using Freyja to determine variant compositions, which were compared to individual data through time series and correlation analyses. Inter-programme agreements were evaluated by mean absolute error (MAE) calculations. WW treatment plant (WWTP) performances were ranked by mean MAE. Volatile periods were identified using numerical derivative analyses. Geospatial spreading patterns were determined by horizontal curve shifting.
Findings Strong concordance was observed between wastewater and individual variant compositions and distributions, influenced by sequencing rate and variant diversity. Overall variant compositions derived from individual sequences and each WWTP were regionally clustered rather than dominated by local population size. Both individual and WW sequencing detected common nucleotide substitutions across many variants and complementary additional substitutions. Conserved spreading patterns were identified using both approaches.
Interpretation Both individual and wastewater WGS effectively monitor SARS-CoV-2 variant dynamics. Combining these approaches enhances confidence in predicting the composition and spread of major variants, particularly with higher sequencing rates. Each method detects unique mutations, and their integration improves overall genome surveillance.
ABSTRACT
Background Robust methods to track pathogens support public health surveillance. Both wastewater (WW) and individual whole genome sequencing (WGS) are used to assess viral variant diversity and spread. However, their relative performance and the information provided by each approach have not been sufficiently quantified. Therefore, we conducted a comparative evaluation using extensive individual and wastewater longitudinal SARS-CoV-2 WGS datasets in Northern Ireland (NI).
Methods WGS of SARS-CoV-2 was performed on >4k WW samples and >23k individuals across NI from 14th November 2021 to 11th March 2023. SARS-CoV-2 RNA was amplified using the ARTIC nCov-2019 protocol and sequenced on an Illumina MiSeq. Wastewater data were analysed using Freyja to determine variant compositions, which were compared to individual data through time series and correlation analyses. Inter-programme agreements were evaluated by mean absolute error (MAE) calculations. WW treatment plant (WWTP) performances were ranked by mean MAE. Volatile periods were identified using numerical derivative analyses. Geospatial spreading patterns were determined by horizontal curve shifting.
Findings Strong concordance was observed between wastewater and individual variant compositions and distributions, influenced by sequencing rate and variant diversity. Overall variant compositions derived from individual sequences and each WWTP were regionally clustered rather than dominated by local population size. Both individual and WW sequencing detected common nucleotide substitutions across many variants and complementary additional substitutions. Conserved spreading patterns were identified using both approaches.
Interpretation Both individual and wastewater WGS effectively monitor SARS-CoV-2 variant dynamics. Combining these approaches enhances confidence in predicting the composition and spread of major variants, particularly with higher sequencing rates. Each method detects unique mutations, and their integration improves overall genome surveillance.