Developing molecular surveillance of SARS-CoV-2 in the Czech Republic (2021-2022)

Abstract

Molecular surveillance was widely used during the COVID-19 pandemic to detect rapidly emerging variants and monitor the transmission of SARS-CoV-2 within communities. In 2021, the Czech COVID-19 Genomics Consortium (COG-CZ) was set up to coordinate a new SARS-CoV-2 molecular surveillance network. In the Czech Republic, molecular surveillance employed whole genome sequencing (WGS) and variant discrimination polymerase chain reaction (VD-PCR) on samples collected through passive, active and sentinel surveillance. All WGS data was uploaded to GISAID and the PANGO lineages used by GISAID were compared to the main variants determined by VD-PCR. To assess the effectiveness and reliability of the gathered data in adapting pandemic responses, the capabilities and turnaround times of the molecular surveillance methods are evaluated. VD-PCR results were available within 48 h of sample collection for 81.5% of cases during the Delta/Omicron transition. WGS enabled the detection of low-frequency novel variants in infection clusters. WGS surveillance showed there was community spread of AY.20.1, a variant that gained novel mutations within the Czech Republic. Molecular surveillance informed the implementation of public health measures; temporal comparisons of restrictions and outcomes are described. Further areas for improvement have been identified for monitoring and managing future pandemics.

Keywords: Czech Republic; Molecular surveillance; SARS-CoV-2 variants; Variant discrimination PCR.

Fig. 1

Progression of the COVID-19 pandemic in the Czech Republic in 2021 and 2022. The timeline of pandemic restrictions (Supplementary Table 3) and key points of the vaccination campaign are overlaid over the 7-day running average of daily confirmed cases (blue). Newly introduced restrictions are shown as dates with red outlines, while the lifting of specific restrictions is shown as dates in green, with notable points of the vaccination campaign in yellow. Descriptions of these restrictions are found in Supplementary Table 3. The 7-day running average number of samples sequenced (green), by date of collection, shows the available sequencing capacity as the sequencing network was formalised and came online in 2021.

Fig. 2

Spatiotemporal spread of SARS-CoV-2 variants of concern within the Czech Republic between January and December 2021. The main variants shown are Pre-alpha (B.1.258 and similar), Alpha (B.1.1.7), Delta (B.1.617.2 or AY.X), and Omicron (BA.X), in monthly intervals. The first row shows the total number of positive cases in the regions according to GISAID. The bottom figure shows the frequencies of each variant in the regions.

Fig. 3

Relative distribution of SARS-CoV-2 lineages in the regions of the Czech Republic from January 2021 to December 2022. The relative prevalence of the most abundant SARS-CoV-2 lineages and changes in their distribution over time and across the regions of the Czech Republic.

Fig. 4

Transition from Alpha to Delta variant dominance in 2021 as seen in the frequencies of amino acid mutations in the Spike protein (S) over time. Mutations compared to reference genome NC_045512.2 occurring in more than 10% of weekly isolates where at least three samples contained the mutation. Total number of weekly samples shown on the bottom axis. Common variants and their typical mutations are shown along the right for comparison. Alpha variant frequency decreased from week 17 of 2021 as the Delta variant started spreading. The frequency of Alpha-specific mutations such as S:Del69/70, S:N501Y or S:P681H decreased while the introduction and spread of the Delta variant could be seen in the rising frequency of S:L452R, S:T478K and S:P681R.

Fig. 5

Excess mortality with weekly confirmed cases. Excess mortality is shown as a proportion of mortality during the reference period (2016–2019) along with smoothed weekly confirmed cases. Excess mortality mirrored case numbers in 2021, whereas the Omicron wave in early 2022 saw a dramatic increase in case numbers while excess mortality stayed near baseline levels.

Fig. 6

Comparison of VD-PCR and WGS surveillance. (a) VD-PCR results were available much sooner than WGS results, which had an inconsistent turnaround time. (b) The plot shows the number of samples analysed by VD-PCR assays stratified by the variant determined by WGS and the agreement of identified variants. (c) Emergence of novel variants in 2021 and 2022 saw dramatic increases in the number of novel mutations (show in red) as the Delta and Omicron variant emerged, resulting in increasing phylogenetic heterogeneity.

Fig. 6

Comparison of VD-PCR and WGS surveillance. (a) VD-PCR results were available much sooner than WGS results, which had an inconsistent turnaround time. (b) The plot shows the number of samples analysed by VD-PCR assays stratified by the variant determined by WGS and the agreement of identified variants. (c) Emergence of novel variants in 2021 and 2022 saw dramatic increases in the number of novel mutations (show in red) as the Delta and Omicron variant emerged, resulting in increasing phylogenetic heterogeneity.