Abstract
In late December 2019, a cluster of pneumonia cases of unknown aetiology was reported linked to a market in Wuhan, China1. The causative agent was identified as the Coronavirus species related to severe acute respiratory syndrome and was named SARS-CoV-2. By April 16, the virus had spread to 185 different countries, infected more than 2,000,000 people and caused more than 130,000 deaths. In the Netherlands, the first case of SARS-CoV-2 was reported on February 27. The outbreak began with several different introductory events from Italy, Austria, Germany, and France, followed by a local amplification in, and later also outside, the southern Netherlands.
The combination of near-real-time whole genome sequence analysis and epidemiology resulted in reliable assessments of the extent of SARS-CoV-2 transmission in the community, facilitating early decision-making to control the local transmission of SARS-CoV-2. SARS-CoV-2 in the Netherlands. We demonstrate how this data was generated and analyzed, and how SARS-CoV-2 whole-genome sequencing, in combination with epidemiological data, was used to inform public health decision-making in the Netherlands.
Methods
- COVID-19 response
This study was carried out in collaboration with the national outbreak response team. This team develops a guide on case detection and containment, based on recommendations and expert advice from WHO and the European Center for Disease Prevention and Control, as defined by the crisis response structure and emergencies. The diagnoses were initially made in suspected cases with a history of recent travel to China, but between February 25 and 28, suspected cases with a history of travel to affected municipalities in northern Italy were also analyzed.
Between March 1 and 11, all suspected cases with a history of travel to the four northern Italian provinces were analyzed, and after March 11, all suspected cases with a history of travel to Italy were analyzed. The sequencing effort was included in the tiered response to the outbreak, which evolved from the initial testing of symptomatic travellers, including testing of symptomatic contacts (phase 1), followed by the inclusion of routine testing of hospitalized patients with severe respiratory infections (phase 2), up to the inclusion of healthcare workers with a low-threshold case definition and tests to define the scope of suspected clusters (phase 3).
Depending on the phase and clinical severity, initial contact with patients was established through public health doctors or nurses from the municipal health service (for cases related to travel, case contacts (hospitalized) and patients belonging to risk groups ). The different phases of this study were based on the observations described in this manuscript. Ethical approval was not required for this study as only anonymous aggregated data was used and no medical interventions were performed on human individuals.
- Contact tracking
On January 29, COVID-19 was classified as a notifiable disease in group A in the Netherlands, and doctors and laboratories had to report any suspected and confirmed cases by phone to the Dutch public health services (PHS ). Upon notification, PHS initiates source identification and contact tracing and conducts risk assessments. In the initial phase of the outbreak (containment), the PHS tracked down and reported all high- and low-risk case contacts with the goal of stopping transmission. For each case, epidemiological information such as demographic information, symptoms, symptom onset date, travel history, contact information, suspected source, underlying disease, and occupation was recorded.
People were asked to report their travel history for the past 14 days, including possible trips to multiple countries. Due to the magnitude of the COVID-19 outbreak, this quickly became impractical in severely affected regions, and the strategy changed to only record data on confirmed cases and inform their high-risk contacts (phase 2) with ongoing active search. cases in fewer affected regions. The PHS informed the Netherlands National Public Health Authority (RIVM) of all laboratory-confirmed cases. There, a national registry of cases was maintained in which a contact matrix of the first 250 cases was maintained.
- Selection of samples
In the first phase, all the samples were selected for sequencing, reflecting the cases associated with travel and their contacts. In the second phase, priority was given to patients identified through better case finding by testing hospitalized patients with severe acute respiratory infections and continually sequencing new incursions. In the third phase, the epidemic began to expand exponentially and sequencing was carried out to continue monitoring the evolution of the outbreak. According to the national testing policy, a substantial proportion of the newly sequenced cases were TS (20%).
- SARS-CoV-2 diagnosis
Clinical samples were collected and the focal distemper virus was added as an internal nucleic acid (NA) extraction control to the supernatant. Clinical samples included oropharyngeal and nasopharyngeal swabs, bronchoalveolar lavage, and sputum. Total NA was extracted from the supernatant using Roche MagNA Pure systems. NA was screened for the presence of SARS-CoV-2 using real-time single-plex reverse-transcription PCR for the focal distemper virus, for the SARS-CoV-2 RdRp gene, and for the SARS-CoV gene.
- SARS-CoV-2 WGS
A SARS-CoV-2-specific multiplex PCR was performed for nanopore sequencing, similar to amplicon-based approaches as previously described. Briefly, primers for 89 overlapping genome-spanning amplicons were designed using primal. The length of the amplicon was established at 500 base pairs with an overlap of 75 base pairs between the different amplicons. Libraries were generated using Nanopore’s native barcode kits (EXP-NBD104, EXP-NBD114 and SQK-LSK109) and sequenced in a cell of R9.4 stream multiplexing up to 24 samples per sequence run.
- Phylogenetic analysis
All available complete SARS-CoV-2 genomes were retrieved from GISAID on March 22, 2020, and aligned to the Dutch SARS-CoV-2 sequences from this study using MUSCLE. Sequences with> 10% “N” were excluded. The alignment was manually checked for discrepancies, after which IQ-TREE26 was used to perform a maximum likelihood phylogenetic analysis under the GTR + F + I + G4 model as the best-predicted model using the ultrafast start option with 1,000. repetitions. Phylogenetic trees were visualized using custom Python and Baltic scripts.