Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data

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Abstract

Genome sequences from evolving infectious pathogens allow quantification of case introductions and local transmission dynamics. We sequenced 11,357 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Switzerland in 2020 - the sixth largest effort globally. Using a representative subset of these data, we estimated viral introductions to Switzerland and their persistence over the course of 2020. We contrasted these estimates with simple null models representing the absence of certain public health measures. We show that Switzerland’s border closures de-coupled case introductions from incidence in neighboring countries. Under a simple model, we estimate an 86–98% reduction in introductions during Switzerland’s strictest border closures. Furthermore, the Swiss 2020 partial lockdown roughly halved the time for sampled introductions to die out. Last, we quantified local transmission dynamics once introductions into Switzerland occurred, using a phylodynamic model. We found that transmission slowed 35–63% upon outbreak detection in summer 2020, but not in fall. This finding may indicate successful contact tracing over summer before overburdening in fall. The study highlights the added value of genome sequencing data for understanding transmission dynamics.

Abstract

Phylogenetic and phylodynamic methods quantify the drop in case introductions and local transmission with implementation of public health measures.

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Most cited references 36

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Fast and accurate short read alignment with Burrows–Wheeler transform

Heng Li, Richard Durbin (2009)

Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk

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IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

Lam-Tung Nguyen, Heiko Schmidt, Arndt von Haeseler … (2014)

Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.

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A new coronavirus associated with human respiratory disease in China

Fan Wu, Su Zhao, Bin Yu … (2020)

Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health 1–3 . Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing 4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here ‘WH-Human 1’ coronavirus (and has also been referred to as ‘2019-nCoV’). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China 5 . This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.

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Author and article information

Contributors

Sarah A. Nadeau: Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SoftwareRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Timothy G. Vaughan: Role: Formal analysisRole: MethodologyRole: SoftwareRole: Visualization

Christiane Beckmann:

ORCID: https://orcid.org/0000-0001-9030-083X

Role: Resources

Ivan Topolsky:

ORCID: https://orcid.org/0000-0002-7561-0810

Role: Data curationRole: SoftwareRole: ValidationRole: Writing - review & editing

Chaoran Chen:

ORCID: https://orcid.org/0000-0002-8763-2937

Role: Data curationRole: Software

Emma Hodcroft:

ORCID: https://orcid.org/0000-0002-0078-2212

Role: ConceptualizationRole: Writing - review & editing

Tobias Schär: Role: Resources

Ina Nissen: Role: Investigation

Natascha Santacroce: Role: Validation

Elodie Burcklen: Role: Investigation

Pedro Ferreira:

ORCID: https://orcid.org/0000-0003-0559-6125

Role: Software

Kim Philipp Jablonski:

ORCID: https://orcid.org/0000-0002-4166-4343

Role: SoftwareRole: Validation

Susana Posada-Céspedes:

ORCID: https://orcid.org/0000-0002-7459-8186

Role: ResourcesRole: SoftwareRole: Writing - review & editing

Vincenzo Capece: Role: Software

Sophie Seidel:

ORCID: https://orcid.org/0000-0002-4484-9888

Role: Data curationRole: InvestigationRole: Methodology

Noemi Santamaria de Souza:

ORCID: https://orcid.org/0000-0001-7134-7480

Role: Data curationRole: InvestigationRole: Software

Phil Cheng:

ORCID: https://orcid.org/0000-0003-2940-006X

Role: InvestigationRole: Resources

Philipp P. Bosshard:

ORCID: https://orcid.org/0000-0002-1154-2281

Role: ConceptualizationRole: ResourcesRole: ValidationRole: Writing - review & editing

Mitchell P. Levesque:

ORCID: https://orcid.org/0000-0001-5902-9420

Role: Data curationRole: Funding acquisitionRole: ResourcesRole: SupervisionRole: VisualizationRole: Writing - review & editing

Verena Kufner:

ORCID: https://orcid.org/0000-0003-4233-5952

Role: InvestigationRole: Writing - review & editing

Stefan Schmutz:

ORCID: https://orcid.org/0000-0002-1955-7007

Role: Investigation

Maryam Zaheri:

ORCID: https://orcid.org/0000-0003-2777-835X

Role: InvestigationRole: Writing - review & editing

Michael Huber:

ORCID: https://orcid.org/0000-0002-0384-0000

Role: Data curationRole: InvestigationRole: Resources

Alexandra Trkola:

ORCID: https://orcid.org/0000-0003-1013-876X

Role: InvestigationRole: Resources

Samuel Cordey:

ORCID: https://orcid.org/0000-0002-2684-5680

Role: Writing - review & editing

Florian Laubscher:

ORCID: https://orcid.org/0000-0002-8803-981X

Role: Data curationRole: Formal analysis

Ana Rita Gonçalves:

ORCID: https://orcid.org/0000-0002-7893-0158

Role: Data curationRole: InvestigationRole: ResourcesRole: Writing - review & editing

Sébastien Aeby:

ORCID: https://orcid.org/0000-0001-9726-7438

Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: Writing - original draft

Trestan Pillonel:

ORCID: https://orcid.org/0000-0002-5725-7929

Role: Data curationRole: InvestigationRole: ResourcesRole: Writing - review & editing

Damien Jacot: Role: InvestigationRole: ResourcesRole: Validation

Claire Bertelli:

ORCID: https://orcid.org/0000-0003-0550-8981

Role: Data curationRole: InvestigationRole: ResourcesRole: Writing - review & editing

Gilbert Greub:

ORCID: https://orcid.org/0000-0001-9529-3317

Role: Data curationRole: Formal analysisRole: InvestigationRole: Project administrationRole: ResourcesRole: ValidationRole: Writing - review & editing

Karoline Leuzinger:

ORCID: https://orcid.org/0000-0002-5654-9356

Role: Data curationRole: Formal analysisRole: InvestigationRole: ResourcesRole: ValidationRole: Writing - review & editing

Madlen Stange:

ORCID: https://orcid.org/0000-0002-4559-2535

Role: Investigation

Alfredo Mari:

ORCID: https://orcid.org/0000-0002-3871-088X

Role: Formal analysisRole: SoftwareRole: Validation

Tim Roloff:

ORCID: https://orcid.org/0000-0003-3435-4723

Role: InvestigationRole: Resources

Helena Seth-Smith: Role: Data curationRole: MethodologyRole: ResourcesRole: ValidationRole: Writing - review & editing

Hans H. Hirsch: Role: ConceptualizationRole: ResourcesRole: Writing - original draftRole: Writing - review & editing

Adrian Egli:

ORCID: https://orcid.org/0000-0002-3564-8603

Role: Data curationRole: Resources

Maurice Redondo: Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: Validation

Olivier Kobel: Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: Software

Christoph Noppen:

ORCID: https://orcid.org/0000-0001-8953-3417

Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Resources

Louis du Plessis:

ORCID: https://orcid.org/0000-0003-0352-6289

Role: MethodologyRole: Writing - review & editing

Niko Beerenwinkel:

ORCID: https://orcid.org/0000-0002-0573-6119

Role: Formal analysisRole: InvestigationRole: SupervisionRole: Writing - review & editing

Richard A. Neher:

ORCID: https://orcid.org/0000-0003-2525-1407

Role: Conceptualization

Christian Beisel:

ORCID: https://orcid.org/0000-0001-5360-2193

Role: Data curationRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: Writing - review & editing

Tanja Stadler:

ORCID: https://orcid.org/0000-0001-6431-535X

Role: ConceptualizationRole: Data curationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing - original draftRole: Writing - review & editing

Journal

Journal ID (nlm-ta): Sci Transl Med

Journal ID (iso-abbrev): Sci Transl Med

Journal ID (publisher-id): stm

Journal ID (hwp): scitranslmed

Title: Science Translational Medicine

Publisher: American Association for the Advancement of Science

ISSN (Print): 1946-6234

ISSN (Electronic): 1946-6242

Publication date (Electronic, pub): 08 November 2022

Publication date PMC-release: 08 November 2022

Volume: 14

Electronic Location Identifier: eabn7979

Affiliations

[ ¹ ]Department of Biosystems Science and Engineering, ETH Zurich; 4058, Basel, Switzerland.

[ ² ]SIB Swiss Institute of Bioinformatics; 1015, Lausanne, Switzerland.

[ ³ ]Viollier AG; 4123, Allschwil, Switzerland.

[ ⁴ ]Institute for Social and Preventive Medicine, University of Bern; 3012, Bern, Switzerland.

[ ⁵ ]Department of Biology, ETH Zurich; 8092, Zurich, Switzerland.

[ ⁶ ]Department of Dermatology, University Hospital Zurich, University of Zurich; 8091, Zurich, Switzerland.

[ ⁷ ]Institute of Medical Virology, University of Zurich; 8057, Zurich, Switzerland.

[ ⁸ ]Laboratory of Virology, Department of Diagnostics, Geneva University Hospitals & Faculty of Medicine; 1205, Geneva, Switzerland.

[ ⁹ ]Swiss National Reference Centre for Influenza, University Hospitals of Geneva; 1205, Geneva, Switzerland.

[ ¹⁰ ]Institute of Microbiology, University Hospital Centre and University of Lausanne; 1011, Lausanne, Switzerland.

[ ¹¹ ]Division of Clinical Virology, University Hospital Basel; 4051, Basel, Switzerland.

[ ¹² ]Department of Biomedicine, University of Basel; 4031, Basel, Switzerland.

[ ¹³ ]Division of Clinical Bacteriology and Mycology, University Hospital Basel; 4031, Basel, Switzerland.

[ ¹⁴ ]Biozentrum, University of Basel; 4056, Basel, Switzerland.

Author notes

[* ]Corresponding author. Email: tanja.stadler@ 123456bsse.ethz.ch (T.S.); sarah.nadeau@ 123456bsse.ethz.ch (S.A.N.)

Author information

Christiane Beckmann https://orcid.org/0000-0001-9030-083X

Ivan Topolsky https://orcid.org/0000-0002-7561-0810

Chaoran Chen https://orcid.org/0000-0002-8763-2937

Emma Hodcroft https://orcid.org/0000-0002-0078-2212

Pedro Ferreira https://orcid.org/0000-0003-0559-6125

Kim Philipp Jablonski https://orcid.org/0000-0002-4166-4343

Susana Posada-Céspedes https://orcid.org/0000-0002-7459-8186

Sophie Seidel https://orcid.org/0000-0002-4484-9888

Noemi Santamaria de Souza https://orcid.org/0000-0001-7134-7480

Julia M. Martinez-Gomez https://orcid.org/0000-0002-5684-3707

Phil Cheng https://orcid.org/0000-0003-2940-006X

Philipp P. Bosshard https://orcid.org/0000-0002-1154-2281

Mitchell P. Levesque https://orcid.org/0000-0001-5902-9420

Verena Kufner https://orcid.org/0000-0003-4233-5952

Stefan Schmutz https://orcid.org/0000-0002-1955-7007

Maryam Zaheri https://orcid.org/0000-0003-2777-835X

Michael Huber https://orcid.org/0000-0002-0384-0000

Alexandra Trkola https://orcid.org/0000-0003-1013-876X

Samuel Cordey https://orcid.org/0000-0002-2684-5680

Florian Laubscher https://orcid.org/0000-0002-8803-981X

Ana Rita Gonçalves https://orcid.org/0000-0002-7893-0158

Sébastien Aeby https://orcid.org/0000-0001-9726-7438

Trestan Pillonel https://orcid.org/0000-0002-5725-7929

Claire Bertelli https://orcid.org/0000-0003-0550-8981

Gilbert Greub https://orcid.org/0000-0001-9529-3317

Karoline Leuzinger https://orcid.org/0000-0002-5654-9356

Madlen Stange https://orcid.org/0000-0002-4559-2535

Alfredo Mari https://orcid.org/0000-0002-3871-088X

Tim Roloff https://orcid.org/0000-0003-3435-4723

Adrian Egli https://orcid.org/0000-0002-3564-8603

Christoph Noppen https://orcid.org/0000-0001-8953-3417

Louis du Plessis https://orcid.org/0000-0003-0352-6289

Niko Beerenwinkel https://orcid.org/0000-0002-0573-6119

Richard A. Neher https://orcid.org/0000-0003-2525-1407

Christian Beisel https://orcid.org/0000-0001-5360-2193

Tanja Stadler https://orcid.org/0000-0001-6431-535X

Article

Publisher ID: abn7979

DOI: 10.1126/scitranslmed.abn7979

PMC ID: 9765449

PubMed ID: 36346321

SO-VID: 0a6bb447-ad70-4b62-9bd7-472462945556

Copyright © Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 20 December 2021

Date accepted : 31 October 2022

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100001711, Swiss National Science Foundation;

Award ID: 31CA30_196267

Funded by: ETH Zurich;

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Swiss public health measures associated with reduced SARS-CoV-2 transmission using genome data

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Novel Coronavirus Disease COVID-19

Most cited references 36

Fast and accurate short read alignment with Burrows–Wheeler transform

IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

A new coronavirus associated with human respiratory disease in China

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