Sampling and testing are key to understanding where a disease is spreading. In the COVID-19 pandemic, the number of samples taken, analysed, tracked and shared have far surpassed any previous pandemic. This course follows the journey of a sample from the swab to the processed data used by experts in pandemic response. It discusses how to share data across teams and internationally, and the ethical and practical implications of using mass data on a pandemic scale.
Learning outcomes
- Outline the journey from sample collection, through PCR to sequencing and data linkage
- Compare the different sample types and how sampling strategy affects test performance
- Explain the importance of linking genomic data to clinical and epidemiological data sets to address public health and scientific questions
- Identify and explore ethical, legal and social implications of data use and sharing
Target audience
This course is for researchers, healthcare and public health professionals, diagnostic professionals, or any person involved in testing and analysis of disease samples.
Week 1 - The journey of a sample
- Glossary
- The testing pathway
- Comparing different types of testing
- PCR testing in the COVID-19 pandemic
- Sample types for testing
- Walkthrough of the sequencing process
- How to avoid the pitfalls and get trustable results?
- Understanding the different sources of samples for testing
- Importance of taking an appropriate sample
- The role of quality management
- High-throughput testing during pandemic response
- Scaling up: implementation and how to overcome limitations
Week 2 - How to make data richer
- How different countries tackled the pandemic: an example
- Introduction to biobanking
- Walking through a biobank
- What is metadata?
- Types of metadata
- Data collection tools
- Public databases benefit epidemiology
- Ensuring sample/data consent and ownership
- Data enrichment benefits to epidemiology
- Benefits and challenges of integrating clinical data
- Practical challenges: setting up a laboratory during lockdown
- De-centralising genomic surveillance
Week 3 - A sample without data is nothing
- Lessons learnt: how to be prepared for the next pandemic
- Data sharing in “peace” and “war” time
- Stakeholders for data sharing and the importance to share
- Opportunities for global collaboration in pathogen genomics
- Challenges and limitations of data sharing
- Data sharing best practices
- The FAIR principles
- How do FAIR principles apply in a public health emergency
- No database is perfect: beware of errors in sequence databases
- How to establish fruitful and fair collaboration: an example
- How to promote data sharing
- Importance of implementing local capacity
- Resources
Educators
Ana Filipe, MRC-University of Glasgow Centre for Virus Research, United Kingdom
Leigh Jackson, University of Exeter, United Kingdom
Moses Luutu Nsubuga, Makerere University, Uganda
Rogers Kamulegeya, Makerere University, Uganda
Contributors
Angela Beckett, University of Portsmouth, United Kingdom
Camila Romano, Universidade de São Paulo, Brazil
Collins Otieno, African Society for Laboratory Medicine, Ethiopia
Dodge Lim, Research Institute for Tropical Medicine, Philippines
Emma Thomson, MRC-University of Glasgow Centre for Virus Research, United Kingdom
Emmanuel Nasinghe, Makerere University, Uganda
Faith Nakazzi, Makerere University, Uganda
Gideon Nsubuga, Makerere University, Uganda
Hanna Pymont, United Kingdom Health Security Agency, United Kingdom
Harper VanSteenhouse, BioClavis Ltd, United States of America
Kirstyn Brunker, University of Glasgow, United Kingdom
Lei Lanna Dancel, Research Institute for Tropical Medicine, Philippines
Malebo Malope, Stellenbosch University, South Africa
Maria Magdalene Namaganda, Makerere University, Uganda
Ma. Ricci Gomez, Research Institute for Tropical Medicine, Philippines
Mark Webber, Quadram Institute, United Kingdom
Muhammad Yasir, Quadram Institute, United Kingdom
Nathan Moore, Hampshire Hospitals NHS Foundation Trust, United Kingdom
Newton Lwanga, Makerere University, Uganda
Paúl Cárdenas, Universidad San Francisco de Quito, Ecuador
Rodrigue Bikangui, Centre de Recherches Médicales de Lambaréné, Gabon
Sam Robson, University of Portsmouth, United Kingdom
Sarah Mwang, Africa CDC, Ethiopia
Senjuti Saha, Child Health Research Foundation, Bangladesh
Sharon Glaysher, University of Portsmouth, United Kingdom
Stephanie Hutchings, United Kingdom Health Security Agency, United Kingdom
Sunando Roy, University College of London, United Kingdom
Reviewers
Cassandra Soo, Wellcome Connecting Science, United Kingdom
Ricardo Khouri, Universidade Federal da Bahia and FIOCRUZ Bahia, Brazil
Education developer
Liã Bárbara Arruda, Wellcome Connecting Science, United Kingdom
COG-UK contributors
Sharon Peacock, University of Cambridge, United Kingdom
Alistair Darby, University of Liverpool, United Kingdom
Catherine Ludden, University of Cambridge, United Kingdom
Darren Smith, Northumbria University, United Kingdom
Ewan Harrison, Wellcome Sanger Institute, United Kingdom
Anna Markov, University of Cambridge, United Kingdom
Ellena Brooks, University of Cambridge, United Kingdom
Kim Smith, University of Cambridge, United Kingdom
Peter McEwan, University of Cambridge, United Kingdom
Wellcome Connecting Science contributors
Alice Matimba, Wellcome Connecting Science, United Kingdom
Dusanka Nikolic, Wellcome Connecting Science, United Kingdom
Jorge Batista da Rocha, Wellcome Connecting Science, United Kingdom
Mel Sharpe, Wellcome Connecting Science, United Kingdom
Rachel Berkson, Wellcome Connecting Science, United Kingdom
Treasa Creavin, Wellcome Connecting Science, United Kingdom
Original platform: FutureLearn
Original course page: Swab to server: testing, sequencing and sharing during a pandemic
Launch of the original version: 9 May 2022
Data collected on 31 May 2023
Number of joiners: 2,701
Number of countries reached: 139
Review score: 4.7/5 (49 reviews)
Any reuse of the course materials is encouraged with due acknowledgement.
This work is licensed under a Creative Commons Attribution 4.0 International License.
COG-Train. (2022). From Swab to Server: Testing, Sequencing and Sharing during a Pandemic. Zenodo. https://doi.org/10.5281/zenodo.8164995