Pandemic Data Science


Data science has played a prominent and significant role in response to the COVID-19 pandemic. Mathematical modellers and data scientists joined virologists, public health professional and policy makers to confront the pandemic using methods that did not exist for previous generations. In recent years, the value of big-data has become increasingly appreciated across all sectors of industry, academia and society. The COVID-19 pandemic revealed to the wider world - that in the modern era - data is an exceedingly valuable commodity. Data-driven insights during the COVID-19 pandemic have played critical roles in understanding and responding to the pandemic. Moreover, data science will continue to be important beyond this pandemic in our preparedness for any future disease outbreaks. 

This course aims to introduce students to the analytical approaches, successes and challenges experienced by the data science and artificial intelligence community during the COVID-19 pandemic. Students will gain experience of how data science has impacted key decisions and policy in response to the pandemic, from epidemiological modelling through to vaccination strategies.   

Programme details

Courses starts: 18 Apr 2024

Week 0: Course Orientation

Week 1: Pandemic preparedness and identification of “disease X”

Week 2: Mathematical modelling and prediction of infectious disease epidemiology

Week 3: Genetic and non-genetic COVID-19 risk factor identification

Week 4: COVID-19 therapeutic clinical trials

Week 5: Vaccine platform technologies and COVID-19 vaccine design

Week 6: COVID-19 vaccine efficacy studies

Week 7: Viral sequencing and variants of concern identification

Week 8: Biomarker identification in infectious diseases

Week 9: Systems immunology and systems vaccinology

Week 10: Artificial intelligence and data science in the context of COVID-19

Digital Certification

To complete the course and receive a certificate, you will be required to attend and participate in at least 80% of the live sessions on the course and pass your final assignment. Upon successful completion, you will receive a link to download a University of Oxford digital certificate. Information on how to access this digital certificate will be emailed to you after the end of the course. The certificate will show your name, the course title and the dates of the course you attended. You will be able to download your certificate or share it on social media if you choose to do so.


Description Costs
Course Fee £280.00
Take this course for CATS points £10.00


If you are in receipt of a UK state benefit, you are a full-time student in the UK or a student on a low income, you may be eligible for a reduction of 50% of tuition fees. Please see the below link for full details:

Concessionary fees for short courses


Prof Daniel O'Connor

Daniel is an Associate Professor within the Oxford Vaccine Group, University of Oxford. Daniel's research interests relate to the analysis of contemporary, high-dimensional datasets (e.g., genomic, transcriptomic, proteomic) to elucidate the molecular determinants of immune responses to vaccines and infectious diseases.

Course aims

  • Basic understanding of current pandemic preparedness strategies.
  • Familiarity with data science, machine learning & artificial intelligence.
  • Insights into the use of data science in infectious disease and vaccine research.

Teaching methods

This course will consist of a weekly, one-hour pre-recorded lecture (including invited expert guest speakers) to be viewed by students in preparation for the once weekly tutor-led live session at the time advertised. The live session will provide us with the opportunity to discuss some of the key theoretical concepts involved in pandemic data science.

Learning outcomes

By the end of the course students will be expected to:

  • have basic understanding of how data science has impacted the response to the COVID-19 pandemic;
  • to have basic understanding of how data science will inform preparedness strategies for any future pandemics.

Assessment methods

The students will need to complete a written assessment.

Students must submit a completed Declaration of Authorship form at the end of term when submitting your final piece of work. CATS points cannot be awarded without the aforementioned form - Declaration of Authorship form


We will close for enrolments 7 days prior to the start date to allow us to complete the course set up. We will email you at that time (7 days before the course begins) with further information and joining instructions. As always, students will want to check spam and junk folders during this period to ensure that these emails are received.

To earn credit (CATS points) for your course you will need to register and pay an additional £10 fee per course. You can do this by ticking the relevant box at the bottom of the enrolment form or when enrolling online.

Please use the 'Book' or 'Apply' button on this page. Alternatively, please complete an enrolment form (Word) or enrolment form (Pdf).

Level and demands

The course will provide a broad and accessible content. However, an in-depth understanding of the concepts provided would require further learning.  

Students who register for CATS points will receive a Record of CATS points on successful completion of their course assessment.

To earn credit (CATS points) you will need to register and pay an additional £10 fee per course. You can do this by ticking the relevant box at the bottom of the enrolment form or when enrolling online.

Coursework is an integral part of all weekly classes and everyone enrolled will be expected to do coursework in order to benefit fully from the course. Only those who have registered for credit will be awarded CATS points for completing work at the required standard.

Students who do not register for CATS points during the enrolment process can either register for CATS points prior to the start of their course or retrospectively from the January 1st after the current full academic year has been completed. If you are enrolled on the Certificate of Higher Education you need to indicate this on the enrolment form but there is no additional registration fee.

Most of the Department's weekly classes have 10 or 20 CATS points assigned to them. 10 CATS points at FHEQ Level 4 usually consist of ten 2-hour sessions. 20 CATS points at FHEQ Level 4 usually consist of twenty 2-hour sessions. It is expected that, for every 2 hours of tuition you are given, you will engage in eight hours of private study.

Credit Accumulation and Transfer Scheme (CATS)