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Overview
Essential aspects of the analysis of outbreak data will be covered, including fundamental principles of statistics, good coding practices, scientific reproducibility and report automation, estimation of key epidemiological delays, mortality and transmissibility, short term forecasting, and the analysis of genetic data to reconstruct transmission trees.
All teaching will be done online, and involve a mixture of lectures, group discussions, and hands-on practical sessions using the R software. Worked examples will be based on direct experience of outbreak responses, including the Ebola epidemic in Eastern Democratic Republic of the Congo (2018 - 2020), and the response to COVID-19 in the UK. Lectures will be recorded and made available online to participants.
Methods of assessment
Students will not be formally assessed. The course will be assessed using anonymous online forms, circulated.
Programme Structure
Day 1
- General introduction to the course
- Lecture: on the emergence of outbreak analytics and its role in outbreak response
- Group discussion: what are the key questions in early outbreak responses?
- Practical: setting up R, Rstudio, using the RECON deployer
- Lecture/practical: introduction to data handling and visualisation using dplyr and ggplot2
- Lecture: principles of reproducible data science
- Practical: reproducibility using R
Day 2
- Lecture: a primer on key statistical concepts for outbreak response
- Lecture: descriptive epidemiology; epidemic curves; estimating mortality; characterising delay distributions; analysing contact data
- Practical: simulated Ebola outbreak response – data handling and visualisation
Day 3
- Lecture: primer on infectious disease modelling; estimating transmissibility (reproduction numbers, growth rates, doubling time); short term forecasting
- Practical: simulated Ebola outbreak response - transmissibility and forecasting; real-life application to publicly available COVID-19 data
Day 4
- Lecture: primer on genetic data analysis for outbreak response
- Lecture: reconstructing transmission trees using epidemiological and genetic data
- Practical: simulated Ebola outbreak response – inferring who infected whom
Day 5
- Lecture: advanced tools for reproducible data science
- Practical: open data session, build-your-own automated reporting infrastructure
Key information
Duration
- Part-time
- 5 days
Start dates & application deadlines
- Starting
- Apply before
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Language
English
Delivered
Online
- Fully structured
Disciplines
Medicine Health Sciences Health Informatics View 29 other Short Courses in Health Informatics in United KingdomAcademic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
This course is open to field epidemiologists, public health practitioners, data managers, statisticians, computer scientists, data scientists, modellers with an interest in infectious disease outbreak response.
Tuition Fee
To always see correct tuition fees
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International
1250 GBP/fullTuition FeeBased on the tuition of 1250 GBP for the full programme during 5 days. -
National
1250 GBP/fullTuition FeeBased on the tuition of 1250 GBP for the full programme during 5 days.
Funding
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