In recent years, data and statistics have become a feature of emerging public health situations to an extent that is historically unprecedented. Scientists, policy makers and the public have had to become confident consumers of numbers and model predictions. The actors involved in the management of infectious diseases are not necessarily modelling specialists themselves, but nevertheless need to interpret statistical and modelling results and be aware of their limitations.
This module will train students to understand what can and cannot be learnt from data and modelling results. The module does not assume that students are experts in statistics or modelling. Students will receive training in how to use simple visualisations and analysis to gain a robust understanding of key patterns in data, and how to recognise common pitfalls in data interpretation. Students will learn the distinction between different approaches in statistics and quantitative modelling, and when it is appropriate to use them. Particular attention will be paid to the management of uncertainty in model predictions. The module will equip students to interpret critically the quantitative results in scientific papers and reports, and how to use them to inform the management of infectious diseases. The module will be assessed by the combination of a presentation and a short report, in the spirit of authentic assessment.