An infectious way to teach students about outbreaks

•An updated epidemiological teaching exercise was developed.•Students participate in an outbreak that they subsequently analyse.•Data from five years of consecutive student cohorts is presented.•An R package and practical are developed that improve the pedagogical experience. The study of infectious...

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Bibliographic Details
Published in:Epidemics 2018-06, Vol.23, p.42-48
Main Authors: Cremin, Íde, Watson, Oliver, Heffernan, Alastair, Imai, Natsuko, Ahmed, Norin, Bivegete, Sandra, Kimani, Teresia, Kyriacou, Demetris, Mahadevan, Preveina, Mustafa, Rima, Pagoni, Panagiota, Sophiea, Marisa, Whittaker, Charlie, Beacroft, Leo, Riley, Steven, Fisher, Matthew C.
Format: Article
Language:English
Subjects:
Computer Simulation
Disease Outbreaks - statistics & numerical data
Epidemiology - education
Humans
Models, Theoretical
Network reconstruction
Outbreak analysis
Pedagogical tool
Simulation analysis
Students
Teaching
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Summary:•An updated epidemiological teaching exercise was developed.•Students participate in an outbreak that they subsequently analyse.•Data from five years of consecutive student cohorts is presented.•An R package and practical are developed that improve the pedagogical experience. The study of infectious disease outbreaks is required to train today’s epidemiologists. A typical way to introduce and explain key epidemiological concepts is through the analysis of a historical outbreak. There are, however, few training options that explicitly utilise real-time simulated stochastic outbreaks where the participants themselves comprise the dataset they subsequently analyse. In this paper, we present a teaching exercise in which an infectious disease outbreak is simulated over a five-day period and subsequently analysed. We iteratively developed the teaching exercise to offer additional insight into analysing an outbreak. An R package for visualisation, analysis and simulation of the outbreak data was developed to accompany the practical to reinforce learning outcomes. Computer simulations of the outbreak revealed deviations from observed dynamics, highlighting how simplifying assumptions conventionally made in mathematical models often differ from reality. Here we provide a pedagogical tool for others to use and adapt in their own settings.
ISSN:1755-4365
1878-0067
DOI:10.1016/j.epidem.2017.12.002