| Autor: |
Íde Cremin, Oliver Watson, Alastair Heffernan, Natsuko Imai, Norin Ahmed, Sandra Bivegete, Teresia Kimani, Demetris Kyriacou, Preveina Mahadevan, Rima Mustafa, Panagiota Pagoni, Marisa Sophiea, Charlie Whittaker, Leo Beacroft, Steven Riley, Matthew C. Fisher |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
Epidemics, Vol 23, Iss , Pp 42-48 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
1755-4365 |
| DOI: |
10.1016/j.epidem.2017.12.002 |
| Popis: |
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. Keywords: Teaching, Outbreak analysis, Pedagogical tool, Simulation analysis, Network reconstruction |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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