An infectious way to teach students about outbreaks
| Autor: | 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. |
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| Přispěvatelé: | Medical Research Council (MRC), National Institute for Health Research, Wellcome Trust |
| Rok vydání: | 2017 |
| Předmět: |
Computer science
Epidemiology education Microbiology Article lcsh:Infectious and parasitic diseases Disease Outbreaks 03 medical and health sciences 0302 clinical medicine Pedagogical tool Virology Humans lcsh:RC109-216 Computer Simulation 030212 general & internal medicine Students Network reconstruction 4. Education Teaching 05 social sciences Public Health Environmental and Occupational Health 050301 education Outbreak 1103 Clinical Sciences Models Theoretical Data science 3. Good health R package Simulation analysis Infectious Diseases 1117 Public Health And Health Services Infectious disease (medical specialty) Parasitology 0503 education Outbreak analysis |
| Zdroj: | Epidemics Epidemics, Vol 23, Iss, Pp 42-48 (2018) |
| Popis: | Highlights • 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. |
| Databáze: | OpenAIRE |
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