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How to make epidemiological training infectious

Steve E Bellan, Juliet RC Pulliam, James C Scott, Jonathan Dushoff, the MMED Organizing Committee and Wim Delva UGent (2012) PLOS BIOLOGY. 10(4).
abstract
Modern infectious disease epidemiology builds on two independently developed fields: classical epidemiology and dynamical epidemiology. Over the past decade, integration of the two fields has increased in research practice, but training options within the fields remain distinct with few opportunities for integration in the classroom. The annual Clinic on the Meaningful Modeling of Epidemiological Data (MMED) at the African Institute for Mathematical Sciences has begun to address this gap. MMED offers participants exposure to a broad range of concepts and techniques from both epidemiological traditions. During MMED 2010 we developed a pedagogical approach that bridges the traditional distinction between classical and dynamical epidemiology and can be used at multiple educational levels, from high school to graduate level courses. The approach is hands-on, consisting of a real-time simulation of a stochastic outbreak in course participants, including realistic data reporting, followed by a variety of mathematical and statistical analyses, stemming from both epidemiological traditions. During the exercise, dynamical epidemiologists developed empirical skills such as study design and learned concepts of bias while classical epidemiologists were trained in systems thinking and began to understand epidemics as dynamic nonlinear processes. We believe this type of integrated educational tool will prove extremely valuable in the training of future infectious disease epidemiologists. We also believe that such interdisciplinary training will be critical for local capacity building in analytical epidemiology as Africa continues to produce new cohorts of well-trained mathematicians, statisticians, and scientists. And because the lessons draw on skills and concepts from many fields in biology-from pathogen biology, evolutionary dynamics of host-pathogen interactions, and the ecology of infectious disease to bioinformatics, computational biology, and statistics-this exercise can be incorporated into a broad array of life sciences courses.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
DISEASE, ELIMINATION, TRACHOMA, DYNAMICS, BLACK-BOX, ECO-EPIDEMIOLOGY, MODELS
journal title
PLOS BIOLOGY
PLoS. Biol.
volume
10
issue
4
article_number
e1001295
pages
8 pages
Web of Science type
Article
Web of Science id
000303541800001
ISSN
1544-9173
DOI
10.1371/journal.pbio.1001295
language
English
UGent publication?
no
classification
A1
copyright statement
I have retained and own the full copyright for this publication
id
3002949
handle
http://hdl.handle.net/1854/LU-3002949
date created
2012-10-01 11:07:22
date last changed
2013-07-19 13:51:49
@article{3002949,
  abstract     = {Modern infectious disease epidemiology builds on two independently developed fields: classical epidemiology and dynamical epidemiology. Over the past decade, integration of the two fields has increased in research practice, but training options within the fields remain distinct with few opportunities for integration in the classroom. The annual Clinic on the Meaningful Modeling of Epidemiological Data (MMED) at the African Institute for Mathematical Sciences has begun to address this gap. MMED offers participants exposure to a broad range of concepts and techniques from both epidemiological traditions. During MMED 2010 we developed a pedagogical approach that bridges the traditional distinction between classical and dynamical epidemiology and can be used at multiple educational levels, from high school to graduate level courses. The approach is hands-on, consisting of a real-time simulation of a stochastic outbreak in course participants, including realistic data reporting, followed by a variety of mathematical and statistical analyses, stemming from both epidemiological traditions. During the exercise, dynamical epidemiologists developed empirical skills such as study design and learned concepts of bias while classical epidemiologists were trained in systems thinking and began to understand epidemics as dynamic nonlinear processes. We believe this type of integrated educational tool will prove extremely valuable in the training of future infectious disease epidemiologists. We also believe that such interdisciplinary training will be critical for local capacity building in analytical epidemiology as Africa continues to produce new cohorts of well-trained mathematicians, statisticians, and scientists. And because the lessons draw on skills and concepts from many fields in biology-from pathogen biology, evolutionary dynamics of host-pathogen interactions, and the ecology of infectious disease to bioinformatics, computational biology, and statistics-this exercise can be incorporated into a broad array of life sciences courses.},
  articleno    = {e1001295},
  author       = {Bellan, Steve E and Pulliam, Juliet RC and Scott, James C and Dushoff, Jonathan and MMED Organizing Committee, the and Delva, Wim},
  issn         = {1544-9173},
  journal      = {PLOS BIOLOGY},
  keyword      = {DISEASE,ELIMINATION,TRACHOMA,DYNAMICS,BLACK-BOX,ECO-EPIDEMIOLOGY,MODELS},
  language     = {eng},
  number       = {4},
  pages        = {8},
  title        = {How to make epidemiological training infectious},
  url          = {http://dx.doi.org/10.1371/journal.pbio.1001295},
  volume       = {10},
  year         = {2012},
}

Chicago
Bellan, Steve E, Juliet RC Pulliam, James C Scott, Jonathan Dushoff, the MMED Organizing Committee, and Wim Delva. 2012. “How to Make Epidemiological Training Infectious.” Plos Biology 10 (4).
APA
Bellan, S. E., Pulliam, J. R., Scott, J. C., Dushoff, J., MMED Organizing Committee, the, & Delva, W. (2012). How to make epidemiological training infectious. PLOS BIOLOGY, 10(4).
Vancouver
1.
Bellan SE, Pulliam JR, Scott JC, Dushoff J, MMED Organizing Committee the, Delva W. How to make epidemiological training infectious. PLOS BIOLOGY. 2012;10(4).
MLA
Bellan, Steve E, Juliet RC Pulliam, James C Scott, et al. “How to Make Epidemiological Training Infectious.” PLOS BIOLOGY 10.4 (2012): n. pag. Print.