11/04/12

Game approach to improve outbreak modelling skills

Not everyone who becomes ill during an outbreak reports to a clinic, say the game's developers Copyright: Flickr/Gates Foundation

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<h1>Game approach to improve outbreak modelling skills</h1>
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<p><span>A game aimed at teaching mathematicians and epidemiologists to understand and handle complex data generated by </span><a href="http://www.scidev.net/en/health/">disease</a><span> outbreaks has been developed by US researchers, according to a story in <em>Science NOW.</em></span></p>
<p><em>Muizenberg Mathematical Fever</em><span> (MMF) was designed by Steve Bellan, an ecologist at the University of California, Berkeley, and Juliet Pulliam, from the University of Florida, and tested at a </span><a href="http://www.scidev.net/en/science-and-innovation-policy/capacity-building/">workshop</a><span> on epidemiology modelling in South Africa that the pair runs each year.</span></p>
<p><span>Their game aims to encourage students to consider such questions as how to include data on patients who hide their infections during an outbreak, as well as those who report to clinics, and also to look critically at how patients are chosen for inclusion in outbreak studies.</span></p>
<p><span>The game simulates a disease outbreak. In it, participants are given a piece of paper telling them that they are "infected", with instructions on how to ‘propagate’ the disease. All are told to inform their instructors of their infection status – but only some are told to ‘visit a clinic’ to report their infection. </span></p>
<p><span>This results in two data sets. One, which would never exist in real life, according to the developers, provides an overview of all infections, while the other – which is more realistic – is the number of cases that are reported to authorities. </span></p>
<p><span>"When you have a real outbreak, you need to rely on whatever data you can get," Bellan told <em>Science NOW</em>. "And our exercise helps show the difference between that data and the reality of the outbreak."</span></p>
<p><span>Once the simulation has run its course, the developers work with epidemiologists to make predictions, based on the number of cases reported to authorities about the possible spread, severity and longevity of the outbreak. These predictions are then compared against the "real" total disease burden.</span></p>
<p><span>Feedback from workshops "has been very positive," Bellan said, adding that instructors who took part in the most recent workshop are </span><a href="http://www.scidev.net/en/science-and-innovation-policy/technology-transfer/"><span>taking the game back to their home institutions</span></a> to test it out in classroom settings.</p>
<p><span>Gavin Hitchcock, a specialist at the South African Centre for Epidemiological Modelling and Analysis in Stellenbosch, South Africa, who was not involved in developing the MMF program, praised the game simulation approach, saying it "brilliantly exemplifies how this integration may be achieved in a practical, hands-on, memorable way" for students from high school to graduate level.</span></p>
<p><span>MMF’s developers now plan to create different versions of the game to study other aspects of epidemiology, such as diseases spread by a range of vectors, and outbreaks caused by different diseases which present with similar symptoms.</span></p>
<p><span><a href="http://news.sciencemag.org/sciencenow/2012/04/-outbreak-the-game.html">Link to story in <em>Science NOW</em></a></span></p>
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A game aimed at teaching mathematicians and epidemiologists to understand and handle complex data generated by disease outbreaks has been developed by US researchers, according to a story in Science NOW.

Muizenberg Mathematical Fever (MMF) was designed by Steve Bellan, an ecologist at the University of California, Berkeley, and Juliet Pulliam, from the University of Florida, and tested at a workshop on epidemiology modelling in South Africa that the pair runs each year.

Their game aims to encourage students to consider such questions as how to include data on patients who hide their infections during an outbreak, as well as those who report to clinics, and also to look critically at how patients are chosen for inclusion in outbreak studies.

The game simulates a disease outbreak. In it, participants are given a piece of paper telling them that they are "infected", with instructions on how to ‘propagate’ the disease. All are told to inform their instructors of their infection status – but only some are told to ‘visit a clinic’ to report their infection.

This results in two data sets. One, which would never exist in real life, according to the developers, provides an overview of all infections, while the other – which is more realistic – is the number of cases that are reported to authorities.

"When you have a real outbreak, you need to rely on whatever data you can get," Bellan told Science NOW. "And our exercise helps show the difference between that data and the reality of the outbreak."

Once the simulation has run its course, the developers work with epidemiologists to make predictions, based on the number of cases reported to authorities about the possible spread, severity and longevity of the outbreak. These predictions are then compared against the "real" total disease burden.

Feedback from workshops "has been very positive," Bellan said, adding that instructors who took part in the most recent workshop are taking the game back to their home institutions to test it out in classroom settings.

Gavin Hitchcock, a specialist at the South African Centre for Epidemiological Modelling and Analysis in Stellenbosch, South Africa, who was not involved in developing the MMF program, praised the game simulation approach, saying it "brilliantly exemplifies how this integration may be achieved in a practical, hands-on, memorable way" for students from high school to graduate level.

MMF’s developers now plan to create different versions of the game to study other aspects of epidemiology, such as diseases spread by a range of vectors, and outbreaks caused by different diseases which present with similar symptoms.

Link to story in Science NOW