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Equations of the End: Teaching Mathematical Modeling Using the Zombie Apocalypse

    Authors: Eric T. Lofgren1,*, Kristy M. Collins2, Tara C. Smith3, Reed A. Cartwright4
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    Affiliations: 1: Network Dynamics and Simulation Science Laboratory, Biocomplexity Institute of Virginia Tech, Virginia Tech, Blacksburg, VA 24061; 2: Biocomplexity Institute of Virginia Tech, Virginia Tech, Blacksburg, VA 24061; 3: College of Public Health, Kent State University, Kent, OH 44242; 4: School of Life Sciences and the Biodesign Institute, Arizona State University, Tempe, AZ 85287
    AUTHOR AND ARTICLE INFORMATION AUTHOR AND ARTICLE INFORMATION
    • Published 01 March 2016
    • ©2016 Author(s). Published by the American Society for Microbiology.
    • [open-access] This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial-NoDerivatives 4.0 International license (https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode), which grants the public the nonexclusive right to copy, distribute, or display the published work.

    • Supplemental materials available at http://jmbe.asm.org
    • *Corresponding author. Mailing address: Paul G. Allen School for Global Animal Health, 240 SE Ott Road, Room 311, Washington State University, Pullman, WA 99164. Phone: 303-912-2595. Fax: 509-335-6328. E-mail: Eric.Lofgren@gmail.com.
    Source: J. Microbiol. Biol. Educ. March 2016 vol. 17 no. 1 137-142. doi:10.1128/jmbe.v17i1.1066
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    Abstract:

    Mathematical models of infectious diseases are a valuable tool in understanding the mechanisms and patterns of disease transmission. It is, however, a difficult subject to teach, requiring both mathematical expertise and extensive subject-matter knowledge of a variety of disease systems. In this article, we explore several uses of zombie epidemics to make mathematical modeling and infectious disease epidemiology more accessible to public health professionals, students, and the general public. We further introduce a web-based simulation, White Zed (http://cartwrig.ht/apps/whitezed/), that can be deployed in classrooms to allow students to explore models before implementing them. In our experience, zombie epidemics are familiar, approachable, flexible, and an ideal way to introduce basic concepts of infectious disease epidemiology.

Key Concept Ranking

Infectious Diseases
0.8057098
Animal Reservoir
0.5665815
Asymptomatic Carriers
0.53125
Incubation Period
0.45406482
Herd Immunity
0.41501346
0.8057098

References & Citations

1. Anderson PWS2002Resident EvilConstantin Film
2. Boyle D200228 Days LaterFox Searchlight Pictures
3. Brooks M2006World War ZCrownNew York
4. Chowell D, Castillo-Chavez C, Krishna S, Qui X, Anderson KS2015Modelling the effect of early detection of EbolaLancet Infect Dis15214814910.1016/S1473-3099(14)71084-925749063 http://dx.doi.org/10.1016/S1473-3099(14)71084-9
5. Cummings P2012The neuropathology of ZombiesSinister PressHarrisonville, MO
6. DiLouie C2011The InfectionPermuted PressFranklin, TN
7. Eisner B2010The CraziesOverture Films
8. Fleischer R2009ZombielandColumbia Pictures
9. Halloran ME, et al2008Modeling targeted layered containment of an influenza pandemic in the United StatesPNAS1054639464410.1073/pnas.0706849105183324362290797 http://dx.doi.org/10.1073/pnas.0706849105
10. Halperin V, Halperin E1932White ZombieUnited Artists
11. Hughes DP Andersen SB, Hywel-Jones NL, Himaman W, Bilen J, Boomsma JJ2011Behavioral mechanisms and morphological symptoms of zombie ants dying from fungal infectionBMC Ecol111310.1186/1472-6785-11-13215546703118224 http://dx.doi.org/10.1186/1472-6785-11-13
12. Kirkman R, et al2010The Walking DeadAnchor Bay EntertainmentBeverly Hills, CA
13. Lavine JS, King AA, Bjørnstad ON2011Natural immune boosting in pertussis dynamics and the potential for long-term vaccine failurePNAS1087259726410.1073/pnas.1014394108214222813084147 http://dx.doi.org/10.1073/pnas.1014394108
14. Lloyd AL2009Sensitivity of model-based epidemiological parameter estimation to model assumptions123141 Chowell G, Hyman JM, Betterncourt LMA, Castillo-Chavez CMathematical and statistical estimation approaches in epidemiologySpringerDordrecht, Germany10.1007/978-90-481-2313-1_6 http://dx.doi.org/10.1007/978-90-481-2313-1_6
15. Lofgren ET, et al2014Opinion: mathematical models: a key tool for outbreak responsePNAS111180951809610.1073/pnas.1421551111255025944280577 http://dx.doi.org/10.1073/pnas.1421551111
16. McCallum H, Barlow N, Hone J2001How should pathogen transmission be modeled?Trends Ecol Evol1629530010.1016/S0169-5347(01)02144-911369107 http://dx.doi.org/10.1016/S0169-5347(01)02144-9
17. Medlock J, Galvani A2009Optimizing influenza vaccine distributionScience3251705170810.1126/science.117557019696313 http://dx.doi.org/10.1126/science.1175570
18. Pauls C, Solomon M2012Deck ZChronicle BooksSan Francisco, CA
19. Press WH, Flannery BP, Teukolsky SA, Vetterling WT2007Numerical recipes: the art of scientific computing3rd edCambridge University PressCambridge
20. Rivers CM, Lofgren ET, Marathe M, Eubank S, Lewis BL2014Modeling the impact of interventions on an epidemic of Ebola in Sierra Leone and LiberiaPLoS Curr6259148594399521
21. Romero G1968Night of the Living DeadThe Walter Reade Organization
22. Smith TC2015Zombie infections: epidemiology, treatment and preventionBMJ351h642310.1136/bmj.h6423 http://dx.doi.org/10.1136/bmj.h6423
23. Snyder Z2004Dawn of the DeadUniversal Pictures
24. Straley B, Druckmann N2013The Last of UsNaughty Dog
25. Yuen W2012The Walking Dead and Philosophy: Zombie Apocalypse NowOpen Court PublishingChicago
26. Zhao J, Eisenberg JE, Spicknall IH, Li S, Koopman JS2012Model analysis of fomite mediated influenza transmissionPLoS One7e5198410.1371/journal.pone.0051984 http://dx.doi.org/10.1371/journal.pone.0051984
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/content/journal/jmbe/10.1128/jmbe.v17i1.1066
2016-03-01
2017-06-25

Abstract:

Mathematical models of infectious diseases are a valuable tool in understanding the mechanisms and patterns of disease transmission. It is, however, a difficult subject to teach, requiring both mathematical expertise and extensive subject-matter knowledge of a variety of disease systems. In this article, we explore several uses of zombie epidemics to make mathematical modeling and infectious disease epidemiology more accessible to public health professionals, students, and the general public. We further introduce a web-based simulation, White Zed (http://cartwrig.ht/apps/whitezed/), that can be deployed in classrooms to allow students to explore models before implementing them. In our experience, zombie epidemics are familiar, approachable, flexible, and an ideal way to introduce basic concepts of infectious disease epidemiology.

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Figures

Image of FIGURE 1

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FIGURE 1

Schematic representation of two models used during one-day modeling workshop. Panel A depicts a simple “SZR” model, wherein the population is divided into three compartments: Susceptible (S), Zombies (Z), and Removed (R). Panel B depicts a more complex model, adding compartments for individuals who have been infected but not yet turned into zombies (E), susceptible individuals who have found shelter (H), and zombies who were killed during interactions with susceptible individuals (K).

Source: J. Microbiol. Biol. Educ. March 2016 vol. 17 no. 1 137-142. doi:10.1128/jmbe.v17i1.1066
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Image of FIGURE 2

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FIGURE 2

Screenshot of the White Zed simulation website. The graph displays population dynamics of a zombie apocalypse. The left control panel allows users to specify the population makeup at the beginning of the simulation, while the right control panel allows users to specify the infection parameters of the disease.

Source: J. Microbiol. Biol. Educ. March 2016 vol. 17 no. 1 137-142. doi:10.1128/jmbe.v17i1.1066
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