Abstract
The spread of diseases remains an important issue in public health. The use of mathematics in predicting and understanding epidemics is not new, but still relevant and useful. In this chapter we provide relevant resources and useful exercises for undergraduate students and their mentors. We describe two different modeling techniques which require different backgrounds. For agent based modeling, we suggest students who are either comfortable with programming or willing to learn and who have basic knowledge of probability. For the differential equation approach, we suggest students who have taken at least Calculus 2. Students with a differential equation background will advance faster and can do a more theoretical analysis of the system. A student who might be willing to spend more time working on this topic can model the same disease outbreak using different modeling techniques which will allow for comparison and much deeper analysis of both the mathematics and the biological and public policy implications. Additionally, we include a sample project, developed and written by an undergraduate student who co-authors this chapter. Finally, we provide four different projects that students and their mentors can work on.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
L. J. Allen, F. Brauer, P. Van den Driessche, and J. Wu. Mathematical epidemiology, volume 1945. Springer, 2008.
M. Andraud, N. Hens, C. Marais, and P. Beutels. Dynamic epidemiological models for dengue transmission: a systematic review of structural approaches. PLoS One, 7(11):e49085, 2012.
J. Arino, J. R. Davis, D. Hartley, R. Jordan, J. M. Miller, and P. Van Den Driessche. A multi-species epidemic model with spatial dynamics. Mathematical Medicine and Biology, 22(2):129–142, 2005.
J. Arino and P. Van den Driessche. A multi-city epidemic model. Mathematical Population Studies, 10(3):175–193, 2003.
J. Arino and P. Van den Driessche. Disease spread in metapopulations. Fields Institute Communications, 48(1):1–13, 2006.
S. Bañuelos, T. Danet, C. Flores, and A. Ramos. An epidemiological math model approach to a political system with three parties. CODEE Journal, 12(1), 2019.
M. J. Berryman and S. D. Angus. Tutorials on agent-based modelling with NetLogo and network analysis with Pajek. World Scientific, 2010.
H. V. Boyett, D. G. Bourne, and B. L. Willis. Elevated temperature and light enhance progression and spread of black band disease on staghorn corals of the great barrier reef. Marine Biology, 151(5):1711–1720, 2007.
F. Brauer and C. Castillo-Chavez. Mathematical models in population biology and epidemiology, volume 40. Springer, 2012.
B. Calderhead, M. Girolami, and D. J. Higham. Is it safe to go out yet? Statistical inference in a zombie outbreak model, 2010.
G. Chartrand and P. Zhang. A first course in graph theory. Courier Corporation, 2013.
M. Clauson, A. Harrison, L. Shuman, M. Shillor, and A. Spagnuolo. Analysis of the steady states of a mathematical model for Chagas disease. Involve, A Journal of Mathematics, 5(3):237–246, 2013.
D. Clayton, M. Hills, and A. Pickles. Statistical models in epidemiology, volume 161. Oxford University Press, Oxford, 1993.
M. Dickerson. Multi-agent simulation and NetLogo in the introductory computer science curriculum. Journal of Computing Sciences in Colleges, 27(1):102–104, 2011.
O. Diekmann, H. Heesterbeek, and T. Britton. Mathematical tools for understanding infectious disease dynamics. Princeton University Press, 2013.
S. P. Ellner, L. E. Jones, L. D. Mydlarz, and C. D. Harvell. Within-host disease ecology in the sea fan Gorgonia ventalina: modeling the spatial immunodynamics of a coral-pathogen interaction. The American Naturalist, 170(6):E143–E161, 2007.
S. M. L. Emily K Kelting, Brittany E Bannish. Toxoplasma gondii: A mathematical model of its transfer between cats and the environment. Siuro, 11, 2018.
Fandom. The walking dead wiki, 2019. https://walkingdead.fandom.com/wiki/Zombies Last accessed on 2019-01-06.
K. R. Fister, H. Gaff, E. Schaefer, G. Buford, and B. Norris. Investigating cholera using an SIR model with age-class structure and optimal control. Involve, A Journal of Mathematics, 9(1):83–100, 2015.
N. Hartsfield and G. Ringel. Pearls in graph theory: a comprehensive introduction. Courier Corporation, 2013.
G. B. Jiechen Chen. Realistic modeling and simulation of influenza transmission over an urban community. Siuro, 8, 2015.
M. J. Keeling and P. Rohani. Modeling infectious diseases in humans and animals. Princeton University Press, 2011.
K. Khan, J. Arino, F. Calderon, A. Chan, M. Gardam, C. Heidebrecht, W. Hu, D. Janes, M. MacDonald, J. Sears, et al. An analysis of Canada’s vulnerability to emerging infectious disease threats via the global airline transportation network. Technical report, 2011.
K. Khan, J. Arino, W. Hu, P. Raposo, J. Sears, F. Calderon, C. Heidebrecht, M. Macdonald, J. Liauw, A. Chan, et al. Spread of a novel influenza a (H1N1) virus via global airline transportation. New England Journal of Medicine, 361(2):212–214, 2009.
S. Levin, T. Powell, and J. Steele. Patch dynamics (lecture notes in biomathematics 96), 1993.
R. L. Lineberry and I. Sharkansky. Urban politics and public policy. Harper & Row New York, 1978.
S. Mandal, R. R. Sarkar, and S. Sinha. Mathematical models of malaria-a review. Malaria Journal, 10(1):202, 2011.
P. Manfredi and A. D’Onofrio. Modeling the interplay between human behavior and the spread of infectious diseases. Springer Science & Business Media, 2013.
J. Mao-Jones, K. B. Ritchie, L. E. Jones, and S. P. Ellner. How microbial community composition regulates coral disease development. PLoS Biology, 8(3):1000345, 2010.
R. Margevicius and H. Joshi. The influence of education in reducing the HIV epidemic. Involve, A Journal of Mathematics, 6(2):127–135, 2013.
R. Martin, M. Sauer, E. Olawsky, and M. Marinello. Stochastic models for HIV transmission as a vector-host disease. Minnesota Journal of Undergraduate Mathematics, 2(1), 2017.
D. Maxin, T. Olson, and A. Shull. Vertical transmission in epidemic models of sexually transmitted diseases with isolation from reproduction. Involve, a Journal of Mathematics, 4(1):13–26, 2011.
A. K. Misra. A simple mathematical model for the spread of two political parties. Nonlinear Analysis: Modelling and Control, 17(3):343–354, 2012.
P. Munz, I. Hudea, J. Imad, and R. J. Smith. When zombies attack!: mathematical modelling of an outbreak of zombie infection. Infectious Disease Modelling Research Progress, 4:133–150, 2009.
S. P. Otto and T. Day. A biologist’s guide to mathematical modeling in ecology and evolution. Princeton University Press, 2011.
C. Ray and M. Hoopes. Metapopulation biology: ecology, genetics, and evolution. Ecology, 78(7):2270–2272, 1997.
R. C. Reiner Jr, T. A. Perkins, C. M. Barker, T. Niu, L. F. Chaves, A. M. Ellis, D. B. George, A. Le Menach, J. R. Pulliam, D. Bisanzio, et al. A systematic review of mathematical models of mosquito-borne pathogen transmission: 1970–2010. Journal of The Royal Society Interface, 10(81):20120921, 2013.
D. Smith and L. Moore. the SIR model for spread of disease - introduction. JOMA, Convergence, 2004.
The Political Compass. Political compass, 2019. https://www.politicalcompass.org/.
The Walking Dead Website. The walking dead comic book series official website, 2019. https://www.skybound.com/the-walking-dead/walking-dead-comics-story/ Last accessed on 2019-01-06.
United State Census Bureau. New census data show differences between urban and rural populations, 2016. https://www.census.gov/newsroom/press-releases/2016/cb16-210.html.
D. B. West et al. Introduction to graph theory, volume 2. Prentice Hall Upper Saddle River, 2001.
Wikipedia. Coral reef, 2019. https://en.wikipedia.org/wiki/Coral_reef Last accessed on 2019-01-06.
U. Wilensky. Netlogo, 1999.
C. Witkowski and B. Blais. Bayesian analysis of epidemics-zombies, influenza, and other diseases. arXiv preprint arXiv:1311.6376, 2013.
J. Woo and H. Chen. Epidemic model for information diffusion in web forums: experiments in marketing exchange and political dialog. SpringerPlus, 5(1):66, 2016.
K. Yokley, J. T. Lee, A. Brown, M. Minor, and G. Mader. A simple agent-based model of malaria transmission investigating intervention methods and acquired immunity. Involve, A Journal of Mathematics, 7(1):15–40, 2013.
Acknowledgement
The authors would like to thank the Office of Research at Youngstown State University for their support.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Bañuelos, S., Bush, M., Martinez, M.V., Prieto-Langarica, A. (2020). Undergraduate Research in Mathematical Epidemiology. In: Harris, P., Insko, E., Wootton, A. (eds) A Project-Based Guide to Undergraduate Research in Mathematics. Foundations for Undergraduate Research in Mathematics. Birkhäuser, Cham. https://doi.org/10.1007/978-3-030-37853-0_11
Download citation
DOI: https://doi.org/10.1007/978-3-030-37853-0_11
Published:
Publisher Name: Birkhäuser, Cham
Print ISBN: 978-3-030-37852-3
Online ISBN: 978-3-030-37853-0
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)