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Classroom Notes

Bringing back the people in modelling epidemics

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Pages 492-508 | Received 25 Mar 2023, Published online: 06 Sep 2023

References

  • Adiga, A., Dubhashi, D., Lewis, B., Marathe, M., Venkatramanan, S., & Vullikanti, A. (2020). Mathematical models for COVID-19 pandemic: A comparative analysis. Journal of the Indian Institute of Science, 100(4), 793–807. https://doi.org/10.1007/s41745-020-00200-6
  • Antonius, S. (2004). Modelling and applications – competences and democratic potential. Mathematics Education – The Nordic Way, 22–31. https://www.matematikksenteret.no/nettbutikk/mathematics-education-nordic-way, https://beta.matematikksenteret.no/sites/default/files/attachments/product/Pre-ICME10%20production.pdf#page=30
  • Arshad-Ayaz, A., & Naseem, M. A. (2021). Politics of citizenship during the COVID-19 pandemic: What can educators do? Journal of International Humanitarian Action, 6(1), 3. https://doi.org/10.1186/s41018-020-00089-x
  • Basu, S., & Andrews, J. (2013). Complexity in mathematical models of public health policies: A guide for consumers of models. PLOS Medicine, 10(10), e1001540. https://doi.org/10.1371/journal.pmed.1001540
  • Bauch, C., d’Onofrio, A., & Manfredi, P. (2013). Behavioral epidemiology of infectious diseases: An overview. In P. Manfredi & A. D'Onofrio (Eds.), Modeling the interplay between human behavior and the spread of infectious diseases. Springer. https://doi.org/10.1007/978-1-4614-5474-8_1
  • Blanchard, P. (1994). Teaching differential equations with a dynamical systems viewpoint. The College Mathematics Journal, 25(5), 385–393. https://doi.org/10.1080/07468342.1994.11973642
  • Bolzoni, L., Della Marca, R., & Groppi, M. (2021). On the optimal control of sir model with erlang-distributed infectious period: Isolation strategies. Journal of Mathematical Biology, 83(4), 36. https://doi.org/10.1007/s00285-021-01668-1
  • Borba, M. C., & Skovsmose, O. (1997). The ideology of certainty in mathematics education. For the Learning of Mathematics, 17(3), 17–23. http://www.jstor.org/stable/40248248.
  • Brauer, F., Castillo-Chavez, C., & Feng, Z. (2019). Mathematical models in epidemiology. Springer. https://doi.org/10.1007/978-1-4939-9828-9
  • Cronin, M. A., Gonzalez, C., & Sterman, J. D. (2009). Why don’t well-educated adults understand accumulation? A challenge to researchers, educators, and citizens. Organizational Behavior and Human Decision Processes, 108(1), 116–130. https://doi.org/10.1016/j.obhdp.2008.03.003
  • Diaz Eaton, C., Highlander, H. C., Dahlquist, K. D., Ledder, G., LaMar, M. D., & Schugart, R. C. (2019). A “rule-of-five” framework for models and modeling to unify mathematicians and biologists and improve student learning. Primus, 29(8), 799–829. https://doi.org/10.1080/10511970.2018.1489318
  • Ford, A. (1999). Modeling the environment: An introduction to system dynamics models of environmental systems. Island press.
  • Gibbs, A. M., & Park, J. Y. (2022). Unboxing mathematics: Creating a culture of modeling as critic. Educational Studies in Mathematics, 110(1), 167–192. https://doi.org/10.1007/s10649-021-10119-z
  • Guillemette, M. (2020). COVID-19: l’heure de gloire de la modélisation. Québec Science. https://www.quebecscience.qc.ca/sante/covid-19-heure-gloire-modelisation/.
  • Habre, S. (2020). Inquiry-oriented differential equations: A guided journey of learning. Teaching Mathematics and its Applications: An International Journal of the IMA, 39(3), 201–212. https://doi.org/10.1093/teamat/hrz015
  • Hallström, J., & Schönborn, K. J. (2019). Models and modelling for authentic STEM education: Reinforcing the argument. International Journal of STEM Education, 6(1), 1–10. https://doi.org/10.1186/s40594-019-0178-z
  • Hauge, K. H., & Barwell, R. (2017). Post-normal science and mathematics education in uncertain times: Educating future citizens for extended peer communities. Futures, 91, 25–34. https://doi.org/10.1016/j.futures.2016.11.013
  • Heyd-Metzuyanim, E., Sharon, S., & Baram-Tsabari, A. (2021). Mathematical media literacy in the COVID-19 pandemic and its relation to school mathematics education. Educational Studies in Mathematics, 108(1–2), 201–225. https://doi.org/10.1007/s10649-021-10075-8
  • INSPQ. (2022). COVID-19, Sondages sur les attitudes et les comportements des adultes québécois. Institut National de Santé Publique du Québec. https://www.inspq.qc.ca/covid-19/sondages-attitudes-comportements-quebecois.
  • Kapmeier, F., Happach, R. M., & Tilebein, M. (2017). Bathtub dynamics revisited: An examination of déformation professionelle in higher education. Systems Research and Behavioral Science, 34(3), 227–249. https://doi.org/10.1002/sres.2407
  • Kollosche, D., & Meyerhöfer, W. (2021). COVID-19, mathematics education, and the evaluation of expert knowledge. Educational Studies in Mathematics, 108(1), 401–417. https://doi.org/10.1007/s10649-021-10097-2
  • Krause, C. M., Di Martino, P., & Moschkovich, J. N. (2021). Tales from three countries: Reflections during COVID-19 for mathematical education in the future. Educational Studies in Mathematics, 108(1-2), 87–104. https://doi.org/10.1007/s10649-021-10066-9
  • Lang, R., Atabati, O., Oxoby, R. J., Mourali, M., Shaffer, B., Sheikh, H., Fullerton, M. M., Tang, T., Leigh, J. P., Manns, B. J., Marshall, D. A., Ivers, N. M., Ratzan, S. C., Hu, J., & Benham, J. L. (2021). Characterization of non-adopters of COVID-19 non-pharmaceutical interventions through a national cross-sectional survey to assess attitudes and behaviours. Scientific Reports, 11. https://doi.org/10.1038/s41598-021-01279-2
  • Lau, N. T. T., Wilkey, E. D., Soltanlou, M., Lagacé Cusiac, R., Peters, L., Tremblay, P., Goffin, C., Alves, I. S., Ribner, A. D., Thompson, C., Van Hoof, J., Bahnmueller, J., Alvarez, A., Bellon, E., Coolen, I., Ollivier, F., & Ansari, D. (2022). Numeracy and COVID-19: Examining interrelationships between numeracy, health numeracy and behaviour. Royal Society Open Science, 9(3), https://doi.org/10.1098/rsos.201303
  • Ledder, G., & Homp, M. (2022). Using a COVID-19 model in various classroom settings to assess effects of interventions. PRIMUS, 32(2), 278–297. https://doi.org/10.1080/10511970.2020.1861143
  • Lesh, R., Post, T., & Behr, M. (1987). Representations and translations among representations in mathematics learning and problem solving. In C. Janvier (Ed.), Problems of representation in the teaching and learning of mathematics (pp. 33–40). Erlbaum.
  • Lopes, A. P. C. (2022). Aspects of attitudes towards mathematics in modeling activities: Usefulness, interest, and social roles of mathematics. International Electronic Journal of Mathematics Education, 17(4), https://doi.org/10.29333/iejme/12394
  • Maass, K., Geiger, V., Ariza, M. R., & Goos, M. (2019). The role of mathematics in interdisciplinary STEM education. ZDM, 51(6), 869–884. https://doi.org/10.1007/s11858-019-01100-5
  • Mainali, B. (2020). Representation in teaching and learning mathematics. International Journal of Education in Mathematics, Science and Technology, 9(1), 1–21. https://doi.org/10.46328/ijemst.1111
  • Martínez-Córdoba, P. J., Benito, B., & García-Sánchez, I. M. (2021). Bibliometric analysis of peer-reviewed literature on antimicrobial stewardship from 1990 to 2019. Globalization and Health, 17(1), 1–13. https://doi.org/10.1186/s12992-020-00651-7
  • Pagel, C., & Yates, C. A. (2022). Role of mathematical modelling in future pandemic response policy. BMJ, 378. https://doi.org/10.1136/bmj-2022-070615
  • Rasmussen, C., & Kwon, O. (2007). An inquiry-oriented approach to undergraduate mathematics. The Journal of Mathematical Behavior, 26(3), 189–194. https://doi.org/10.1016/j.jmathb.2007.10.001
  • Rhodes, T., & Lancaster, K. (2020). Mathematical models as public troubles in COVID-19 infection control: Following the numbers. Health Sociology Review, 29(2), 177–194. https://doi.org/10.1080/14461242.2020.1764376
  • Rubin, D. M., Achari, S., Carlson, C. S., Letts, R. F., Pantanowitz, A., Postema, M., & Wigdorowitz, B. (2021). Facilitating understanding, modeling and simulation of infectious disease epidemics in the age of COVID-19. Frontiers in Public Health, 9, 593417. https://doi.org/10.3389/fpubh.2021.593417
  • Sandset, T., & Villadsen, K. (2023). Pandemic modelling and model citizens: Governing COVID-19 through predictive models, sovereignty and discipline. The Sociological Review, 71(3). https://doi.org/10.1177/00380261221102023
  • Skovsmose, O., & Valero, P. (2008). Democratic access to powerful mathematical ideas. Handbook of International Research in Mathematics Education. Directions for the 21st Century. (2nd ed., pp. 415–438). Erlbaum.

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