Simulations for Epidemiology and Public Health Education
Recent and potential outbreaks of infectious diseases are triggering interest in predicting epidemic dynamics on a national scale and testing the efficacies of different combinations of public health policies. Network-based simulations are proving their worth as tools for addressing epidemiology and public health issues considered too complex for field investigations and questionnaire analyses. Universities and research centres are therefore using network-based simulations as teaching tools for epidemiology and public health education students, but instructors are discovering that constructing appropriate network models and epidemic simulations are difficult tasks in terms of individual movement and contact patterns. In this paper we will describe (a) a four-category framework (based on demographic and geographic properties) to discuss ways of applying network-based simulation approaches to undergraduate students and novice researchers; (b) our experiences simulating the transmission dynamics of two infectious disease scenarios in Taiwan (HIV and influenza); (c) evaluation results indicating significant improvement in student knowledge of epidemic transmission dynamics and the efficacies of various public health policy suites; and (d) a geospatial modelling approach that integrates a national commuting network as well as multi-scale contact structures.
KeywordsHepatitis Transportation Influenza Syringe Heroin
Unable to display preview. Download preview PDF.
- Aldrich C (2004). Simulations and the Future of Learning: An Innovative (and Perhaps Revolutionary) Approach to e-Learning. Pfeiffer: San Francisco, CA.Google Scholar
- Barrett CL, Eubank SG and Smith JP (2003). If smallpox strikes Portland. Sci Am 292 (3): 42–49.Google Scholar
- Bertsche D, Crawford C and Macadam SE (1996). Is simulation better than experience. McKinsey Quart 1 (1): 50–58.Google Scholar
- Directorate General of Budget, Accounting and Statistics (2006). Social indicators, Executive Yuan, Republic of China.Google Scholar
- Gilbert GN and Troitzsch KG (1999). Simulation for the Social Scientist. Open University Press: Philadelphia, PA.Google Scholar
- Hargrave CP and Kenton JM (2000). Preinstructional simulations: Implications for science classroom teaching. J Comput Math Sci Teach 19 (1): 47–58.Google Scholar
- Hsieh JL, Huang CY, Sun CT and Chen YMA (2005). Using the CAMIM small-world epidemic model to analyze public health policies. In: Proceedings of Western Simulation Multiconference on Health Sciences Simulation. New Orleans, Louisiania, USA, pp 63–69. The Society for Modeling and Simulation International: San Diego, California, USA.Google Scholar
- Huang CY, Sun CT, Hsieh JL and Lin H (2004). Simulating SARS: Small-world epidemiological modelling and public health policy assessments. JASSS7 (4), http://jasss.soc.surrey.ac.uk/7/4/2.html.
- Huang CY, Sun CT and Lin HC (2005a). Influence of local information on social simulations in small-world network models. JASSS 8(4), http://jasss.soc.surrey.ac.uk/8/4/8.html.
- Klein CA, Berlin LS, Kostolansky TJ and Del Palacio JR (2004). Stock simulation Engine for an Options Trading Game, Issued on March 23, 2003. United States Patent No. 6709330.Google Scholar
- Levy M, Levy H and Solomon S (1995). Microscopic simulation of the stock market: The effect of microscopic diversity. J Phys I 5: 1087–1107.Google Scholar
- Liao YH and Sun CT (2001). An educational genetic algorithms learning tool. IEEE T Educ 44 (2): 20.Google Scholar
- Piaget J (1978). The Development of Thought: Equilibration of Cognitive Structures. Viking Press: New York, NY.Google Scholar
- Savery JR and Duffy TM 1995. Problem based learning: An instructional model and its constructivist framework. Educ Technol 35 (5): 31–38.Google Scholar
- Stroud P et al (2007). Spatial dynamics of pandemic influenza in a massive artificial society. JASSS10 (4), http://jasss.soc.surrey.ac.uk/10/4/9.html.
- Sumodhee CJ, et al (2005). Impact of social behaviors on HIV epidemic: A computer simulation view. In: Proceedings of International Conference on Computational Intelligence for Modelling, Control and Automation, Vienna, Austria 2: 550–556. IEEE Computer Society: Los Alamitos, CA, USA.Google Scholar
- Wenglinsky H 1998. Does it Compute? The Relationship Between Educational Technology and Student Achievement in Mathe matics. Educational Testing Service: Princeton, NJ.Google Scholar