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Development of an individual-based model for polioviruses: implications of the selection of network type and outcome metrics

  • H. RAHMANDAD (a1), K. HU (a1), R. J. DUINTJER TEBBENS (a2) (a3) and K. M. THOMPSON (a2)
Summary

We developed an individual-based (IB) model to explore the stochastic attributes of state transitions, the heterogeneity of the individual interactions, and the impact of different network structure choices on the poliovirus transmission process in the context of understanding the dynamics of outbreaks. We used a previously published differential equation-based model to develop the IB model and inputs. To explore the impact of different types of networks, we implemented a total of 26 variations of six different network structures in the IB model. We found that the choice of network structure plays a critical role in the model estimates of cases and the dynamics of outbreaks. This study provides insights about the potential use of an IB model to support policy analyses related to managing the risks of polioviruses and shows the importance of assumptions about network structure.

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Corresponding author
*Author for correspondence: Dr H. Rahmandad, Department of Industrial and Systems Engineering, Virginia Tech, Falls Church, VA 22043, USA. (Email: hazhir@vt.edu)
References
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1.Dutta, A. Epidemiology of poliomyelitis – options and update. Vaccine 2008; 26: 57675773.
2.Thompson, KM, Duintjer Tebbens, RJ. Eradication versus control for poliomyelitis: an economic analysis. Lancet 2007; 369: 13631371.
3.Thompson, KM, et al. The risks, costs, and benefits of possible future global policies for managing polioviruses. American Journal of Public Health 2008; 98: 13221330.
4.Duintjer Tebbens, RJ, et al. Uncertainty and sensitivity analyses of a decision analytic model for posteradication polio risk management. Risk Analysis 2008; 28: 855876.
5.Duintjer Tebbens, RJ, et al. Risks of paralytic disease due to wild or vaccine-derived poliovirus after eradication. Risk Analysis 2006; 26: 14711505.
6.Sutter, RW, Kew, OM, Cochi, SL. Poliovirus vaccine – live. In: Plotkin, SA, Orenstein, WA, Offit, PA, eds. Vaccines, 5th edn. Philadelphia: Saunders Elsevier, 2008, pp. 631686.
7.Nathanson, N, Martin, J. The epidemiology of poliomyelitis: enigmas surrounding its appearance, epidemicity, and disappearance. American Journal of Epidemiology 1979; 110: 672692.
8.Dowdle, W, Birmingham, M. The biologic principles of poliovirus eradication. Journal of Infectious Diseases 1997; 175: 286292.
9.Duintjer Tebbens, RJ, et al. A dynamic model of poliomyelitis outbreaks: learning from the past to help inform the future. American Journal of Epidemiology 2005; 162: 358372.
10.Aylward, RB, et al. Risk management in a polio-free world. Risk Analysis 2006; 26: 14411448.
11.Prevots, D, Ciofi degli, AM, Sallabanda, A. Outbreak of paralytic poliomyelitis in albania, 1996: High attack rate among adults and apparent interruption of transmission following nationwide mass vaccination. Clinical Infectious Diseases 1998; 26: 419425.
12.World Health Organization. Polio eradication initiative cessation of routine oral polio vaccine (OPV) use after global polio eradication. Framework for national policy makers in OPV-using countries. WHO: Geneva. Switzerland, 2005.
13.Thompson, KM, Duintjer Tebbens, RJ. The case for cooperation in managing and maintaining the end of poliomyelitis: stockpile needs and coordinated OPV cessation. Medscape Journal of Medicine 2008; 10, 190.
14.Duintjer Tebbens, RJ, et al. Optimal vaccine stockpile design for an eradicated disease: Application to polio. Vaccine 2010; 28: 43124327.
15.Thompson, KM, Duintjer Tebbens, RJ, Pallansch, MA. Evaluation of response scenarios to potential polio outbreaks using mathematical models. Risk Analysis 2006; 26: 15411556.
16.Colizza, V, et al. Epidemic predictions and predictiability in complex environments. International Symposium on Mathematical and Computational Biology (BIOMAT 2007); 2007 24–29 November, Armacao dos Buzios, Brazil.
17.Toivonen, R, et al. The role of edge weights in social networks: modelling structure and dynamics. Conference on Noise and Stochastics in Complex Systems and Finance, 21–24 May 2007. Florence, Italy.
18.Jeger, MJ, et al. Modelling disease spread and control in networks: implications for plant sciences. New Phytologist 2007; 174: 279297.
19.Keeling, MJ, et al. Dynamics of the 2001 UK foot and mouth epidemic: stochastic dispersal in a heterogeneous landscape. Science 2001; 294: 813817.
20.Wallinga, J, Edmunds, WJ, Kretzschmar, M. Perspective: human contact patterns and the spread of airborne infectious diseases. Trends in Microbiology 1999; 7: 372377.
21.Riley, S. Large-scale spatial-transmission models of infectious disease. Science 2007; 316: 12981301.
22.Rahmandad, H, Sterman, J. Heterogeneity and network structure in the dynamics of diffusion: Comparing agent-based and differential equation models. Management Science 2008; 54: 998–1014.
23.Brisson, M, et al. Modelling the impact of immunization on the epidemiology of varicella zoster virus. Epidemiology and Infection 2000; 125: 651669.
24.Mossong, J, et al. Social contacts and mixing patterns relevant to the spread of infectious diseases. PLOS Medicine 2008; 5: 381391.
25.Erdos, P, Renyi, A. On the evolution of random graphs. Publications of the Mathematical Inistitute of the Hungarian Academy of Sciences 1960; 5: 1761.
26.Watts, DJ, Strogatz, SH. Collective dynamics of ‘small-world’ networks. Nature 1998; 393: 440442.
27.Barabasi, AL, Albert, R. Emergence of scaling in random networks. Science 1999; 286: 509512.
28.Ferguson, NM, Donnelly, CA, Anderson, RM. Transmission intensity and impact of control policies on the foot and mouth epidemic in Great Britain. Nature 2001; 414: 329.
29.Eames, KTD, Read, JM, Edmunds, WJ. Epidemic prediction and control in weighted networks. Epidemics 2009; 1: 7076.
30.Friedman, SR, et al. Some data-driven reflections on priorities in aids network research. AIDS and Behavior 2007; 11: 641651.
31.Longini, IM Jr., et al. Containing pandemic influenza at the source. Science 2005; 309: 10831087.
32.Halloran, ME, et al. Modeling targeted layered containment of an influenza pandemic in the united states. Proceedings of the National Academy of Sciences USA 2008; 105: 46394644.
33.Zagheni, E, et al. Using time-use data to parameterize models for the spread of close-contact infectious diseases. American Journal of Epidemiology 2008; 168: 10821090.
34.Eubank, S, et al. Modelling disease outbreaks in realistic urban social networks. Nature 2004; 429: 180184.
35.Melnick, JL. Poliovirus and other enteroviruses. In: Evans, AS, Kaslow, RA, eds. Viral Infections of Humans: Epidemiology and Control. New York, NY: Plenum Medical Book Company, 1997, pp. 583663.
36.Highfield, LD, et al. Critical parameters for modelling the spread of foot-and-mouth disease in wildlife. Epidemiology and Infection 2010; 138: 125138.
37.Viet, AF, Fourichon, C, Seegers, H. Review and critical discussion of assumptions and modelling options to study the spread of the bovine viral diarrhoea virus (BVDV) within a cattle herd. Epidemiology and Infection 2007; 135: 706721.
38.Colizza, V, et al. Modeling the worldwide spread of pandemic influenza: baseline case and containment interventions. PLOS Medicine 2007; 4: 95–110.
39.May, RM. Uses and abuses of mathematics in biology. Science 2004; 303: 790793.
40.Donnelly, CA, Cox, DR. Mathematical biology and medical statistics: Contributions to the understanding of aids epidemiology. Statistical Methods in Medical Research 2001; 10: 141154.
41.Anderson, RM, Gupta, S, Ng, W. The significance of sexual partner contact networks for the transmission dynamics of hiv. Journal of Acquired Immune Deficiency Syndromes 1990; 3: 417429.
42.Ferguson, NM, et al. Strategies for containing an emerging influenza pandemic in southeast asia. Nature 2005; 437: 209214.
43.Centers for Disease Control and Prevention. Resurgence of wild poliovirus type 1 transmission and consequences of importation – 21 previously polio-free countries, 2002–2005. Morbidity and Mortality Weekly Report 2006; 55: 145150.
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Epidemiology & Infection
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