Measles epidemics and PEPA: An exploration of historic disease dynamics using process algebra

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7436 LNCS, Issue , 2012, Pages 101-115

  Benkirane, Soufiene ^a   Norman, Rachel ^a   Scott, Erin ^a   Shankland, Carron ^a  

^a UNIVERSITY OF STIRLING   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX DISEASE; DISEASE DYNAMICS; HISTORIC DATA; PROCESS ALGEBRAS; REALISTIC MODEL; SEASONAL EFFECTS; STOCHASTIC SIMULATIONS;

ALGEBRA; STOCHASTIC MODELS;

EPIDEMIOLOGY;

EID: 84865996961     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-32759-9_11     Document Type: Conference Paper

References (29)

1. Anderson, R.M., May, R.M.: The population-dynamics of micro-parasites and their invertebrate hosts. Philosophical Transactions of the Royal Society of London Series B 291, 451-524 (1981)
2. Benkirane, S.: Process algebra for epidemiology: evaluating and enhancing the ability of PEPA to describe biological systems. Ph.D. thesis, University of Stirling (2011), http://hdl.handle.net/1893/3603
3. Benkirane, S., Hillston, J., McCaig, C., Norman, R., Shankland, C.: Improved Continuous Approximation of PEPA Models through Epidemiological Examples. In: From Biology to Concurrency and Back, FBTC 2008. ENTCS, vol. 229, pp. 59-74. Elsevier (2008)
4. Bjørnstad, O.N., Finkenstädt, B.F., Grenfell, B.T.: Dynamics of measles epidemics: estimating scaling of transmission rates using a time series SIR model. Ecological Monographs 72(2), 169-184 (2002)
5. Bolker, B., Grenfell, B.: Space, persistence and dynamics of measles epidemics. Philosophical Transactions of the Royal Society of London - Series B: Biological Sciences 348(1325), 309-320 (1995)
6. Ciocchetta, F., Hillston, J.: Bio-PEPA: A framework for the modelling and analysis of biological systems. Theor. Comput. Sci. 410(33-34), 3065-3084 (2009)
7. Ciocchetta, F., Hillston, J.: Bio-PEPA for epidemiological models. Electronic Notes in Theoretical Computer Science 261, 43-69 (2010);
8. Proceedings of Practical Application of Stochastic Modelling (PASM 2009)
9. Duguid, A., Gilmore, S., Guerriero, M.L., Hillston, J., Loewe, L.: Design and development of software tools for Bio-PEPA. In: Proc. of Winter Simulation Conference 2009, pp. 956-967 (2009)
10. Duke, T., Mgone, C.S.: Measles: not just another viral exanthem. The Lancet 361, 763-773 (2003)
11. Durrett, R.: Probability: Theory and Examples. Cambridge Series in Statistical and Probabilistic Mathematics (2010)
12. Fine, P.E., Clarkson, J.A.: Measles in England and Wales-I: An analysis of factors underlying seasonal patterns. Int. Journal of Epidemiology 11(1), 5-14 (1982)
13. Finkenstädt, B.F., Keeling, M., Grenfell, B.T.: Patterns of density dependence in measles dynamics. Proceedings of the Royal Society B 265, 753-762 (1998)
14. Gilmore, S., Tribastone, M., Duguid, A., Clark, A.: PEPA plug-in for eclipse (2008), homepages.inf.ed.ac.uk/mtribast/plugin/
15. Hillston, J.: A Compositional Approach to Performance Modelling. Cambridge University Press (1996)
16. Hillston, J.: Tuning systems: From composition to performance. The Computer Journal 48(4), 385-400 (2005);
17. The Needham Lecture Paper
18. Kermack, W.O., McKendrick, A.G.: Contributions to the mathematical theory of epidemics. Proceedings of the Royal Society of London A 115, 700-721 (1927)
19. McCaig, C., Begon, M., Norman, R., Shankland, C.: A rigorous approach to investigating common assumptions about disease transmission: Process algebra as an emerging modelling methodology for epidemiology. Theory in Biosciences 130, 19-29 (2011);
20. special issue on emerging modelling methodologies
21. McCaig, C., Norman, R., Shankland, C.: From individuals to populations: A symbolic process algebra approach to epidemiology. Mathematics in Computer Science 2(3), 139-155 (2009)
22. McCaig, C.: From individuals to populations: changing scale in process algebra models of biological systems. Ph.D. thesis, University of Stirling (2008), http://hdl.handle.net/1893/398
23. Miller, D.L.: Frequency of complications of measles, 1963. British Medical Journal 2, 75-78 (1964)
24. Norman, R., Shankland, C.: Developing the Use of Process Algebra in the Derivation and Analysis of Mathematical Models of Infectious Disease. In: Moreno-Díaz Jr., R., Pichler, F. (eds.) EUROCAST 2003. LNCS, vol. 2809, pp. 404-414. Springer, Heidelberg (2003)
25. Perry, R., Halsey, N.: The clinical significance of measles: A review. Journal of Infectious Diseases 189(1), S4-S16 (2004)
26. The Medical News: Measles history, http://www.news-medical.net/health/ Measles-History.aspx
27. Tofts, C.: Processes with probabilities, priority and time. Formal Aspects of Computing 6, 536-564 (1994)
28. University of Cambridge: Pathogen population dynamics (2002), http://www.zoo.cam.ac.uk/zoostaff/grenfell/measles.htm
29. World Health Organization: The world health report 2004 (2004), http://www.who.int/whr/2004/annex/topic/en/annex-2-en.pdf