Exact Bayesian inference and model selection for stochastic models of epidemics among a community of households

Scandinavian Journal of Statistics

Volumn 34, Issue 2, 2007, Pages 259-274

  Clancy, Damian ^a   O'Neill, Philip D ^b  

^a UNIVERSITY OF LIVERPOOL   (United Kingdom)

^b UNIVERSITY OF NOTTINGHAM   (United Kingdom)

Author keywords

Bayesian inference; Bayesian model selection; Epidemic data; Influenza; Rejection sampling; Stochastic epidemic models

Indexed keywords

EID: 34547321913     PISSN: 03036898     EISSN: 14679469     Source Type: Journal    
DOI: 10.1111/j.1467-9469.2006.00522.x     Document Type: Article

References (21)

1. Addy, C. L., Longini, I. M. Haber, M. (1991). A generalized stochastic model for the analysis of infectious disease final size data. Biometrics 47, 961 974.
2. Andersson, H. Britton, T. (2000). Stochastic epidemic models and their statistical analysis. Lecture Notes in Statistics 151, Springer, New York, NY.
3. Ball, F. G., Mollison, D. Scalia-Tomba, G. (1997). Epidemics with two levels of mixing. Ann. Appl. Probab. 7, 46 89.
4. Becker, N. G. (1989). Analysis of infectious disease data. Chapman and Hall, London.
5. Becker, N. G., Britton, T. O'Neill, P. D. (2003). Estimating vaccine effects on transmission of infection from household outbreak data. Biometrics 59, 467 475.
6. Cauchemez, S., Carrat, F., Viboud, C., Valleron, A. J. Böelle, P. Y. (2004). A Bayesian MCMC approach to study transmission of influenza: application to household longitudinal data. Statist. Med. 23, 3469 3487.
7. Fox, J. P. Hall, C. E. (1980). Viruses in families, PSG Publishing, Littleton, MA.
8. Gibson, G. J. (1997). Markov chain Monte Carlo methods for fitting spatio-temporal stochastic models in plant epidemiology. J. Roy. Statist. Soc. Ser. C 46, 215 233.
9. Lee, J. C. Sabavala, D. J. (1987). Bayesian estimation and prediction for the beta-binomial model. J. Bus. Econ. Statist. 5, 357 367.
10. Lefèvre, C. Picard, P. (1990). A non-standard family of polynomials and the final size distribution of Reed-Frost epidemic processes. Adv. Appl. Probab. 22, 25 48.
11. Longini, I. M. Koopman, J. S. (1982). Household and community transmission parameters from final distributions of infections in households. Biometrics 38, 115 126.
12. Longini, I. M., Koopman, J. S., Monto, A. S. Fox, J. P. (1982). Estimating household and community transmission parameters for influenza. Amer. J. Epidemiol. 115, 736 751.
13. Longini, I. M., Koopman, J. S., Haber, M. Cotsonis, G. A. (1988). Statistical inference for infectious diseases. Risk-specific household and community transmission parameters. Amer. J. Epidemiol. 128, 845 859.
14. Minhajuddin, A. T. M., Harris, I. R. Schucany, W. R. (2004). Simulating multivariate distributions with specific correlations. J. Statist. Comput. Simul. 74, 599 607.
15. Monto, A. S., Koopman, J. S. Longini, I. M. (1985). Tecumseh study of illness. XIII. Influenza infection and disease, 1976-1981. Am. J. Epidemiol. 121, 811 822.
16. O'Hagan, A. (1994). Kendall's advanced theory of statistics vol. 2B: Bayesian inference. Edward Arnold, London, UK.
17. O'Neill, P. D. (2002). A tutorial introduction to Bayesian inference for stochastic epidemic models using Markov chain Monte Carlo methods. Math. Biosci. 180, 103 114.
18. O'Neill, P. D. (2003). Perfect simulation for Reed-Frost epidemic models. Statist. Comput. 13, 37 44.
19. O'Neill, P. D. Marks, P. J. (2005). Bayesian model choice and infection route modelling in an outbreak of Norovirus. Statist. Med. 24, 2011 2024.
20. O'Neill, P. D., Balding, D. J., Becker, N. G., Eerola, M. Mollison, D. (2000). Analyses of infectious disease data from household outbreaks by Markov chain Monte Carlo methods. J. Roy. Statist. Soc. Ser. C 49, 517 542.
21. Ripley, B. D. (1987). Stochastic simulation, Wiley, New York, NY.