The Stochastic SIR Household Epidemics With TI ≡ 4:1 and TI Having GAMMA(a, b) Infectious Period Distribution
Abstract
Model estimates, their functions are in no doubt affected by wrong choice of the infectious period distribution, TI when the actual one is unknown. This is a misspecification problem which is often accompanied with biased and imprecise estimates. This work does not com- pletely examined this problem but explored the choice of constant infectious period, TI ≡ 4.1 and TI distributed as Γ(2, 2.05) for the household epidemic and then examined their effects on the behaviours of the model functions and quality of its maximum likelihood estimates in order to see if there are considerable disparities in the maximum likelihood estimates and behaviours of the functions giving these scenarios and whether constant infectious period is a reasonable assumption for the stochastic SIR household epidemic.
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References
[2] H. ANDERSSON AND T. BRITTON. (2000). Lecture Notes in Statistics: Stochastic Epidemic Models and Their Statistical Analysis. Springer, Verlag.
[3] F. G. BALL. (1983). The Threshold Behaviour of Epidemic Models. Journal of Applied Probability, 20(2) :) 227-241.
[4] F. G. BALL. (1986). A Unified Approach to the Distribution of the total size and Total Area under the Trajectory of Infection in Epidemic Models. Advances in Applied Probability, 18(2) : 289-310.
[5] F. G. BALL, D. MOLLISON AND G. SCALIA-TOMBA. (1997). Epdemics with Two Levels of Mixing. Annals of Applied Probability, 7(1) : 46-89.
[6] F. G. BALL AND O. D. LYNE. (2000). Epidemics Among A Population of Households. Mathematical Approaches for the Emerging and Reemerging Infectious Disease: Models, Methods and Theory, (The IMA Volumes in Mathematics and its Applications), Springer, Editor: Castillo-Chavez, 126 : 115-125.
[7] F. G. BALL AND P. NEAL. (2002). A general model for the stochastic SIR epidemic with two levels of mixing. Journal of Math. Biosciences, 180 : 73-102.
[8] N. G. BECKER. (1989). Analysis of Infectious Disease Data: Monographs on Statistics and Applied Probability. Chapman and Hall/CRC.
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[9] M. E. HALLORAN, I. M. LONGINI AND C. J. STRUCHINER. (2010). Design and Analysis of Vaccine Studies. Statistics for Biology and Health, Springer.
[10] I. M. LONGINI, JR AND J.S. KOOPMAN. (1982). Household and Community Transmis- sion Parameters from Final Distribution of Infections in Households. Biometrics, 38(1) : 115-126.
[11] I. M. LONGINI, JR, J. S. KOOPMAN, A. S. MONTO, AND J. P. FOX. (1982). Estimat- ing Household and Community Transmission Parameters for Influenza. American Journal of Epidemiology, 115(5) : 736-750.
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