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A note on maximum likelihood estimation of the initial number of susceptibles in the general stochastic epidemic model

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  • Kypraios, Theodore

Abstract

The initial number of susceptible individuals in a population is usually assumed to be known and statistical inference for some of the quantities of interest, such as the basic reproductive number R0, is straightforward. However, in any epidemic, there may exist a number of individuals who may not be involved in the transmission of the disease. In this note we show how maximum likelihood estimators can be derived for the parameters of interest. The proposed methodology is then applied to the Abakaliki smallpox data in Nigeria.

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  • Kypraios, Theodore, 2009. "A note on maximum likelihood estimation of the initial number of susceptibles in the general stochastic epidemic model," Statistics & Probability Letters, Elsevier, vol. 79(18), pages 1972-1976, September.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:18:p:1972-1976
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    1. P. D. O’Neill & G. O. Roberts, 1999. "Bayesian inference for partially observed stochastic epidemics," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 162(1), pages 121-129.
    2. Huggins, Richard M. & Yip, Paul S. F. & Lau, Eric H. Y., 2004. "A note on the estimation of the initial number of susceptible individuals in the general epidemic model," Statistics & Probability Letters, Elsevier, vol. 67(4), pages 321-330, May.
    3. Niels G. Becker & Abraham M. Hasofer, 1997. "Estimation in Epidemics with Incomplete Observations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(2), pages 415-429.
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