Abstract
This paper considers estimation of the within-household infection rate for a Markov SIR (susceptible → infective → recovered) epidemic among a population that is partitioned into households, from data on the early exponentially growing phase of an epidemic. It is assumed that an estimate of the early exponential growth rate r of the epidemic is available, together with more detailed household-level data from a sample of households. A basic method, which uses the total size distribution of single-household epidemics, is usually biased owing to the emerging nature of an epidemic. An alternative method, which uses the asymptotic theory of continuous-time, multitype Markov branching processes to account for the emerging nature of an epidemic, is developed and shown by simulations to be feasible for realistic population sizes. A modified single-household epidemic process is used to show that the basic method is approximately unbiased when r is small.
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Laurence Shaw was supported by an EPSRC Doctoral Training grant.
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Ball, F., Shaw, L. (2016). Inference for Emerging Epidemics Among a Community of Households. In: del Puerto, I., et al. Branching Processes and Their Applications. Lecture Notes in Statistics(), vol 219. Springer, Cham. https://doi.org/10.1007/978-3-319-31641-3_16
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DOI: https://doi.org/10.1007/978-3-319-31641-3_16
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