K - College of Natural Resources - University of California, Berkeley

quantity p0, the proportion of cases not transmitting, to be tabulated routinely alongside
R0 in outbreak reports.
Due to its self-evident existence and suspected importance, heterogeneity in
infectiousness has been incorporated in previous theoretical and simulation studies of
DCC dynamics. Lipsitch et al. (Lipsitch et al. 2003) used a branching process as a
heuristic tool to demonstrate the increased extinction probability due to individual
variation for SARS, and superspreading individuals were included in a network
simulation of SARS (Masuda et al. 2004). A separate analysis assumed an exponential
distribution of transmission rates for SARS (Chowell et al. 2004). Gani & Leach (Gani
and Leach 2004) showed that pneumonic plague transmission is described better by a
geometric than a Poisson distribution, and explored resulting impacts on control
measures. “Epidemic trees” reconstructed from the 2001 outbreak of foot-and-mouth
disease in Britain allowed direct estimation of farm-level reproductive numbers, and
emphasized the importance of variance in ν (Haydon et al. 2003). Observed prevalence
patterns of Escherichia coli O157 in Scottish cattle farms were explained better by
models incorporating individual-level variation in transmission than those with farm-
level differences L. Matthews et al., in preparation.. Chain binomial models
incorporating various assumptions about infectiousness have been used to study
stochastic outbreaks in finite populations (such as households) in great detail (Bailey
1975; Becker 1989), and analysis of a multitype branching process yielded important
insight into group-level variation in both infectiousness and susceptibility (Becker and
Marschner 1990). Our study builds on this work, presenting empirical evidence
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