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Volume 12, Number 12—December 2006

Research

Evaluating Detection of an Inhalational Anthrax Outbreak

David L. Buckeridge*Comments to Author , Douglas K. Owens†‡, Paul Switzer‡, John Frank§, and Mark A. Musen‡
Author affiliations: *McGill University, Montreal, Quebec, Canada; †Veterans Affairs Palo Alto Health Care System, Palo Alto, California, USA; ‡Stanford University, Stanford, California, USA; §University of Toronto, Toronto, Ontario, Canada

Main Article

Table 1

Sampling intervals for parameter values in the simulation model*

Parameter Parameter value intervals Probability distribution Source†
Disease model
Incubation duration, d; median (5, 9) (9, 11) (11, 15) Log normal (2,21,22)
Incubation duration, dispersion (1.5, 1.9) (1.9, 2.1) (2.1, 2.5) Log normal (2,21,22)
Prodromal duration, d; median (1.5, 2.3) (2.3 ,2.7) (2.7, 3.5) Log normal (2,22)
Prodromal duration, dispersion (1.2, 1.4) (1.4, 1.5) (1.5, 1.7) Log normal (2,22)
Healthcare use
Probability of visit, prodromal state (0.05, 0.25) (0.25, 0.35) (0.35, 0.55) Bernoulli (23,24)
Probability of visit, fulminant state (0.7, 0.9) (0.9, 0.95) (0.95, 1) Bernoulli Estimate
Probability of respiratory syndrome, prodromal state (0.5, 0.7) (0.7, 0.8) (0. 8,1) Bernoulli (25,26)
Blood culture test, prodromal state (0.001, 0.01) (0.01, 0.015) (0.015, 0.025) Bernoulli (28)
Blood culture test, fulminant state (0.7, 0.9) (0.9, 0.95) (0.95, 1) Bernoulli Estimate
Sensitivity of blood culture (0.5, 0.8) (0.8, 0.9) (0.9, 1) Bernoulli (27)
Time until blood culture growth, d (0.4, 0.8) (0.8, 1.0) (1.0, 1.4) Exponential (30)
Probability of isolation given growth (0.5, 0.8) (0.8, 0.9) (0.9, 1) Bernoulli (29)
Time until blood culture isolation, d (0.5, 0.6) (0.6, 0.9) (0.9, 1.5) Exponential (25)

*Using a Latin hypercube strategy, a value for each parameter was sampled by randomly selecting 1 of the 3 intervals for the parameter and randomly sampling a value on the selected interval. The sampled values parameterize probability distributions, which are sampled for the simulation model.
†References that support the parameter value intervals.

*Using a Latin hypercube strategy, a value for each parameter was sampled by randomly selecting 1 of the 3 intervals for the parameter and randomly sampling a value on the selected interval. The sampled values parameterize probability distributions, which are sampled for the simulation model.
†References that support the parameter value intervals.

*Using a Latin hypercube strategy, a value for each parameter was sampled by randomly selecting 1 of the 3 intervals for the parameter and randomly sampling a value on the selected interval. The sampled values parameterize probability distributions, which are sampled for the simulation model.
†References that support the parameter value intervals.

Main Article

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