However, such interpretations required confirmation by the analysis of larger samples collected from wide range of outbreaks.
Comparison of model outputs with public health surveillance data to verify that they reflect the range of outbreaks observed to date may be a useful means of validating the simulated datasets and model parameters.
Strategies used to support validity have included the incorporation of uncertainty using sensitivity analyses, modelling a range of possible scenarios [ 9], and simulating a range of outbreaks so that those most similar to observed outbreaks for the disease under investigation can be used [ 4].
The stochastic nature of the model ensures that simulations provide a representation of the possible range of outbreak scenarios based on existing knowledge about disease transmission.
However, we present this figure for qualitative comparisons, so that the reader can visualize the effects of baseline and outbreak temporal distribution, size, and duration on relative algorithm performance, over the range of outbreak signals we tested.
Next, we simulated a range of outbreak signal durations (lasting 1, 2, 4, 6, 8, 16, and 32 days) and a range of sizes using the forecast errors of the six algorithms[ 18].
Our estimate of a person-to-person basic reproduction number R0 pp ≈ 1 in 1976 suggests that Ebola would have been capable of generating a wide range of outbreak sizes in the absence of any extrinsic variation in epidemiological conditions.
Rather than try to model the full outbreak process from infection to ED visit, as has been done for some limited outbreak types[ 17], we tried to model a wide range of outbreak signals, representing various ways that outbreaks in the community could alter ED syndrome counts.
Starting in the mid-1990s, the frequency, severity, and geographic range of WNV outbreaks increased, and outbreaks of WNV meningitis and encephalitis affecting primarily adults struck Bucharest, Romania, in 1996, Volgograd, Russia, in 1999, and Israel, in 2000 [ 14– 16].
These potential changes in migratory patterns could help to spread or limit the range of anthrax outbreaks and subsequent B. anthracis introduction and survival.
Agent-based models should be applied in the future to evaluate the efficacy of control measures for a range of disease outbreaks in a range of settings given sufficient information about the given case and knowledge about the transmission processes at a fine scale.
