A Simple Geometric Validation Approach to Assess the Basic Behaviour of Space- and Time- Distributed Models of Epidemic Spread - An Example Using the Ontario Rabies Model

Abstract

Dynamic mathematical modelling and stochastic simulation of disease-host systems for the purpose of epidemiological analysis offer great opportunities for testing hypotheses, especially when field experiments are impractical or when there is a need to evaluate multiple experimental scenarios. This, combined with the ever increasing computer power available to researchers, has contributed to the development of many mathematical models for epidemic simulations, such as the individual-based model (IBM). Nevertheless, few of these models undergo extensive validation and proper assessment of intrinsic variability. The Ontario rabies model (ORM) will be used here to exemplify some advantages of appropriate model behaviour validation and to illustrate the use of a simple geometric procedure for testing directional bias in distributed stochastic dynamic model of spread of diseases. Results were obtained through the comparison of 10 000 epizootics resulting from 100 epidemic simulations started using 100 distinct base populations. The analysis results demonstrated a significant directional bias in epidemic dispersion, which prompted further verification of the model code and the identification of a coding error, which was then corrected. Subsequent testing of the corrected code showed that the directional bias could no longer be detected. These results illustrate the importance of proper validation and the importance of sufficient knowledge of the model behaviour to ensure the results will not confound the objectives of the end-users.

Modelling the effect of landscape heterogeneity on the efficacy of vaccination for wildlife infectious disease control

“…; Rees ; Ludwig et al . ). Because sensitivity analysis indicated strong disease response to the disease transmission parameter and because this parameter was estimated by a model fitting process similar to Smith et al .…”

“…Values for population and disease dynamics input parameters (Table 1) were primarily drawn from empirical scientific studies for the mid-latitude eastern North American raccoon and rabies system, primarily from Ontario, Canada (Rees et al 2008). Validity and sensitivity analyses demonstrated that the model parameter set was parsimonious and that the model responded to input parameters as expected (Rees et al 2004;Rees 2007;Ludwig et al 2012). Because sensitivity analysis indicated strong disease response to the disease transmission parameter and because this parameter was estimated by a model fitting process similar to Smith et al (2002) rather than from direct empirical evidence, we conducted further experiment-specific sensitivity analyses described in the following statistical analysis section.…”

Differential impacts of vaccination on wildlife disease spread during epizootic and enzootic phases

“…Model processes were stochastically determined and operated at a weekly interval. Validity and sensitivity analyses demonstrated that the model parameter set simulated the expected raccoon demographics and RRV dynamics (Ludwig, Berthiaume, Richer, Tinline, & Bigras‐Poulin, ; Rees, ; Rees, Pond, Tinline, & Ball, ; Rees et al., ).…”

“…Validity and sensitivity analyses demonstrated that the model parameter set simulated the expected raccoon demographics and RRV dynamics (Ludwig, Berthiaume, Richer, Tinline, & Bigras-Poulin, 2012;Rees, 2007;Rees, Pond, Tinline, & Ball, 2004;Rees et al, 2013). We created two model landscapes.…”