Selected article for: "model parameter and parameter fit"
Author: Greer, Amy L.; Spence, Kelsey; Gardner, Emma
Title: Understanding the early dynamics of the 2014 porcine epidemic diarrhea virus (PEDV) outbreak in Ontario using the incidence decay and exponential adjustment (IDEA) model
  • Document date: 2017_1_5
    • ID: 1g2ij37f_13
    Snippet: Where, I t is the number of incident cases in each model generation, R 0 is the basic reproductive number, d is a control parameter that allows for the decay of disease incidence over time and t is scaled in terms of the generation time. In the absence of any disease control interventions, we would expect the disease to increase over time with cases growing to the power of t. However, when control measures or interventions are implemented in the .....
    Document: Where, I t is the number of incident cases in each model generation, R 0 is the basic reproductive number, d is a control parameter that allows for the decay of disease incidence over time and t is scaled in terms of the generation time. In the absence of any disease control interventions, we would expect the disease to increase over time with cases growing to the power of t. However, when control measures or interventions are implemented in the system, we expect that those controls act on the disease transmission parameter (R 0 ) by reducing it over time by a power of t 2. Best-fit model parameter values are obtained using maximum likelihood estimation (MLE) by fitting the model to the cumulative incidence data.

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