Selected article for: "outbreak number and small number"

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_28
    Snippet: Sensitivity analyses were conducted to examine the impact of underestimating the potential generation time for the PEDV outbreak in Ontario. Compared to our base case scenario with a generation time of seven days, increasing the possible generation time (to 10 and 13 days) aggregated the available data into fewer total epidemic generations for the period of time being investigated. As a result, best-fit model parameters for both R 0 and d were fo.....
    Document: Sensitivity analyses were conducted to examine the impact of underestimating the potential generation time for the PEDV outbreak in Ontario. Compared to our base case scenario with a generation time of seven days, increasing the possible generation time (to 10 and 13 days) aggregated the available data into fewer total epidemic generations for the period of time being investigated. As a result, best-fit model parameters for both R 0 and d were found to increase with increasing generation time (Table 1) representing more explosive epidemic growth but also most intensive intervention and control. However, changing our assumption about the possible generation time resulted in less accuracy when using a small number of epidemic generations to predict final outbreak size and timing (Fig. 5) . Using a generation time of 10 days, IDEA model projections of final outbreak size (48 cases) and timing (generation nine, May 21, 2014) when using only data from the first three epidemic generations, overestimated the epidemic by 11 cases and approximately 21 days (Fig. 5 ). In comparison, using a generation time of 13 days, projections of final outbreak size (29 cases) and timing (generation five, April 26, 2014) when only using data from the first three epidemic generations, underestimated the epidemic trajectory by 8 cases and 4 days (Fig. 5) . Suggesting that our initial estimate of 7 days provides the most predictive fit available using minimal, publically available data inputs.

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