|MALLADI, SASIDHAR - University Of Minnesota|
|SSEMATIMBA, AMOS - University Of Minnesota|
|STEPEHNS, CHRIS - Orise Fellow|
Submitted to: Journal of Veterinary Diagnostic Investigation
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/10/2019
Publication Date: 7/1/2019
Publication URL: https://handle.nal.usda.gov/10113/6556978
Citation: Spackman, E., Malladi, S., Ssematimba, A., Stepehns, C. 2019. Assessment of replicate numbers for titrating avian influenza virus using dose-response models. Journal of Veterinary Diagnostic Investigation. 31(4):616-619. https://doi.org/10.1177/1040638719853851.
Interpretive Summary: Determining the quantity of avian influenza virus (AIV) in a sample requires the use of a large number of chicken eggs. Essentially the virus can grown in chicken eggs and by seeing how far it can be diluted and still be detected one can determine the concentration in a sample. For accuracy, several egg needs to be treated with each dilution; usually five eggs for each dilution and six dilutions are tested; so 30 eggs per sample. Because eggs are expensive and take a lot of room, we investigated whether using only 3 eggs would provide enough accuracy. Data from experiments quantifying AIV was applied to several statistical models to determine how using only 3 eggs would affect the accuracy of the test. It was found that there was a minor effect on accuracy and precision, but overall results with 3 eggs instead of 5 were valid. This will result in substantial monetary savings when AIV needs to be quantified because fewer eggs (18 instead of 30) need to be used.
Technical Abstract: Embryonating chicken eggs (ECEs) are among the most sensitive laboratory host systems for avian influenza virus (AIV) titration, but ECEs are expensive and require space for storage and incubation. Therefore, reducing ECE use would conserve resources. We utilized statistical modeling to evaluate the accuracy and precision of AIV titration with 3 instead of 5 ECEs for each dilution by the Reed–Muench method for 50% endpoint calculation. Beta-Poisson and exponential dose-response models were used in a simulation study to evaluate observations from actual titration data from 18 AIV isolates. The reproducibility among replicates of a titration was evaluated with one AIV isolate titrated in 3 replicates with the beta-Poisson, exponential, and Weibull dose-response models. The standard deviation (SD) of the error between input and estimated virus titers was estimated with Monte Carlo simulations using the fitted dose-response models. Good fit was observed with all models that were utilized. Reducing the number of ECEs per dilution from 5 to 3 resulted in the width of the 95% confidence interval increasing from ±0.64 to ±0.75 log10 50% ECE infectious doses (EID50) and the SD of the error increased by 0.03 log10 EID50. Our study suggests that using fewer ECEs per dilution is a viable approach that will allow laboratories to reduce costs and improve efficiency.