You are here

Home / Framework / Dose Response / Completed Dose Response Models / Listeria monocytogenes (Death as response): Dose Response Models

General Overview

Listeria monocytogenes is a Gram-positive rod-shaped bacterium. It is the causative agent of listeriosis, a serious infection caused by eating food contaminated with the bacteria. The disease generally affects older adults, pregnant women, newborns, and adults with weakened immune systems. However, rarely, persons without these risk factors can also be affected, according to the CDC[1] and Todar[2].

The overt form of the disease has mortality greater than 25 percent. The two main clinical manifestations are sepsis and meningitis. Meningitis is often complicated by encephalitis, a pathology that is unusual for bacterial infections, according to Todar [2].

Summary Data

Czuprynski et al.[3] studied susceptibility of C57BL/6 mice and A/J mice to Listeria monocytogenes (strain Scott A) inoculating them intragastrically. Similarly, Golnazarian et al. [4] also compared infectious dose in normal and compromised C57BL/6J mice with pathogens( strain F5817) via oral route.

Experiment serial number Reference Host type Agent strain Route # of doses Dose units Response Best fit model Optimized parameter(s) LD50/ID50

 
291* Golnazarian et al. [4] C57B1/6J mice F5817 oral 6 CFU death exponential k = 1.15E-05 6.05E+04
293 Czuprynski et al.[3] A/J Mice Scott A intragastric 3 CFU death exponential k = 5.71E-07 1.21E+06
294 Czuprynski et al.[3] C57BL/6 Mice Scott A intragastric 3 CFU death beta-Poisson α = 2.71E-01 , N50 = 7.89E+07 7.89E+07
*This model is preferred in most circumstances. However, consider all available models to decide which one is most appropriate for your analysis.

Exponential and betapoisson model.jpg

Optimization Output for experiment 291

C57BL/6J mice/Listeria monocytogenes (Golnazarian et al. [4])
Dose DEATH NOT DEATH Total
5500 1 9 10
32400 2 8 10
55000 4 6 10
251000 10 0 10
550000 10 0 10
2820000 10 0 10

 

Goodness of fit and model selection
Model Deviance Δ Degrees
of freedom		 χ20.95,1
p-value		 χ20.95,m-k
p-value
Exponential 2.22 -0.000453 5 3.84
1		 11.1
0.818
Beta Poisson 2.22 4 9.49
0.695
Exponential is preferred to beta-Poisson; cannot reject good fit for exponential.

 

Optimized k parameter for the exponential model, from 500 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
k 1.15E-05 7.13E-06 7.83E-06 7.96E-06 1.71E-05 1.85E-05 2.07E-05
ID50/LD50/ETC* 6.05E+04 3.35E+04 3.75E+04 4.06E+04 8.71E+04 8.85E+04 9.73E+04
*Not a parameter of the exponential model; however, it facilitates comparison with other models.

 

ExpHisto_ID291.png

Parameter histogram for exponential model (uncertainty of the parameter)

ExpModel_ID291.png

Exponential model plot, with confidence bounds around optimized model

 

 

 

 

Optimization Output for experiment 293

A/J mice/Listeria monocytogenes (Czuprynski et al.[3])
Dose DEATH NOT DEATH Total
1E+05 1 5 6
1E+06 2 4 6
1E+07 6 0 6

 

Goodness of fit and model selection
Model Deviance Δ Degrees
of freedom		 χ20.95,1
p-value		 χ20.95,m-k
p-value
Exponential 1.25 -0.0018 2 3.84
1		 5.99
0.536
Beta Poisson 1.25 1 3.84
0.264
Exponential is preferred to beta-Poisson; cannot reject good fit for exponential.

 

Optimized k parameter for the exponential model, from 500 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
k 5.71E-07 2.31E-07 2.31E-07 2.98E-07 1.30E-06 1.49E-06 2.19E-06
ID50/LD50/ETC* 1.21E+06 3.17E+05 4.64E+05 5.35E+05 2.32E+06 3.00E+06 3.00E+06
*Not a parameter of the exponential model; however, it facilitates comparison with other models.

 

ExpHisto_ID293.png

Parameter histogram for exponential model (uncertainty of the parameter)

ExpModel_ID293.png

Exponential model plot, with confidence bounds around optimized model

 

 

Optimization Output for experiment 294

C57BL/6 mice/Listeria monocytogenes (Czuprynski et al.[3])
Dose DEATH NOT DEATH Total
1E+07 1 5 6
1E+08 4 2 6
1E+09 4 2 6

 

 

Goodness of fit and model selection
Model Deviance Δ Degrees
of freedom		 χ20.95,1
p-value		 χ20.95,m-k
p-value
Exponential 10.7 9.97 2 3.84
0.0016		 5.99
0.00471
Beta Poisson 0.752 1 3.84
0.386
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 500 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 2.71E-01 9.85E-04 9.98E-04 1.01E-03 1.46E+00 5.95E+01 2.41E+05
N50 7.89E+07 9.28E-03 2.42E+02 2.56E+03 7.18E+08 1.90E+09 1.99E+14

 

BPscatter_ID294.png

Parameter scatter plot for beta Poisson model ellipses signify the 0.9, 0.95 and 0.99 confidence of the parameters.

References

ID Exposure Route # of Doses Agent Strain Dose Units Host type Μodel LD50/ID50 Optimized parameters Response type Reference
292 oral 6 F5817 CFU beta-Poisson α = 0.253

N50 = 277
infection
Experiment ID:
292
# of Doses:
6
Agent Strain:
F5817
Dose Units:
CFU
Host type:
Μodel:
beta-Poisson
Optimized parameters: a = 0.253


N50 = 277
Reference:

 

Goodness of Fit and Model Selection
Model Deviance Δ Degrees 
of freedom		 χ20.95,1 
p-value		 χ20.95,m-k 
p-value
Exponential 9.88 6.48 5 3.84 
0.011		 11.1
0.0788
beta Poisson 3.4 4 9.49
0.494
beta-Poisson fits better than exponential; can not reject good fit for beta-Poisson

 

 

 

 

 

 

 

Bootstrapped Parameter Estimates
Parameter MLE Estimate 0.5% 2.5% 5% 95% 97.5% 99.5%

α

 6.95E-01 2.69E-01 3.39E-01 3.78E-01 2.56E+0 2.28E+01 1.18E+03
N50 3.39E+03 3.58E+01 2.47E+02 4.67E+02 1.09E+04 1.26E+04 1.85E+04