Description
mice (10day old, day1-21) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 10 10
2.5 0 10 10
25 0 16 16
25 0 16 16
250 0 15 15
250 0 15 15
2500 0 13 13
2500 2 11 13
25000 12 4 16
25000 13 3 16
250000 14 3 17
250000 14 3 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

48.6 

36.3 11 3.84 
 1.65e-09
19.7
1.09e-06
Beta Poisson

12.3

10 18.3 
0.265
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 6.01E-01 3.11E-01 3.69E-01 3.97E-01 1.04E+00 1.20E+00 2.01E+00
N50 1.48E+04 8.01E+03 9.07E+03 1.00E+04 2.29E+04 2.55E+04 2.83E+04

 

 

 

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

beta Poisson model plot, with confidence bounds around optimized model

# of Doses
12.00
Μodel
N50
1.48E+04
LD50/ID50
1.48E+04
Dose Units
Response
Exposure Route
Contains Preferred Model
a
6.01E-01
Agent Strain
ATCC 19660
Experiment ID
283,284
Description
mice (10day old, day2-21) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 10 10
25 0 16 16
250 0 15 15
2500 2 11 13
25000 13 3 16
250000 14 3 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

27.3

23.1 5 3.84 
 1.54e-06
11.1
5.01e-05
Beta Poisson

4.19

4 9.49 
0.381
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 5.49E-01 2.38E-01 2.87E-01 3.17E-01 1.37E+00 1.13E+01 1.15E+04
N50 1.13E+04 4.53E+03 5.70E+03 6.34E+03 2.17E+04 2.46E+04 3.39E+04

 

 

 

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

beta Poisson model plot, with confidence bounds around optimized model

# of Doses
6.00
Μodel
N50
1.13E+04
LD50/ID50
1.13E+04
Dose Units
Exposure Route
Contains Preferred Model
a
5.49E-01
Agent Strain
ATCC 19660
Experiment ID
284
Description
mice (10day old, day1) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 10 10
25 0 16 16
250 0 15 15
2500 0 13 13
25000 12 4 16
250000 14 3 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

21.1

13.8 5 3.84 
0.000207
11.1 
0.000783
Beta Poisson

7.32

4 9.49 
0.12
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 6.73E-01 3.02E-01 3.62E-01 3.80E-01 1.55E+00 6.30E+03 1.06E+04
N50 1.93E+04 9.62E+03 1.12E+04 1.18E+04 3.42E+04 4.01E+04 5.18E+04

 

 

 

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

beta Poisson model plot, with confidence bounds around optimized model

# of Doses
6.00
Μodel
N50
1.93E+04
LD50/ID50
1.93E+04
Dose Units
Exposure Route
Contains Preferred Model
a
6.73E-01
Agent Strain
ATCC 19660
Experiment ID
283
Description
mice (5day old) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 13 13
25 0 14 14
250 0 12 12
2500 4 13 17
25000 15 0 15
250000 17 0 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

2.17

-0.000196 

5 3.84 
1
11.1 
0.825
Beta Poisson

2.17

4 9.49 
0.704
Exponential is preferred to beta-Poisson; cannot reject good fit for exponential.

 

Optimized k parameter for the exponential model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
k 1.39E-04 8.87E-05 9.90E-05 9.90E-05 2.05E-04 2.36E-04 2.73E-04
ID50/LD50/ETC* 4.98E+03 2.54E+03 2.94E+03 3.38E+03 7.00E+03 7.00E+03 7.82E+03
*Not a parameter of the exponential model; however, it facilitates comparison with other models.

 

Parameter histogram for exponential model (uncertainty of the parameter)

Exponential model plot, with confidence bounds around optimized model

# of Doses
6.00
Μodel
LD50/ID50
4.98E+03
Dose Units
Exposure Route
Contains Preferred Model
k
1.39E-04
Agent Strain
ATCC 19660
Experiment ID
282
Description
mice (5day old) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 13 13
25 0 14 14
250 0 12 12
2500 4 13 17
25000 13 2 15
250000 17 0 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

0.802

0.0885 5 3.84 
0.766
11.1 
0.977
Beta Poisson

0.713

4 9.49 
0.95
Exponential is preferred to beta-Poisson; cannot reject good fit for exponential.

 

Optimized k parameter for the exponential model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
k 8.52E-05 4.21E-05 4.99E-05 5.50E-05 1.53E-04 1.57E-04 2.05E-04
ID50/LD50/ETC* 8.13E+03 3.38E+03 4.40E+03 4.54E+03 1.26E+04 1.39E+04 1.65E+04
*Not a parameter of the exponential model; however, it facilitates comparison with other models.

 

Parameter histogram for exponential model (uncertainty of the parameter)

Exponential model plot, with confidence bounds around optimized model

# of Doses
6.00
Μodel
LD50/ID50
8.13E+03
Dose Units
Response
Exposure Route
Contains Preferred Model
k
8.52E-05
Agent Strain
ATCC 19660
Experiment ID
281
Description

mice (5day old, day 1-21 pooled) /  Pseudomonas aeruginosa 

Dose Dead Survived Total
2.5 0 13 13
2.5 0 13 13
25 0 14 14
25 0 14 14
250 0 12 12
250 0 12 12
2500 4 13 17
2500 4 13 17
25000 13 2 15
25000 15 0 15
250000 17 0 17
250000 17 0 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

4.36 

 -0.000549

  3.84 
1
19.7
0.958
Beta Poisson

4.36

10 18.3 
0.93
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 1.05E-04 6.84E-05 7.49E-05 7.84E-05 1.48E-04 1.57E-04 1.73E-04
ID50/LD50/ETC* 6.61E+03 4.01E+03 4.40E+03 4.68E+03 8.84E+03 9.26E+03 1.01E+04
*Not a parameter of the exponential model; however, it facilitates comparison with other models.

 

 

 

Parameter histogram for exponential model (uncertainty of the parameter)

Exponential model plot, with confidence bounds around optimized model

# of Doses
12.00
Μodel
LD50/ID50
6.61E+03
Dose Units
Response
Exposure Route
Contains Preferred Model
k
1.05E-04
Agent Strain
ATCC 19660
Experiment ID
281,282 (pooled)

Pseudomonas aeruginosa (bacterimia): Dose Response Models

General Overview

Pseudomonas aeruginosa causes bacteremia primarily in immunocompromised and immunosupressed patients. Hematologic malignancies, immunodeficiency relating to AIDS, diabetes mellitus, and severe burns are some of the preexisting conditions (Todar 2012) .

ID Exposure Route # of Doses Agent Strain Dose Units Host type Μodel LD50/ID50 Optimized parameters Response type Reference
281 injected in eyelids 6.00 ATCC 19660 CFU Swiss webster mice (5day old) exponential 8.13E+03 k = 8.52E-05 death
Hazlett, L. D., Rosen, D. D., & Berk, R. S. (1978). Age-Related Susceptibility to Pseudomonas aeruginosa Ocular Infections in Mice. Infection and Immunity, 20, 1.
281,282 (pooled) injected in eyelids 12.00 ATCC 19660 CFU Swiss webster mice (5day old) exponential 6.61E+03 k = 1.05E-04 death
Hazlett, L. D., Rosen, D. D., & Berk, R. S. (1978). Age-Related Susceptibility to Pseudomonas aeruginosa Ocular Infections in Mice. Infection and Immunity, 20, 1.
282 injected in eyelids 6.00 ATCC 19660 CFU Swiss webster mice (5day old) exponential 4.98E+03 k = 1.39E-04 death(after day 21)
Hazlett, L. D., Rosen, D. D., & Berk, R. S. (1978). Age-Related Susceptibility to Pseudomonas aeruginosa Ocular Infections in Mice. Infection and Immunity, 20, 1.
283 injected in eyelids 6.00 ATCC 19660 CFU Swiss webster mice(10day old) beta-Poisson 1.93E+04 a = 6.73E-01 N50 = 1.93E+04 death(after day 1)
Hazlett, L. D., Rosen, D. D., & Berk, R. S. (1978). Age-Related Susceptibility to Pseudomonas aeruginosa Ocular Infections in Mice. Infection and Immunity, 20, 1.
283,284 injected in eyelids 12.00 ATCC 19660 CFU Swiss webster mice(10day old) beta-Poisson 1.48E+04 a = 6.01E-01 N50 = 1.48E+04 death
Hazlett, L. D., Rosen, D. D., & Berk, R. S. (1978). Age-Related Susceptibility to Pseudomonas aeruginosa Ocular Infections in Mice. Infection and Immunity, 20, 1.
284 injected in eyelids 6.00 ATCC 19660 CFU Swiss webster mice(10day old) beta-Poisson 1.13E+04 a = 5.49E-01 N50 = 1.13E+04 death(after day 2-21)
Hazlett, L. D., Rosen, D. D., & Berk, R. S. (1978). Age-Related Susceptibility to Pseudomonas aeruginosa Ocular Infections in Mice. Infection and Immunity, 20, 1.
Exposure Route:
injected in eyelids
# of Doses:
6.00
Agent Strain:
ATCC 19660
Dose Units:
CFU
Host type:
Swiss webster mice (5day old)
Μodel:
exponential
LD50/ID50:
8.13E+03
Optimized parameters: k = 8.52E-05
Response type:
death

mice (5day old) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 13 13
25 0 14 14
250 0 12 12
2500 4 13 17
25000 13 2 15
250000 17 0 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

0.802

0.0885 5 3.84 
0.766
11.1 
0.977
Beta Poisson

0.713

4 9.49 
0.95
Exponential is preferred to beta-Poisson; cannot reject good fit for exponential.

 

Optimized k parameter for the exponential model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
k 8.52E-05 4.21E-05 4.99E-05 5.50E-05 1.53E-04 1.57E-04 2.05E-04
ID50/LD50/ETC* 8.13E+03 3.38E+03 4.40E+03 4.54E+03 1.26E+04 1.39E+04 1.65E+04
*Not a parameter of the exponential model; however, it facilitates comparison with other models.

 

Parameter histogram for exponential model (uncertainty of the parameter)

Exponential model plot, with confidence bounds around optimized model

Highest quality
Exposure Route:
injected in eyelids
# of Doses:
12.00
Agent Strain:
ATCC 19660
Dose Units:
CFU
Host type:
Swiss webster mice (5day old)
Μodel:
exponential
LD50/ID50:
6.61E+03
Optimized parameters: k = 1.05E-04
Response type:
death

mice (5day old, day 1-21 pooled) /  Pseudomonas aeruginosa 

Dose Dead Survived Total
2.5 0 13 13
2.5 0 13 13
25 0 14 14
25 0 14 14
250 0 12 12
250 0 12 12
2500 4 13 17
2500 4 13 17
25000 13 2 15
25000 15 0 15
250000 17 0 17
250000 17 0 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

4.36 

 -0.000549

  3.84 
1
19.7
0.958
Beta Poisson

4.36

10 18.3 
0.93
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 1.05E-04 6.84E-05 7.49E-05 7.84E-05 1.48E-04 1.57E-04 1.73E-04
ID50/LD50/ETC* 6.61E+03 4.01E+03 4.40E+03 4.68E+03 8.84E+03 9.26E+03 1.01E+04
*Not a parameter of the exponential model; however, it facilitates comparison with other models.

 

 

 

Parameter histogram for exponential model (uncertainty of the parameter)

Exponential model plot, with confidence bounds around optimized model

Exposure Route:
injected in eyelids
# of Doses:
6.00
Agent Strain:
ATCC 19660
Dose Units:
CFU
Host type:
Swiss webster mice (5day old)
Μodel:
exponential
LD50/ID50:
4.98E+03
Optimized parameters: k = 1.39E-04
Response type:
death(after day 21)

mice (5day old) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 13 13
25 0 14 14
250 0 12 12
2500 4 13 17
25000 15 0 15
250000 17 0 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

2.17

-0.000196 

5 3.84 
1
11.1 
0.825
Beta Poisson

2.17

4 9.49 
0.704
Exponential is preferred to beta-Poisson; cannot reject good fit for exponential.

 

Optimized k parameter for the exponential model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
k 1.39E-04 8.87E-05 9.90E-05 9.90E-05 2.05E-04 2.36E-04 2.73E-04
ID50/LD50/ETC* 4.98E+03 2.54E+03 2.94E+03 3.38E+03 7.00E+03 7.00E+03 7.82E+03
*Not a parameter of the exponential model; however, it facilitates comparison with other models.

 

Parameter histogram for exponential model (uncertainty of the parameter)

Exponential model plot, with confidence bounds around optimized model

Exposure Route:
injected in eyelids
# of Doses:
6.00
Agent Strain:
ATCC 19660
Dose Units:
CFU
Host type:
Swiss webster mice(10day old)
Μodel:
beta-Poisson
LD50/ID50:
1.93E+04
Optimized parameters: a = 6.73E-01 N50 = 1.93E+04
Response type:
death(after day 1)

mice (10day old, day1) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 10 10
25 0 16 16
250 0 15 15
2500 0 13 13
25000 12 4 16
250000 14 3 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

21.1

13.8 5 3.84 
0.000207
11.1 
0.000783
Beta Poisson

7.32

4 9.49 
0.12
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 6.73E-01 3.02E-01 3.62E-01 3.80E-01 1.55E+00 6.30E+03 1.06E+04
N50 1.93E+04 9.62E+03 1.12E+04 1.18E+04 3.42E+04 4.01E+04 5.18E+04

 

 

 

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

beta Poisson model plot, with confidence bounds around optimized model

Exposure Route:
injected in eyelids
# of Doses:
12.00
Agent Strain:
ATCC 19660
Dose Units:
CFU
Host type:
Swiss webster mice(10day old)
Μodel:
beta-Poisson
LD50/ID50:
1.48E+04
Optimized parameters: a = 6.01E-01 N50 = 1.48E+04
Response type:
death

mice (10day old, day1-21) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 10 10
2.5 0 10 10
25 0 16 16
25 0 16 16
250 0 15 15
250 0 15 15
2500 0 13 13
2500 2 11 13
25000 12 4 16
25000 13 3 16
250000 14 3 17
250000 14 3 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

48.6 

36.3 11 3.84 
 1.65e-09
19.7
1.09e-06
Beta Poisson

12.3

10 18.3 
0.265
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 6.01E-01 3.11E-01 3.69E-01 3.97E-01 1.04E+00 1.20E+00 2.01E+00
N50 1.48E+04 8.01E+03 9.07E+03 1.00E+04 2.29E+04 2.55E+04 2.83E+04

 

 

 

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

beta Poisson model plot, with confidence bounds around optimized model

Exposure Route:
injected in eyelids
# of Doses:
6.00
Agent Strain:
ATCC 19660
Dose Units:
CFU
Host type:
Swiss webster mice(10day old)
Μodel:
beta-Poisson
LD50/ID50:
1.13E+04
Optimized parameters: a = 5.49E-01 N50 = 1.13E+04
Response type:
death(after day 2-21)

mice (10day old, day2-21) /  Pseudomonas aeruginosa 
Dose Dead Survived Total
2.5 0 10 10
25 0 16 16
250 0 15 15
2500 2 11 13
25000 13 3 16
250000 14 3 17

 

Goodness of fit and model selection
Model Deviance Δ Degrees 
of freedom
χ20.95,1 
p-value
χ20.95,m-k 
p-value
Exponential

27.3

23.1 5 3.84 
 1.54e-06
11.1
5.01e-05
Beta Poisson

4.19

4 9.49 
0.381
Beta-Poisson fits better than exponential; cannot reject good fit for beta-Poisson.

 

Optimized parameters for the beta-Poisson model, from 10000 bootstrap iterations
Parameter MLE estimate Percentiles
0.5% 2.5% 5% 95% 97.5% 99.5%
α 5.49E-01 2.38E-01 2.87E-01 3.17E-01 1.37E+00 1.13E+01 1.15E+04
N50 1.13E+04 4.53E+03 5.70E+03 6.34E+03 2.17E+04 2.46E+04 3.39E+04

 

 

 

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

beta Poisson model plot, with confidence bounds around optimized model