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| | Crump, J.A. & Mintz, E.D., 2010. Global trends in typhoid and paratyphoid Fever. ''Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America'', 50(2), pp.241-246. [http://cid.oxfordjournals.org/content/50/2/241.full.pdf+html Full text] <br /> | | Crump, J.A. & Mintz, E.D., 2010. Global trends in typhoid and paratyphoid Fever. ''Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America'', 50(2), pp.241-246. [http://cid.oxfordjournals.org/content/50/2/241.full.pdf+html Full text] <br /> |
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| − | Hornick, R.B. et al., 1970. Typhoid fever: pathogenesis and immunologic control. ''The New England Journal of Medicine'', 283(13), pp.686-691. [http://www.nejm.org/doi/pdf/10.1056/NEJM197010012831406 Abstract]
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| − | Hornick, R.B. et al., 1966. Study of induced typhoid fever in man. I. Evaluation of vaccine effectiveness. ''Transactions of the Association of American Physicians'', 79, pp.361-367.
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| | [[Category:Completed Dose Response Models: Bacteria]][[Category:Dose Response Model]][[Category:Salmonella (Typhi)]] | | [[Category:Completed Dose Response Models: Bacteria]][[Category:Dose Response Model]][[Category:Salmonella (Typhi)]] |
Revision as of 19:42, 23 August 2012
Typhoid Salmonella
Kyle S. Enger, MPH
Overview
Salmonella enterica, serovar Typhi (S. Typhi for short, but formerly known as Salmonella typhi or Salmonella typhosa) causes typhoid fever (Crump and Mintz 2010). Paratyphoid fever is a similar syndrome (but less common and less severe than typhoid fever) caused by Salmonella enterica, serovar Typhi (S. Paratyphi) (Miliotis and Bier 2003). Typhoid and paratyphoid fevers are also jointly known as enteric fever (Crump and Mintz 2010). Other Salmonella enterica serovars (e.g., Enteritidis, Typhimurium) cause a gastroenteritis known as salmonellosis (Miliotis and Bier 2003).
S. Typhi and S. Paratyphi only infect humans and are transmitted by the fecal-oral route (Miliotis and Bier 2003). Disease may include any combination of the following: cough, constipation, diarrhea, abdominal pain, anorexia, rose spots on the torso, or fever (Miliotis and Bier 2003). S. Typhi may also be shed asymptomatically for years in the feces of chronic carriers (Miliotis and Bier 2003).
Summary of data
There have been two feeding studies (Hornick et al. 1966, Hornick et al. 1970) in male prisoners of the Quailes strain of S. Typhi (which was named Salmonella typhosa at that time). Data from these two studies can be pooled (P > 0.05), and the beta-Poisson model is superior to the exponential model for all datasets. Although the pooled model fails the goodness-of-fit test, it does not fail by much (P = 0.032), and therefore it is the preferred model.
Other model fits to these data have been published (Haas, Rose, and Gerba 1999). However, these model fits exclude some of the experimental data for unclear reasons.
| Experiment serial number |
Reference |
Host type |
Agent strain |
Route |
# of doses |
Dose units |
Response |
Best fit model |
Optimized parameter(s) |
LD50/ID50
|
| 79, 80* |
[1][2] |
human |
Quailes |
oral, in milk |
8 |
CFU |
disease |
beta-Poisson |
α = 1.75E-01 , N50 = 1.11E+06 |
1.11E+06
|
| 79 |
[1] |
human |
Quailes |
oral, in milk |
3 |
CFU |
disease |
beta-Poisson |
α = 1.11E-01 , N50 = 3.45E+06 |
3.45E+06"
|
| 80 |
[2] |
human |
Quailes |
oral, in milk |
5 |
CFU |
disease |
beta-Poisson |
α = 2.03E-01 , N50 = 8.53E+05 |
8.53E+05
|
| *This model is preferred in most circumstances. However, consider all available models to decide which one is most appropriate for your analysis.
|
|
Optimization Output for experiment 79, 80
Model data for S. Typhi (Quailes) in humans [1][2]
| Dose |
Disease |
No disease |
Total
|
| 1000 |
0 |
14 |
14
|
| 1E+05 |
28 |
76 |
104
|
| 1E+05 |
32 |
84 |
116
|
| 1E+07 |
15 |
15 |
30
|
| 1E+07 |
16 |
16 |
32
|
| 1E+08 |
8 |
1 |
9
|
| 1E+09 |
4 |
0 |
4
|
| 1E+09 |
40 |
2 |
42
|
|
Goodness of fit and model selection
| Model |
Deviance |
Δ |
Degrees
of freedom |
χ20.95,1
p-value |
χ20.95,m-k
p-value
|
| Exponential
|
419
|
406
|
7
|
3.84
0
|
14.1
0
|
| Beta Poisson
|
13.8
|
6
|
12.6
0.0321
|
| Neither the exponential nor beta-Poisson fits well; beta-Poisson is less bad.
|
|
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
|
1.75E-01
|
1.21E-01 |
1.32E-01 |
1.39E-01 |
2.23E-01 |
2.34E-01 |
2.58E-01
|
| N50
|
1.11E+06
|
5.13E+05 |
6.10E+05 |
6.72E+05 |
2.00E+06 |
2.28E+06 |
2.95E+06
|
|
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
Optimization Output for experiment 79
Model data for S. Typhi (Quailes) in humans [1]
| Dose |
Disease |
No disease |
Total
|
| 1E+05 |
28 |
76 |
104
|
| 1E+07 |
15 |
15 |
30
|
| 1E+09 |
4 |
0 |
4
|
|
Goodness of fit and model selection
| Model |
Deviance |
Δ |
Degrees
of freedom |
χ20.95,1
p-value |
χ20.95,m-k
p-value
|
| Exponential
|
124
|
121
|
2
|
3.84
0
|
5.99
0
|
| Beta Poisson
|
2.87
|
1
|
3.84
0.0905
|
| 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
|
1.11E-01
|
3.19E-02 |
4.80E-02 |
5.49E-02 |
1.96E-01 |
2.17E-01 |
2.59E-01
|
| N50
|
3.45E+06
|
4.81E+05 |
6.95E+05 |
8.50E+05 |
9.53E+07 |
2.24E+08 |
4.19E+09
|
|
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
Optimization Output for experiment 80
Model data for S. Typhi (Quailes) in humans [2]
| Dose |
Disease |
No disease |
Total
|
| 1000 |
0 |
14 |
14
|
| 1E+05 |
32 |
84 |
116
|
| 1E+07 |
16 |
16 |
32
|
| 1E+08 |
8 |
1 |
9
|
| 1E+09 |
40 |
2 |
42
|
|
Goodness of fit and model selection
| Model |
Deviance |
Δ |
Degrees
of freedom |
χ20.95,1
p-value |
χ20.95,m-k
p-value
|
| Exponential
|
293
|
284
|
4
|
3.84
0
|
9.49
0
|
| Beta Poisson
|
8.63
|
3
|
7.81
0.0346
|
| Neither the exponential nor beta-Poisson fits well; beta-Poisson is less bad.
|
|
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
|
2.03E-01
|
1.33E-01 |
1.49E-01 |
1.57E-01 |
2.74E-01 |
2.89E-01 |
3.27E-01
|
| N50
|
8.53E+05
|
3.38E+05 |
4.28E+05 |
4.80E+05 |
1.62E+06 |
1.85E+06 |
2.49E+06
|
|
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
References
- ↑ 1.0 1.1 1.2 1.3 Hornick, R.B. et al., 1966. Study of induced typhoid fever in man. I. Evaluation of vaccine effectiveness. Transactions of the Association of American Physicians, 79, pp.361-367.
- ↑ 2.0 2.1 2.2 2.3 Hornick, R.B. et al., 1970. Typhoid fever: pathogenesis and immunologic control. The New England Journal of Medicine, 283(13), pp.686-691. Abstract
Miliotis, M.D. & Bier, J. eds., 2003. International Handbook of Foodborne Pathogens, New York: M. Dekker.
Crump, J.A. & Mintz, E.D., 2010. Global trends in typhoid and paratyphoid Fever. Clinical Infectious Diseases: An Official Publication of the Infectious Diseases Society of America, 50(2), pp.241-246. Full text
