Rhinovirus
Author: Yin Huang
General overview
Rhinovirus, a small icosahedral viruses made of a protein capsid that encases a single-stranded, positive-sense RNA molecule, belongs to the Picornaviridae family. About 100 different serotypes have been identified and characterized by their own specific antigens.
Rhinoviruses are responsible for 30 to 50% of adult colds and 10 to 25% of colds in children. Other cold-causing viruses are adenoviruses, coronaviruses, coxsackieviruses, echoviruses, orthomyxoviruses, paramyxoviruses, respiratory syncytial virus, and enteroviruses, each of which produces infections with slightly different patterns of symptoms and severity. Several of the above-mentioned viruses also account for other more severe illnesses (Bella and Rossmann 1999).
Summary Data
Hendley et al. (1972) inoculated young adult human volunteers over the age of 21 with Rhinovirus type 39 (RV 39), strain SF 299, and rhinovirus type 14 (RV 14), strain SF 765, via intranasal exposure route. Shedding of the challenge virus and/or a fourfold or greater increase in titer of serum antibody to a homotypic rhinovirus were accepted as evidence of infection.
Experiment serial number |
Reference |
Host type |
Agent strain |
Route |
# of doses |
Dose units |
Response |
Best fit model |
Optimized parameter(s) |
LD50/ID50
|
65* |
[1] |
human |
type 39 |
intranasal |
6 |
TCID50 doses |
infection |
beta-Poisson |
α = 2.21E-01 , N50 = 1.81E+00 |
1.81E+00
|
64 |
[1] |
human |
type 14 |
intranasal |
6 |
TCID50 doses |
infection |
beta-Poisson |
α = 2.01E-01 , N50 = 9.22E+00 |
9.22E+00
|
310 |
[1] |
human |
type 14 |
intranasal |
6 |
TCID50 doses |
infection |
beta-Poisson |
α = 2.52E-01 , N50 = 3.83E+00 |
3.83E+00
|
311 |
[1] |
human |
type 39 |
intranasal |
6 |
TCID50 doses |
infection |
beta-Poisson |
α = 7.01E-01 , N50 = 1.9E-01 |
1.9E-01
|
312 |
[1] |
human |
type 14 |
intranasal |
6 |
TCID50 doses |
infection |
beta-Poisson |
α = 1.81E-01 , N50 = 2.22E+01 |
2.22E+01
|
313 |
[1] |
human |
type 39 |
intranasal |
6 |
TCID50 doses |
infection |
beta-Poisson |
α = 2E-01 , N50 = 1.05E+01 |
1.05E+01
|
312, 313 |
[1] |
human |
type 14 |
intranasal |
12 |
TCID50 doses |
infection |
beta-Poisson |
α = 1.82E-01 , N50 = 1.38E+01 |
1.38E+01
|
*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 65
human/type 39 strain SF 299 model data [1]
Dose |
Infected |
Non-infected |
Total
|
0.05 |
0 |
11 |
11
|
0.15 |
2 |
7 |
9
|
0.5 |
8 |
16 |
24
|
5 |
5 |
11 |
16
|
50 |
47 |
15 |
62
|
|
Goodness of fit and model selection
Model |
Deviance |
Δ |
Degrees of freedom |
χ20.95,1 p-value |
χ20.95,m-k p-value
|
Exponential
|
50.3
|
44.3
|
4
|
3.84 2.76e-11
|
9.49 3.06e-10
|
Beta Poisson
|
6.01
|
3
|
7.81 0.111
|
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
|
2.24E-01
|
9.88E-04 |
1.40E-01 |
1.53E-01 |
3.71E-01 |
4.27E-01 |
7.63E-01
|
N50
|
3.29E+00
|
1.90E-02 |
1.34E+00 |
1.59E+00 |
7.67E+00 |
9.27E+00 |
1.59E+01
|
|
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 64
human/type 14 strain SF 765model data [1]
Dose |
Infected |
Non-infected |
Total
|
0.5 |
1 |
8 |
9
|
1.5 |
4 |
6 |
10
|
5 |
4 |
6 |
10
|
15 |
6 |
4 |
10
|
150 |
27 |
13 |
40
|
300 |
10 |
2 |
12
|
|
Goodness of fit and model selection
Model |
Deviance |
Δ |
Degrees of freedom |
χ20.95,1 p-value |
χ20.95,m-k p-value
|
Exponential
|
51.8
|
50.2
|
5
|
3.84 1.42e-12
|
11.1 5.8e-10
|
Beta Poisson
|
1.68
|
4
|
9.49 0.794
|
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
|
2.01E-01
|
7.76E-02 |
1.07E-01 |
1.22E-01 |
3.36E-01 |
3.69E-01 |
4.61E-01
|
N50
|
9.22E+00
|
1.41E+00 |
2.57E+00 |
3.40E+00 |
2.47E+01 |
3.14E+01 |
5.26E+01
|
|
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 310
TITLE [1]
Dose |
INFECTION |
NOT
INFECTION || Total
|
0.5 |
1 |
4 |
5
|
1.5 |
2 |
3 |
5
|
5 |
3 |
2 |
5
|
15 |
2 |
1 |
3
|
150 |
14 |
5 |
19
|
300 |
5 |
0 |
5
|
|
Goodness of fit and model
selection
Model |
Deviance |
Δ |
Degrees of freedom |
χ20.95,1 p-value |
χ20.95,m-k p-value
|
Exponential
|
29.7
|
27.3
|
5
|
3.84 {{{pbPbetter}}}
|
11.1 1.71e-05
|
Beta Poisson
|
2.42
|
4
|
9.49 0
selection
|
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
|
2.52E-01
|
9.79E-04 |
9.14E-02 |
1.16E-01 |
5.50E-01 |
6.41E-01 |
1.06E+00
|
N50
|
3.83E+00
|
9.08E-03 |
3.23E-01 |
6.41E-01 |
1.48E+01 |
2.04E+01 |
8.86E+01
|
|
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 311
TITLE [1]
Dose |
INFECTION |
NOT
INFECTION || Total
|
0.05 |
0 |
2 |
2
|
0.15 |
1 |
3 |
4
|
0.5 |
5 |
2 |
7
|
1.5 |
18 |
1 |
19
|
5 |
1 |
0 |
1
|
50 |
19 |
1 |
20
|
|
Goodness of fit and model
selection
Model |
Deviance |
Δ |
Degrees of freedom |
χ20.95,1 p-value |
χ20.95,m-k p-value
|
Exponential
|
61.7
|
56.8
|
5
|
3.84 {{{pbPbetter}}}
|
11.1 5.32e-12
|
Beta Poisson
|
4.95
|
4
|
9.49 0
selection
|
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
|
7.01E-01
|
2.29E-01 |
3.14E-01 |
3.63E-01 |
1.81E+06 |
3.82E+06 |
1.41E+07
|
N50
|
1.9E-01
|
2.27E-02 |
5.85E-02 |
7.93E-02 |
4.20E-01 |
4.52E-01 |
5.56E-01
|
|
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 312
TITLE [1]
Dose |
INFECTION |
NOT
INFECTION || Total
|
0.5 |
0 |
4 |
4
|
1.5 |
2 |
3 |
5
|
5 |
1 |
4 |
5
|
15 |
4 |
3 |
7
|
150 |
13 |
8 |
21
|
300 |
5 |
2 |
7
|
|
Goodness of fit and model
selection
Model |
Deviance |
Δ |
Degrees of freedom |
χ20.95,1 p-value |
χ20.95,m-k p-value
|
Exponential
|
24.3
|
21.5
|
5
|
3.84 {{{pbPbetter}}}
|
11.1 0.000194
|
Beta Poisson
|
2.77
|
4
|
9.49 0
selection
|
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
|
1.81E-01
|
3.92E-02 |
7.30E-02 |
9.02E-02 |
4.00E-01 |
4.79E-01 |
7.28E-01
|
N50
|
2.22E+01
|
3.12E+00 |
5.01E+00 |
6.38E+00 |
1.22E+02 |
2.06E+02 |
1.26E+03
|
|
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 313
TITLE [1]
Dose |
INFECTION |
NOT
INFECTION || Total
|
0.05 |
0 |
4 |
4
|
0.15 |
1 |
4 |
5
|
0.5 |
3 |
14 |
17
|
1.5 |
4 |
10 |
14
|
5 |
4 |
11 |
15
|
50 |
28 |
14 |
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
|
29.2
|
26.2
|
5
|
3.84 {{{pbPbetter}}}
|
11.1 2.16e-05
|
Beta Poisson
|
2.93
|
4
|
9.49 0
selection
|
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
|
2E-01
|
7.86E-02 |
9.79E-02 |
1.11E-01 |
4.65E-01 |
5.58E-01 |
8.66E-01
|
N50
|
1.05E+01
|
3.00E+00 |
3.98E+00 |
4.65E+00 |
3.67E+01 |
5.32E+01 |
1.22E+02
|
|
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 pooled experiments of 312&313
TITLE [1]
Dose |
INFECTION |
NOT
INFECTION || Total
|
0.05 |
0 |
4 |
4
|
0.15 |
1 |
4 |
5
|
0.5 |
0 |
4 |
4
|
0.5 |
3 |
14 |
17
|
1.5 |
2 |
3 |
5
|
1.5 |
4 |
10 |
14
|
5 |
1 |
4 |
5
|
5 |
4 |
11 |
15
|
15 |
4 |
3 |
7
|
50 |
28 |
14 |
42
|
150 |
13 |
8 |
21
|
300 |
5 |
2 |
7
|
|
"
Goodness of fit and model
selection
Model |
Deviance |
Δ |
Degrees of freedom |
χ20.95,1 p-value |
χ20.95,m-k p-value
|
Exponential
|
78.6
|
72.3
|
11
|
3.84 {{{pbPbetter}}}
|
19.7 2.8e-12
|
Beta Poisson
|
6.22
|
10
|
18.3 0.796
|
{{{interpretation}}}
|
|
"
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
|
1.82E-01
|
1.04E-03 |
1.03E-01 |
1.14E-01 |
3.04E-01 |
3.38E-01 |
4.09E-01
|
N50
|
1.38E+01
|
2.98E+00 |
5.64E+00 |
6.67E+00 |
3.77E+01 |
4.98E+01 |
1.32E+02
|
|
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
Summary
The responses caused by doses less than one observed in these two experiments are probably due to the uncertainties of dose counting in the original study.
References
- ↑ 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 1.11 1.12 1.13 Hendley, J.O., Edmondson Jr., W.P. and Gwaltney Jr., J.M. (1972) Relation between naturally acquired immunity and infectivity of two rhinoviruses involunteers. Journal of Infectious Diseases 125, 243-248. Cite error: Invalid
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Bella, J. and Rossmann, M.G. (1999) Review: Rhinoviruses and their icam receptors. Journal of Structural Biology 128, 69–74.