Integrating between-host transmission and within-host immunity to analyze the impact of varicella vaccination on zoster
- University of Antwerp, Belgium
- Hasselt University, Belgium
- University of New South Wales, Australia
Figures
Figure 1
Observed (open circles) and simulated (continuous lines) Belgian herpes zoster (HZ) incidence data by age.
https://doi.org/10.7554/eLife.07116.004-
Figure 1—source data 1
Observed Belgian HZ incidence per age group and per person-year.
- https://doi.org/10.7554/eLife.07116.005
Figure 2 with 1 supplement
Observed (open circles) and simulated (continuous lines) Belgian HZ incidence data by age.
https://doi.org/10.7554/eLife.07116.006
Figure 2—figure supplement 1
Observed (open circles) Belgian HZ incidence data by age and simulated HZ incidence data (continuous lines) for the 13 best parameter sets with a sensitivity analysis for the HZ infectiousness parameter (values: 0.03, 0.10, 0.17, 0.24, 0.31, 0.38 and 0.45) and three runs per parameter set.
https://doi.org/10.7554/eLife.07116.007
Figure 3
Normalized varicella-zoster virus (VZV)-specific CMI averaged over 80 simulation years and over all individuals for the two best parameter sets.
Caption: note that this figure shows average dynamics although some individuals will have VZV-specific CMI values below 1 (making them susceptible to HZ).
Figure 4
Predicted HZ incidence (aggregated for all ages) over time with a CP vaccine for 1 year olds using the best-fitting parameter sets.
The red line indicates the moment of CP vaccine introduction, which is assumed to be 100% effective.
Figure 5
Time-evolution of the relative contribution to HZ incidence per age group before and after introduction of 100% effective varicella vaccination for 1 year olds.
https://doi.org/10.7554/eLife.07116.010
Figure 6
Simplified dynamics of VZV-CMI, VZV reactivation and boosting events as modeled.
The sequence of exogenous boosting and VZV reactivation can be switched.
Figure 7
VZV IBM demography.
https://doi.org/10.7554/eLife.07116.012
Figure 8
Three different boosting scenarios.
(A) Illustrates the exponential decline parameterized by a peak (+120%) at 6 weeks, (+60%) 1 year later, (50%) 2 years later and (+40%) 3 years later as presented by the Zostavax vaccine trial by Levin et al. (B) Illustrates the exponential decline from peak (+120%) to (+60%) 1 year later and constant for x years (as defined by the parameter set) after wards, as a modified interpretation of the results of the Zostavax vaccine trial by Levin et al. (C) Illustrates the increase to a peak value as defined by the parameter set that is followed by an exponential decline so that the pre-boosting value is reached after x years.
Figure 9
Different cumulative distribution functions (CDF) for Force of Reactivation (FoR).
https://doi.org/10.7554/eLife.07116.015Tables
Table 1
Best fitting parameter sets
| Parameter set | Deviance* | Annual waning rate (%) | Boosting scenario | Duration of boosting (years) | Peak fold increase following exogenous boosting | VZV weekly reactivation probability (%) | Distribution threshold VZV-CMI for HZ | Peak fold increase following endogenous boosting |
|---|---|---|---|---|---|---|---|---|
| Original Search (obtained after Step 2 in Table 1) | ||||||||
| 1 | 926 | 2.0 | 3 | 10 | 1.3 | 1.5 | 4 | 1 |
| 2 | 939 | 1.5 | 3 | 3 | 1.3 | 1.5 | 4 | 1 |
| 3 | 949 | 2.0 | 3 | 7 | 1.3 | 1.5 | 4 | 1 |
| 4 | 951 | 2.0 | 3 | 12 | 1.3 | 1.5 | 4 | 1 |
| 5 | 968 | 2.0 | 3 | 7 | 1.3 | 1.0 | 4 | 1 |
| 6 | 970 | 1.0 | 3 | 2 | 1.3 | 1.0 | 4 | 1 |
| 7 | 969 | 2.0 | 3 | 15 | 1.3 | 1.5 | 4 | 1 |
| 8 | 934 | 1.0 | 3 | 1 | 2.5 | 5.0 | 4 | 1 |
| Border search | ||||||||
| 9 | 751 | 1.0 | 3 | 1 | 2.8 | 5.0 | 4 | 1 |
| 10 | 799 | 1.0 | 3 | 1 | 3.1 | 5.0 | 4 | 1 |
| 11 | 965 | 1.5 | 3 | 2 | 3.4 | 5.0 | 4 | 1 |
| 12 | 804 | 1.5 | 3 | 2 | 3.7 | 5.0 | 4 | 1 |
| 13 | 722 | 1.5 | 3 | 2 | 4.0 | 5.0 | 4 | 1 |
-
*
Results shown are averaged results per parameter set.
-
VZV, varicella-zoster virus; HZ, herpes zoster.
Table 2
Initial parameter sets
| Parameters | Step 1 | Step 2 |
|---|---|---|
| Annual waning rate (%) | 2.0 | 0.5 |
| 3.0 | 1.0 | |
| 4.0 | 1.5 | |
| – | 2.0 | |
| – | 2.5 | |
| Boosting scenario | 1 | 3 |
| 2 | – | |
| 3 | – | |
| Duration of boosting (years) | 1 | 1 |
| 2 | 2 | |
| 4 | 3 | |
| 7 | 4 | |
| 12 | 5 | |
| – | 7 | |
| – | 10 | |
| – | 12 | |
| – | 15 | |
| Peak fold increase following exogenous boosting | 1 | 1.3 |
| 1.6 | 1.6 | |
| 2.2 | 1.9 | |
| – | 2.2 | |
| – | 2.5 | |
| VZV weekly reactivation probability (%) | 0.01 | 0.001 |
| 0.1 | 0.05 | |
| 0.3 | 0.01 | |
| 0.5 | 0.015 | |
| – | 0.1 | |
| – | 0.2 | |
| – | 0.3 | |
| – | 0.4 | |
| Distribution threshold VZV-CMI for HZ | 1 | 1 |
| 2 | 2 | |
| 3 | 4 | |
| 4 | – | |
| Peak fold increase following endogenous boosting | 1 | 1 |
| 1.4 | 1.2 | |
| 1.8 | – | |
| 2.2 | – |
Table 3
Step 2 parameter set selection
| Parameters | Best parameter sets + deviance +5% | Most prevalent parameters in Q2.5 |
|---|---|---|
| Annual waning rate (%) | 2.0 | 2.0 |
| Boosting scenario | 3 | 3 |
| Duration of exogenous boosting (years) | 1 | 1 |
| 4 | 2 | |
| – | 4 | |
| – | 7 | |
| – | 12 | |
| Peak fold increase following exogenous boosting | 1.6 | 1.6 |
| – | 2.2 | |
| VZV weekly reactivation probability (%) | 0.01 | 0.01 |
| 0.1 | 0.3 | |
| Distribution threshold VZV-CMI for HZ | 2 | 1 |
| 4 | 2 | |
| Peak fold increase following endogenous boosting | 1 | 1 |
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Integrating between-host transmission and within-host immunity to analyze the impact of varicella vaccination on zoster
eLife 4:e07116.
https://doi.org/10.7554/eLife.07116
