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. 2010 Dec 23;5(12):e15626.
doi: 10.1371/journal.pone.0015626.

Uncertainty in the tail of the variant Creutzfeldt-Jakob disease epidemic in the UK

Tini Garske  1 , Azra C Ghani
Affiliations

Uncertainty in the tail of the variant Creutzfeldt-Jakob disease epidemic in the UK

Tini Garske et al. PLoS One. .

Abstract

Despite low case numbers the variant Creutzfeldt-Jakob disease epidemic poses many challenges for public health planning due to remaining uncertainties in disease biology and transmission routes. We develop a stochastic model for variant CJD transmission, taking into account the known transmission routes (food and red-cell transfusion) to assess the remaining uncertainty in the epidemic. We use Bayesian methods to obtain scenarios consistent with current data. Our results show a potentially long but uncertain tail in the epidemic, with a peak annual incidence of around 11 cases, but the 95% credibility interval between 1 and 65 cases. These cases are predicted to be due to past food-borne transmissions occurring in previously mostly unaffected genotypes and to transmissions via blood transfusion in all genotypes. However, we also show that the latter are unlikely to be identifiable as transfusion-associated cases by case-linking. Regardless of the numbers of future cases, even in the absence of any further control measures, we do not find any self-sustaining epidemics.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Input data.
A Time series of observed cases by genotype and presumed transmission route, B time-dependence of the exposure of the British population to the BSE agent, C age-dependent annual blood donation rates, D age-distribution of red cell use, E Age-dependent survival probability, F age-dependent excess mortality associated with red cell transfusions.
Figure 2
Figure 2. Flowchart of the model.
The population is stratified by age (a) and genotype (g). S =  susceptible, E1/2 =  exposed via primary/secondary infection, I1/2,pre =  preclinically infectious for primary/secondary infection, I1/2, sub =  subclinically infectious for primary/secondary infection, D1 =  death from primary vCJD disease, Dnatural =  death from other causes than vCJD, D2,id. =  death from identifiable transfusion associated vCJD disease, D2,unid =  death from transfusion transmitted vCJD disease, but transmission route unidentifiable, ω1 =  proportion of subclinical infection for primary transmission, ω2 =  proportion of subclinical infection for transfusion associated transmission.
Figure 3
Figure 3. Posterior distribution of simulated case numbers to the end of 2009.
A all cases, B identifiable blood cases, C unidentifiable blood cases, D MM cases, E MV cases, F VV cases.
Figure 4
Figure 4. Posterior distribution of the prevalence of detectable PrPSc by batch as defined in the survey .
A 1941–1960 cohort, B 1961–1985 cohort, C 1986–1990 cohort. The vertical dotted lines indicate exact binomial confidence intervals for the prevalence based on the number of samples tested and the number of positives. For A and C, the upper end of the confidence interval lies to the right of the scale due to the smaller number of samples in these batches.
Figure 5
Figure 5. Joint posterior density of relative susceptibility and total number of cases with mean incubation period.
A and B: relative susceptibility vs mean incubation period, C and D: total number of cases vs mean incubation period. A and C for MV genotypes, B and D for VV genotypes. Dark  =  high density, light  =  low density.
Figure 6
Figure 6. Median and posterior distributions of projected time series.
A Total number of cases, B transfusion associated cases that can be identified through donor-recipient pairing, C unidentifiable transfusion associated cases and D to F number of cases in the different genotypes, MM, MV and VV, respectively. Diamonds  =  observed epidemic, solid line  =  median, greyscale graduations: 10% range to 90% range.
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References

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