BACKGROUND: In Switzerland, SARS-CoV-2 vaccination campaigns started in early 2021. Vaccine coverage reached 65% of the population in December 2021, mostly with mRNA vaccines from Moderna and Pfizer-BioNtech. Simultaneously, the proportion of vaccinated among COVID-19-related hospitalisations and deaths rose, creating some confusion in the general population. We aimed to assess vaccine effectiveness against severe forms of SARS-CoV-2 infection using routine surveillance data on the vaccination status of COVID-19-related hospitalisations and deaths, and data on vaccine coverage in Switzerland. METHODS: We considered all routine surveillance data on COVID-19-related hospitalisations and deaths received at the Swiss Federal Office of Public Health from 1 July to 1 December 2021. We estimated the relative risk of COVID-19-related hospitalisation or death for not fully vaccinated compared with fully vaccinated individuals, adjusted for the dynamics of vaccine coverage over time, by age and location. We stratified the analysis by age group and by calendar month. We assessed variations in the relative risk of hospitalisation associated with the time since vaccination. RESULTS: We included a total of 5948 COVID-19-related hospitalisations of which 1245 (21%) were fully vaccinated patients, and a total of 739 deaths of which 259 (35%) were fully vaccinated. We found that the relative risk of COVID-19 related hospitalisation was 12.5 (95% confidence interval [CI] 11.7–13.4) times higher for not fully vaccinated than for fully vaccinated individuals. This translates into a vaccine effectiveness against hospitalisation of 92.0% (95% CI 91.4–92.5%). Vaccine effectiveness against death was estimated to be 90.3% (95% CI 88.6–91.8%). Effectiveness appeared to be comparatively lower in age groups over 70 and during the months of October and November 2021. We also found evidence of a decrease in vaccine effectiveness against hospitalisation for individuals vaccinated for 25 weeks or more, but this decrease appeared only in age groups below 70. CONCLUSIONS: The observed proportions of vaccinated among COVD-19-related hospitalisations and deaths in Switzerland were compatible with a high effectiveness of mRNA vaccines from Moderna and Pfizer-BioNtech against hospitalisation and death in all age groups. Effectiveness appears comparatively lower in older age groups, suggesting the importance of booster vaccinations. We found inconclusive evidence that vaccine effectiveness wanes over time. Repeated analyses will be able to better assess waning and the effect of boosters.

Abstract. The evaluation of the activity of radionuclides in radioactive waste is required for its disposal in final repositories. Easy-to-measure nuclides, like g-emitters and high-energy X-rays, can be measured via nondestructive nuclear techniques from outside a waste package. Some radionuclides are difficult-to-measure (DTM) from outside a package because they are a-or b-emitters. The present article discusses the application of linear regression, scaling factors (SF) and the so-called "mean activity method" to estimate the activity of DTM nuclides on metallic waste produced at the European Organization for Nuclear Research (CERN). Various statistical sampling techniques including simple random sampling, systematic sampling, stratified and authoritative sampling are described and applied to 2 waste populations of activated copper cables. The bootstrap is introduced as a tool to estimate average activities and standard errors in waste characterization. The analysis of the DTM Ni-63 is used as an example. Experimental and theoretical values of SFs are calculated and compared. Guidelines for sampling historical waste using probabilistic and non-probabilistic sampling are finally given.

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This paper describes the process adopted at the European Organization for Nuclear Research (CERN) to quantify uncertainties affecting the characterization of very-low-level radioactive waste. Radioactive waste is a by-product of the operation of high-energy particle accelerators. Radioactive waste must be characterized to ensure its safe disposal in final repositories. Characterizing radioactive waste means establishing the list of radionuclides together with their activities. The estimated activity levels are compared to the limits given by the national authority of the waste disposal. The quantification of the uncertainty affecting the concentration of the radionuclides is therefore essential to estimate the acceptability of the waste in the final repository but also to control the sorting, volume reduction and packaging phases of the characterization process. The characterization method consists of estimating the activity of produced radionuclides either by experimental methods or statistical approaches. The uncertainties are estimated using classical statistical methods and uncertainty propagation. A mixed multivariate random vector is built to generate random input parameters for the activity calculations. The random vector is a robust tool to account for the unknown radiological history of legacy waste. This analytical technique is also particularly useful to generate random chemical compositions of materials when the trace element concentrations are not available or cannot be measured. The methodology was validated using a waste population of legacy copper activated at CERN. The methodology introduced here represents a first approach for the uncertainty quantification (UQ) of the characterization process of waste produced at particle accelerators.