Maten voor prestige, sociaal-economische status en sociale klasse voor de standaard beroepen classificatie 1992.

FdR – Publicaties zonder aanstelling Universiteit Leide

Multi-source statistics:Basic situations and methods

Many National Statistical Institutes (NSIs), especially in Europe, are moving from single‐source statistics to multi‐source statistics. By combining data sources, NSIs can produce more detailed and more timely statistics and respond more quickly to events in society. By combining survey data with already available administrative data and Big Data, NSIs can save data collection and processing costs and reduce the burden on respondents. However, multi‐source statistics come with new problems that need to be overcome before the resulting output quality is sufficiently high and before those statistics can be produced efficiently. What complicates the production of multi‐source statistics is that they come in many different varieties as data sets can be combined in many different ways. Given the rapidly increasing importance of producing multi‐source statistics in Official Statistics, there has been considerable research activity in this area over the last few years, and some frameworks have been developed for multi‐source statistics. Useful as these frameworks are, they generally do not give guidelines to which method could be applied in a certain situation arising in practice. In this paper, we aim to fill that gap, structure the world of multi‐source statistics and its problems and provide some guidance to suitable methods for these problems

Molecular characteristics of carbapenemase-producing Enterobacterales in the Netherlands; results of the 2014–2018 national laboratory surveillance

Objectives: Carbapenem resistance mediated by mobile genetic elements has emerged worldwide and has become a major public health threat. To gain insight into the molecular epidemiology of carbapenem resistance in The Netherlands, Dutch medical microbiology laboratories are requested to submit suspected carbapenemase-producing Enterobacterales (CPE) to the National Institute for Public Health and the Environment as part of a national surveillance system. Methods: Meropenem MICs and species identification were confirmed by E-test and MALDI-TOF and carbapenemase production was assessed by the Carbapenem Inactivation Method. Of all submitted CPE, one species/carbapenemase gene combination per person per year was subjected to next-generation sequencing (NGS). Results: In total, 1838 unique isolates were received between 2014 and 2018, of which 892 were unique CPE isolates with NGS data available. The predominant CPE species were Klebsiella pneumoniae (n = 388, 43%), Escherichia coli (n = 264, 30%) and Enterobacter cloacae complex (n = 116, 13%). Various carbapenemase alleles of the same carbapenemase gene resulted in different susceptibilities to meropenem and this effect varied between species. Analyses of NGS data showed variation of prevalence of carbapenemase alleles over time with blaOXA-48 being predominant (38%, 336/892), followed by blaNDM-1 (16%, 145/892). For the first time in the Netherlands, blaOXA-181, blaOXA-232 and blaVIM-4 were detected. The genetic background of K. pneumoniae and E. coli isolates was highly diverse. Conclusions: The CPE population in the Netherlands is diverse, suggesting multiple introductions. The predominant carbapenemase alleles are blaOXA-48 and blaNDM-1. There was a clear association between species, carbapenemase allele and susceptibility to meropenem