Biology subjects

Donker, T.

Publications and source records attributed to Donker, T..

3 recordsLinked to original sources

bioRxiv2019

When do big problems far away become smaller than the problems closer to home: Lessons for antimicrobial resistance from Father Ted

Infection prevention and control strategies aimed at reducing the occurrence of Carbapenemase-Producing Enterobacteriaceae (CPE) and other antimicrobial-resistant organisms often include advice about screening patients coming from hospitals with a known resistance problem, to prevent introductions into new hospitals by shared patients. We argue that, despite being an efficient method of identifying cases, admission screening for introduction prevention is only effective if the absolute number of imported cases from other hospitals outnumbers the cases coming from the hospitals own patient population, and therefore is only a feasible control strategy during the start of an epidemic. When determining whether import screening is still advisable, we therefore need to be continuously reminded of how Father Ted so eloquently summarised the principles of perspective: "These are small, but the ones out there are far away".

epidemiology↗

bioRxiv2019

Using hospital network-based surveillance for antimicrobial resistance as a more robust alternative to self-reporting

Hospital performance is often measured using self-reported statistics, such as the incidence of hospital-transmitted micro-organisms or those exhibiting antimicrobial resistance (AMR), encouraging hospitals with high levels to improve their performance. However, hospitals that increase screening efforts will appear to have a higher incidence and perform poorly, undermining comparison between hospitals and disincentivising testing, thus hampering infection control. We propose a surveillance system in which hospitals test patients previously discharged from other hospitals and report observed cases. Using NHS Hospital Episode Statistics data, we analysed patient movements across England and assessed the number of hospitals required to participate in such a reporting scheme to deliver robust estimates of incidence. With over 1.2 million admissions to English hospitals previously discharged from other hospitals annually, even when only a fraction of hospitals (41/155) participate (each screening at least 1000 of these admissions), the proposed surveillance system can estimate incidence across all hospitals. By reporting on other hospitals, the reporting of incidence is separated from the task of improving own performance. Therefore the incentives for increasing performance can be aligned to increase (rather than decrease) screening efforts, thus delivering both more comparable figures on the AMR problems across hospitals and improving infection control efforts.

epidemiology↗

bioRxiv2018

Rapid statistical methods for inferring intra- and inter-hospital transmission of nosocomial pathogens from whole genome sequence data

Whole genome sequence (WGS) data for bacterial pathogens can provide evidence as to the source of nosocomial infection, and more specifically the ability to distinguish between intra- and inter-hospital transmission. This is currently achieved either through using SNP thresholds, which can lack statistical robustness, or by constructing phylogenetic trees, which can be computationally expensive and difficult to interpret. Here we compare two alternative statistical approaches using 1022 genomes of methicillin resistant Staphylococcus aureus (MRSA) clone ST22. In 71% of cases both methods predict the same hospital origin, which is also supported by the ML tree. Robust assignments are divided approximately equally between intra-hospital transmission and inter-hospital transmission. Our approaches are rapid and produce intuitive output that could inform on immediate infection control priorities, as well as providing long-term data on inter-hospital transmission networks. We discuss the strengths and weakness of our methods, and the generalisability of this approach.\n\nOne Sentence SummaryWe present rapid statistical methods for distinguishing intra- versus inter-hospital transmission of bacterial pathogens using whole genome sequence data; these methods do not require the use of SNP thresholds or the generation and interpretation of phylogenetic trees.

epidemiology↗