Accuracy of quantitative viral secondary standards: a re-examination

Interlaboratory agreement of viral load assays depends on the accuracy and uniformity of quantitative calibrators. Previous work demonstrated poor agreement of secondary cytomegalovirus (CMV) standards with nominal values. This study re-evaluated this issue among commercially produced secondary standards for both BK virus (BKV) and CMV, using digital polymerase chain reaction (dPCR) to compare the materials from three different manufacturers. Overall, standards showed an improved agreement compared to prior work, against nominal values in both log10 copies/mL and log10 international unit (IU)/mL, with bias from manufacturer-assigned nominal values of 0.0-0.9 log10 units (either copies or IU)/mL. Standards normalized to IU and those values assigned by dPCR rather than by real-time PCR (qPCR) showed better agreement with nominal values. The latter reinforces prior conclusions regarding the utility of using such methods for quantitative value assignment in reference materials. Quantitative standards have improved over the last several years, and the remaining bias from nominal values might be further reduced by universal implementation of dPCR methods for value assignment, normalized to IU.

IMPORTANCE

Interlaboratory agreement of viral load assays depends on accuracy and uniformity of quantitative calibrators. Previous work, published in JCM several years ago, demonstrated poor agreement of secondary cytomegalovirus (CMV) standards with nominal values. This study re-evaluated this issue among commercially produced secondary standards for both BK virus (BKV) and CMV, using digital polymerase chain reaction (dPCR) to compare the materials from three different manufacturers. Overall, standards showed an improved agreement compared to prior work, against nominal values, indicating a substantial improvement in the production of accurate secondary viral standards, while supporting the need for further work in this area and for the broad adaption of international unit (IU) as a reporting standard for quantitative viral load results.

A prospective bacterial whole-genome-sequencing-based surveillance programme for comprehensive early detection of healthcare-associated infection transmission in paediatric oncology patients

BACKGROUND

Bacterial whole-genome sequencing (WGS) and determination of genetic relatedness is an important tool for investigation of epidemiologically suspected outbreaks.

AIM

This prospective cohort study evaluated a comprehensive, prospective bacterial WGS-based surveillance programme for early detection of transmission of most bacterial pathogens among patients at a paediatric oncology hospital.

METHODS

Cultured bacterial isolates from clinical diagnostic specimens collected prospectively from both inpatient and outpatient encounters between January 2019 and December 2021 underwent routine WGS and core genome multi-locus sequence typing to determine isolates' relatedness. Previously collected isolates from January to December 2018 were retrospectively analysed for identification of prior or ongoing transmission. Multi-patient clusters were investigated to identify potential transmission events based on temporal and spatial epidemiological links and interventions were introduced.

FINDINGS

A total of 1497 bacterial isolates from 1025 patients underwent WGS. A total of 259 genetically related clusters were detected, of which 18 (6.9%) multi-patient clusters involving 38 (3.7%) patients were identified. Sixteen clusters involved two patients each, and two clusters involved three patients. Following investigation, epidemiologically plausible transmission links were identified in five (27.8%) multi-patient clusters. None of the multi-patient clusters were suspected by conventional epidemiological surveillance.

CONCLUSION

Bacterial WGS-based surveillance for early detection of hospital transmission detected several limited multi-patient clusters that were unrecognized by conventional epidemiological methods. Genomic surveillance helped efficiently focus interventions while reducing unnecessary investigations.