Shiga toxin-producing Escherichia coli diagnosed by Stx PCR: assessing the public health risk of non-O157 strains

Autor: Keerthi Mohan, L Harvey-Vince, K J Carroll, Sooria Balasegaram, Claire Jenkins
Rok vydání: 2021
Předmět:
Zdroj: European Journal of Public Health.
ISSN: 1464-360X
1101-1262
DOI: 10.1093/eurpub/ckaa232
Popis: Background The implementation by diagnostic laboratories in England of polymerase chain reaction (PCR) to screen faecal specimens for Shiga toxin-producing Escherichia coli (STEC) has resulted in a significant increase in notifications mainly due to non-O157 strains. The purpose of this study was to develop an approach to public health risk assessment that prioritizes follow-up to cases caused by haemolytic uraemic syndrome (HUS) associated E. coli (HUSEC) strains and minimizes unnecessary actions. Methods Epidemiological and microbiological data were prospectively collected from 1 November 2013 to 31 March 2017 and used to compare three risk assessment approaches. Results A history of HUS/bloody diarrhoea/age under 6 years and faecal specimens positive for stx-predicted HUSEC with a diagnostic accuracy of 84% (95% CI; 81–88%). STEC isolated by Gastrointestinal Bacteria Reference Unit (GBRU) and stx2 and eae positive predicted HUSEC with a diagnostic accuracy of 99% (95% CI; 98–100%). Risk assessment combining these two tests predicts the most efficient use of resources, predicting that 18% (97/552) of cases would be eligible for follow-up at some stage, 16% (86/552) following local stx PCR results, 1% (7/552) following GBRU results of stx2 and eae status and 0.7% (4/552) following whole-genome sequencing. Follow-up could be stopped in 78% (76/97) of these cases, 97% (74/76) following second stage risk assessment. Conclusions This three-stage risk assessment approach prioritizes follow-up to HUSEC and minimizes unnecessary public health actions. We developed it into the algorithm for public health actions included in the updated PHE Guidance for management of STEC published in August 2018.
Databáze: OpenAIRE