Linking epidemiological and genomic data in cases of enteric fever in England to inform clinical management and public health action

Author:

Buczkowska Matylda12,Chattaway Marie A2,Jenkins Claire12,Hungerford Daniel13,Katwa Parisha4,Kirkbride Hilary4,Hawker Jeremy15

Affiliation:

1. National Institute for Health Research Health Protection Research Unit in Gastrointestinal Infections, University of Liverpool , Liverpool , UK

2. Gastrointestinal Bacteria Refence Unit, United Kingdom Health Security Agency (UKHSA) , London NW9 5HT , UK

3. Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool , Liverpool , UK

4. Travel Health and International Health Regulations Team, UK Health Security Agency , London , UK

5. Field Epidemiology Service, UK Health Security Agency , Birmingham , UK

Abstract

Abstract Objectives To explore the feasibility of linking data from enhanced surveillance patient questionnaires from each enteric fever case in England with genome sequencing data, including antimicrobial resistance (AMR) profiles, from the corresponding isolate of typhoidal salmonellae. Methods After linking data we interrogated the merged dataset and assessed the utility of passive surveillance data to match and monitor antimicrobial treatment regimens in enteric fever patients with the AMR profiles of the infectious agent. Results A high proportion of cases were given antibiotics (n = 1230/1415; 86.9%); half of the cases stated the class of antibiotic they were given (n = 630/1239) and half were prescribed cephalosporins (n = 316/630). Reported treatment with a combination of antibiotics increased with symptom severity. Nearly half of isolates (n = 644/1415; 45.5%) had mutations conferring resistance to ciprofloxacin. Based on genome-derived AMR profiles, typhoidal salmonellae isolates inferred to be susceptible to the recommended first-line antimicrobials were twice as likely to be isolated from individuals residing in the least deprived areas compared with the most deprived (n = 26/169; 15.4% versus n = 32/442; 7.2%). Conclusions Due to the high proportion of missing data obtained from patient interviews, we recommend a more transparent and systematic approach to recording the antibiotic prescription details by healthcare professionals in primary and secondary care. A more robust approach to data capture at this point in the care pathway would enable us to audit inconsistencies in the prescribing algorithms across England and ensure equitable treatment across all sections of society. Integrating prescribing data with the genome-derived AMR profiles of the causative agent at the individual patient level provides an opportunity to monitor the impact of treatment on clinical outcomes, and to promote best practice in real time.

Funder

National Institute for Health and Care Research Health Protection Research Unit

UK Health Security Agency

University of Liverpool

University of Warwick

Department of Health and Social Care

NIHR Post-doctoral Fellowship

Publisher

Oxford University Press (OUP)

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