Imperial College London

ProfessorAlisonHolmes

Faculty of MedicineDepartment of Infectious Disease

Professor of Infectious Diseases
 
 
 
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Contact

 

+44 (0)20 3313 1283alison.holmes

 
 
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Location

 

8N16Hammersmith HospitalHammersmith Campus

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Summary

 

Publications

Publication Type
Year
to

296 results found

Borek AJ, Campbell A, Dent E, Butler CC, Holmes A, Moore M, Walker AS, McLeod M, Tonkin-Crine Set al., 2021, Implementing interventions to reduce antibiotic use: a qualitative study in high-prescribing practices, BMC FAMILY PRACTICE, Vol: 22

Journal article

Rawson TM, Hernandez B, Wilson R, Wilson R, Ming D, Herrero P, Ranganathan N, Skolimowska K, Gilchrist M, Satta G, Georgiou P, Holmes Aet al., 2021, Supervised machine learning to support the diagnosis of bacterial infection in the context of COVID-19, JAC-Antimicrobial Resistance, Vol: 3, Pages: 1-4, ISSN: 2632-1823

Background: Bacterial infection has been challenging to diagnose in patients with COVID-19. We developed and evaluated supervised machine learning algorithms to support the diagnosis of secondary bacterial infection in hospitalized patients during COVID-19.Methods: Inpatient data at three London hospitals for the first COVD-19 wave in March and April 2020 were extracted. Demographic, blood test, and microbiology data for individuals with and without SARS-CoV-2 positive PCR were obtained. A Gaussian-Naïve Bayes (GNB), Support Vector Machine (SVM), and Artificial Neuronal Network (ANN) were trained and compared using the area under the receiver operating characteristic curve (AUCROC). The best performing algorithm (SVM with 21 blood test variables) was prospectively piloted in July 2020. AUCROC was calculated for the prediction of a positive microbiological sample within 48 hours of admission. Results: A total of 15,599 daily blood profiles for 1,186 individual patients were identified to train the algorithms. 771/1186 (65%) individuals were SARS-CoV-2 PCR positive. Clinically significant microbiology results were present for 166/1186 (14%) patients during admission. A SVM algorithm trained with 21 routine blood test variables and over 8000 individual profiles had the best performance. AUCROC was 0.913, sensitivity 0.801, and specificity 0.890. Prospective testing on 54 patients on admission (28/54, 52% SARS-CoV-2 PCR positive) demonstrated an AUCROC of 0.960 (0.90-1.00). Conclusion: A SVM using 21 routine blood test variables had excellent performance at inferring the likelihood of positive microbiology. Further prospective evaluation of the algorithms ability to support decision making for the diagnosis of bacterial infection in COVID-19 cohorts is underway.

Journal article

Huttner A, Bricheux A, Buurmeijer-van Dijk CCJM, Harvey M, Holmes A, Lassmann B, Lavergne V, Mailles A, Mendelson M, Muller N, Sanguinetti M, Sears C, Skevaki C, Syed U, Thomas S, Swartz TH, European Society of Clinical Microbiology and Infectious Diseases, Federation of European Microbiological Societies, Infectious Disease Society of America, International Society for Infectious Diseases, Swiss Society for Infectious Diseaseset al., 2021, Joint ESCMID, FEMS, IDSA, ISID and SSI position paper on the fair handling of career breaks among physicians and scientists when assessing eligibility for early-career awards., Clin Microbiol Infect

BACKGROUND: Though women increasingly make up the majority of medical-school and other science graduates, they remain a minority in academic biomedical settings, where they are less likely to hold leadership positions or be awarded research funding. A major factor is the career breaks that women disproportionately take to see to familial duties. They experience a related yet overlooked hurdle upon their return: they are often too old to be eligible for 'early-career researcher' grants and 'career-development' awards, which are stepping stones to leadership positions in many institutions and determine therewith the demographics of their hierarchies for decades to come. Though age limits are imposed to protect young applicants from more experienced seniors, they have an unintended side effect of excluding returning workers, still disproportionately women, from the running. METHODS: In this joint effort by the European Society of Clinical Microbiology and Infectious Diseases (ESCMID), the Federation of European Microbiological Societies (FEMS), the Infectious Disease Society of America (IDSA), the International Society for Infectious Diseases (ISID) and the Swiss Society for Infectious Diseases (SSI), we invited all ECCMID-affiliated medical societies and funding bodies to participate in a survey on current 'early-career' application restrictions and measures taken to provide protections for career breaks. RECOMMENDATIONS: The following simple consensus recommendations are geared to funding bodies, academic societies, and other organizations for the fair handling of eligibility for early-career awards: 1. Apply a professional, not physiologic, age limit to applicants. 2. State clearly in the award announcement that career breaks will be factored into applicants' evaluations such that: • Time absent is time extended: for every full-time equivalent (FTE) of career break taken, the same FTE will be extended to the professional age limit. • Opportunity costs will

Journal article

Zhu J, Ferlie E, Castro-Sánchez E, Birgand G, Holmes A, Atun R, Kieltyka H, Ahmad Ret al., 2021, Macro level factors influencing strategic responses to emergent pandemics: a scoping review, Journal of Global Health, ISSN: 2047-2978

Journal article

Zhu N, Aylin P, Rawson T, Gilchrist M, Majeed A, Holmes Aet al., 2021, Investigating the impact of COVID-19 on primary care antibiotic prescribing in North West London across two epidemic waves., Clin Microbiol Infect

OBJECTIVES: We investigated the impact of COVID-19 and national pandemic response on primary care antibiotic prescribing in London. METHODS: Individual prescribing records between 2015 and 2020 for 2 million residents in North West London were analysed. Prescribing records were linked to SARS-CoV-2 test results. Prescribing volumes, in total, and stratified by patient characteristics, antibiotic class, and AWaRe classification, were investigated. Interrupted time series analysis was performed to detect measurable change in the trend of prescribing volume since the national lockdown in March 2020, immediately before the first COVID-19 peak in London. RESULTS: Records covering 366,059 patients, 730,001 antibiotic items, and 848,201 SARS-CoV-2 tests between January and November 2020 were analysed. Before March 2020, there was a background downward trend (decreasing by 584 items/month) in primary care antibiotic prescribing. This reduction rate accelerated to 3504 items/month from March 2020. This rate of decrease was sustained beyond the initial peak, continuing into winter and the second peak. Despite an overall reduction in prescribing volume, co-amoxiclav, a broad-spectrum "Access" antibiotic prescribing rose by 70.1% in patients aged 50 and older from February to April. Commonly prescribed antibiotics within 14 days of a positive SARS-CoV-2 test were amoxicillin (863/2474, 34.9%) and doxycycline (678/2474, 27.4%). This aligned with national guidelines on management of community pneumonia of unclear cause. The proportion of "Watch" antibiotics used decreased during the peak in COVID-19. CONCLUSIONS: A sustained reduction in community antibiotic prescribing was observed since the first lockdown. Investigation of community-onset infectious diseases and potential unintended consequences of reduced prescribing is urgently needed.

Journal article

Bonaconsa C, Mbamalu O, Mendelson M, Boutall A, Warden C, Rayamajhi S, Pennel T, Hampton M, Joubert I, Tarrant C, Holmes A, Charani Eet al., 2021, Visual mapping of team dynamics and communication patterns on surgical ward rounds: an ethnographic study, BMJ Quality & Safety, ISSN: 2044-5415

Background: Team dynamics influence infection prevention and management practices and implementation of antibiotic stewardship (AS). Using an innovative visual mapping approach, alongside traditional qualitative methods, we aimed to study team dynamics and flow of communication (who gets to speak, and whose voice is heard) during surgical ward rounds, and how team dynamics and communication patterns may shape decision-making in relation to infection management and AS.Materials/methods: Between May and November 2019, data were gathered through direct observations of ward rounds and face-to-face interviews with ward round participants in selected surgical specialties at a tertiary hospital in South Africa. Using a visual mapping method – sociograms – content and flow of communication and the social links between individual participants were plotted. Field notes from observations and interview transcripts were analysed using a grounded theory approach.Results: Data were gathered from 60 hours of ward round observations, including 1024 individual patient discussions; 60 sociograms, interviews with healthcare professionals (60) and patients (7). The nature of discussions about AS and IPC on ward rounds vary across specialties and are affected by the content and structure of the clinical update provided, the consultant’s leadership and interaction style, and competing priorities at the bedside. Registrars act as gatekeepers, initiating antibiotic discussions; consultants are key decision-makers. Other team members have limited input in ward round conversations, despite having recognised roles in AS and IPC. Hierarchies in teams manifest themselves on ward rounds in where staff position themselves, influencing their contribution to care. Varied leadership styles affect ward-round dynamics, in particular, whether nurses and patients are actively engaged in key decisions on infection management and antibiotic therapy, and whether actions are assigned to i

Journal article

Petersen E, Lucey D, Blumberg L, Kramer LD, Al-Abri S, Lee SS, Pinto TDCA, Obiero CW, Rodriguez-Morales AJ, Yapi R, Abubakar A, Tambyah PA, Holmes A, Chen LHet al., 2021, COVID-19 vaccines under the International Health Regulations - We must use the WHO International Certificate of Vaccination or Prophylaxis., Int J Infect Dis, Vol: 104, Pages: 175-177

Journal article

Rodriguez-Manzano J, Malpartida-Cardenas K, Moser N, Pennisi I, Cavuto M, Miglietta L, Moniri A, Penn R, Satta G, Randell P, Davies F, Bolt F, Barclay W, Holmes A, Georgiou Pet al., 2021, Handheld Point-of-Care System for Rapid Detection of SARS-CoV-2 Extracted RNA in under 20 min, ACS Central Science, ISSN: 2374-7943

The COVID-19 pandemic is a global health emergency characterized by the high rate of transmission and ongoing increase of cases globally. Rapid point-of-care (PoC) diagnostics to detect the causative virus, SARS-CoV-2, are urgently needed to identify and isolate patients, contain its spread and guide clinical management. In this work, we report the development of a rapid PoC diagnostic test (<20 min) based on reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) and semiconductor technology for the detection of SARS-CoV-2 from extracted RNA samples. The developed LAMP assay was tested on a real-time benchtop instrument (RT-qLAMP) showing a lower limit of detection of 10 RNA copies per reaction. It was validated against extracted RNA from 183 clinical samples including 127 positive samples (screened by the CDC RT-qPCR assay). Results showed 91% sensitivity and 100% specificity when compared to RT-qPCR and average positive detection times of 15.45 ± 4.43 min. For validating the incorporation of the RT-LAMP assay onto our PoC platform (RT-eLAMP), a subset of samples was tested (n = 52), showing average detection times of 12.68 ± 2.56 min for positive samples (n = 34), demonstrating a comparable performance to a benchtop commercial instrument. Paired with a smartphone for results visualization and geolocalization, this portable diagnostic platform with secure cloud connectivity will enable real-time case identification and epidemiological surveillance.

Journal article

Charani E, Holmes A, Bonaconsa C, Mbamalu O, Mendelson M, Surendran S, Singh S, Nampoothiri V, Boutall A, Tarrant C, Dhar P, Pennel T, Leather A, Hampton Met al., 2021, Investigating infection management and antimicrobial stewardship in surgery: a qualitative study from India and South Africa, Clinical Microbiology and Infection, ISSN: 1198-743X

Objectives To investigate the drivers for infection management and antimicrobial stewardship (AMS) across high infection risk surgical pathways. Methods An qualitative study, ethnographic observation of clinical practices, patient case studies, and face-to-face interviews with healthcare professionals (HCP) and patients was conducted across cardiovascular and thoracic and gastrointestinal surgical pathways in South Africa (SA) and India. Aided by Nvivo 11 software, data were coded and analysed until saturation was reached. The multiple modes of enquiry enabled cross-validation and triangulation of findings.Results Between July 2018–August 2019 data were gathered from 190 hours of non-participant observations (138 India, 72 SA); interviews with HCPs (44 India, 61 SA); patients (6 India, 8 SA), and, case studies (4 India, 2 SA). Across the surgical pathway, multiple barriers impede effective infection management and AMS. The existing, implicit roles of HCPs (including nurses, and senior surgeons) are overlooked as interventions target junior doctors, bypassing the opportunity for integrating infection-related care across the surgical team. Critically, the ownership of decisions remains with the operating surgeons and entrenched hierarchies restrict the inclusion of other HCPs in decision-making. The structural foundations to enable staff to change their behaviours and participate in infection-related surgical care is lacking.ConclusionsIdentifying the implicit existing HCPs roles in infection management is critical and will facilitate the development of effective and transparent processes across the surgical team for optimised care. Applying a framework approach that includes nurse leadership, empowering pharmacists and engaging surgical leads is essential for integrated AMS and infection-related care. Keywords: antibiotic prescribing, infection control, ethnography, low- and middle-income country, surgery

Journal article

Zhu NJ, McLeod M, McNulty CAM, Lecky DM, Holmes AH, Ahmad Ret al., 2021, Trends in Antibiotic Prescribing in Out-of-Hours Primary Care in England from January 2016 to June 2020 to Understand Behaviours during the First Wave of COVID-19, ANTIBIOTICS-BASEL, Vol: 10, ISSN: 2079-6382

Journal article

Price JR, Mookerjee S, Dyakova E, Myall A, Leung W, Weiße AY, Shersing Y, Brannigan ET, Galletly T, Muir D, Randell P, Davies F, Bolt F, Barahona M, Otter JA, Holmes AHet al., 2021, Development and delivery of a real-time hospital-onset COVID-19 surveillance system using network analysis, Clinical Infectious Diseases, Vol: 72, Pages: 82-89, ISSN: 1058-4838

BackgroundUnderstanding nosocomial acquisition, outbreaks and transmission chains in real-time will be fundamental to ensuring infection prevention measures are effective in controlling COVID-19 in healthcare. We report the design and implementation of a hospital-onset COVID-19 infection (HOCI) surveillance system for an acute healthcare setting to target prevention interventions.MethodsThe study took place in a large teaching hospital group in London, UK. All patients tested for SARS-CoV-2 between 4th March and 14th April 2020 were included. Utilising data routinely collected through electronic healthcare systems we developed a novel surveillance system for determining and reporting HOCI incidence and providing real-time network analysis. We provided daily reports on incidence and trends over time to support HOCI investigation, and generated geo-temporal reports using network analysis to interrogate admission pathways for common epidemiological links to infer transmission chains. By working with stakeholders the reports were co-designed for end users.ResultsReal-time surveillance reports revealed: changing rates of HOCI throughout the course of the COVID-19 epidemic; key wards fuelling probable transmission events; HOCIs over-represented in particular specialities managing high-risk patients; the importance of integrating analysis of individual prior pathways; and the value of co-design in producing data visualisation. Our surveillance system can effectively support national surveillance.ConclusionsThrough early analysis of the novel surveillance system we have provided a description of HOCI rates and trends over time using real-time shifting denominator data. We demonstrate the importance of including the analysis of patient pathways and networks in characterising risk of transmission and targeting infection control interventions.

Journal article

Ahuja S, Godwin G, Birgand G, Leather A, Singh S, Pranav V, Peiffer-Smadja N, Charani E, Holmes A, Sevdalis Net al., 2020, Understanding the intervention co-design process for perioperative antibiotic use at tertiary care hospital in Southern part of India: a two phased qualitative study, Publisher: BMC, ISSN: 1748-5908

Conference paper

Ahuja S, Peiffer-Smadja N, Peven K, White M, Singh S, Mendelson M, Holmes A, Leather A, Birgand G, Sevdalis Net al., 2020, Use of feedback data to reduce surgical site infections and optimise antibiotic use in surgery: a systematic scoping review, Publisher: BMC, ISSN: 1748-5908

Conference paper

Castro-Sanchez E, Surendran S, Nampoothiri V, Joseph S, Singh S, Tarrant C, Holmes AH, Charani Eet al., 2020, Are current infection prevention and control expectations fit for purpose? Interim results from an ethnographic study in South India, Publisher: ELSEVIER SCI LTD, Pages: 307-307, ISSN: 1201-9712

Conference paper

Sangkaew S, 2020, Enhancing risk prediction of progression to severe disease during the febrile phase of dengue: A systematic review and meta-analysis, The Lancet Infectious Diseases, Vol: 101, Pages: 237-238, ISSN: 1473-3099

Background: Since no effective vaccine or specific treatment for dengue exists, the early prediction of progression to severe disease plays a keys role in patient triage and clinical management during the febrile phase. Without differentiating the time-course of the illness, previous systematic reviews and meta-analyses may have failed to identify early prognostic factors for progression to severe disease. This study aimed to identify the factors associated with progression to severe dengue disease, which are detectable specifically in the febrile phase.Methods and materials: We conducted a systematic review and meta-analysis to identify prognostic factors associated with disease progression identifiable during the febrile phase. Eight medical databases including MEDLINE, EMBASE, and Web of Science were searched for studies published from January 1997 to February 2018. The relevant studies were selected and assessed by three reviewers independenly with discrepancies resolved by consensus. We performed meta-analysis for factors reported in at least four studies. Meta-analysis were performed using random-effects models; heterogeneity and publication bias were also assessed.Results: In line with the 2009 WHO guidelines, we found that vomiting, abdominal pain and tenderness, spontaneous and mucosal bleeding, and clinical fluid accumulation were clinical features associated with severe disease. In addition, we found that the presence of specific pre-existing comorbidities (diabetes mellitus, hypertension and renal disease) were associated with progression to severe disease. We also found that individuals with a lower platelet count, lower serum albumin and higher aminotransferase levels (AST or ALT), detected during the first four days of the illness, were more prone to progress to severe disease. Dengue virus serotype 2 and secondary infections were also associated with progression to severe disease.Conclusion: This study supports the monitoring of the warning signs des

Journal article

Naylor N, Yamashita K, Iwami M, Kunisawa S, Mizuno S, Castro-Sánchez E, Imanaka Y, Ahmad R, Holmes Aet al., 2020, Code-sharing in cost-of-illness calculations: an application to antibiotic-resistant bloodstream infections, Frontiers in Public Health, Vol: 8, ISSN: 2296-2565

Background: More data-driven evidence is needed on the cost of antibiotic resistance. Both Japan and England have large surveillance and administrative datasets. Code sharing of costing models enables reduced duplication of effort in research.Objective: To estimate the burden of antibiotic-resistant Staphylococcus aureus bloodstream infections (BSIs) in Japan, utilizing code that was written to estimate the hospital burden of antibiotic-resistant Escherichia coli BSIs in England. Additionally, the process in which the code-sharing and application was performed is detailed, to aid future such use of code-sharing in health economics.Methods: National administrative data sources were linked with voluntary surveillance data within the Japan case study. R software code, which created multistate models to estimate the excess length of stay associated with different exposures of interest, was adapted from previous use and run on this dataset. Unit costs were applied to estimate healthcare system burden in 2017 international dollars (I$).Results: Clear supporting documentation alongside open-access code, licensing, and formal communication channels, helped the re-application of costing code from the English setting within the Japanese setting. From the Japanese healthcare system perspective, it was estimated that there was an excess cost of I$6,392 per S. aureus BSI, whilst oxacillin resistance was associated with an additional I$8,155.Conclusions: S. aureus resistance profiles other than methicillin may substantially impact hospital costs. The sharing of costing models within the field of antibiotic resistance is a feasible way to increase burden evidence efficiently, allowing for decision makers (with appropriate data available) to gain rapid cost-of-illness estimates.

Journal article

Ellington MJ, Davies F, Jauneikaite E, Hopkins KL, Turton JF, Adams G, Pavlu J, Innes AJ, Eades C, Brannigan ET, Findlay J, White L, Bolt F, Kadhani T, Chow Y, Patel B, Mookerjee S, Otter JA, Sriskandan S, Woodford N, Holmes Aet al., 2020, A multi-species cluster of GES-5 carbapenemase producing Enterobacterales linked by a geographically disseminated plasmid, Clinical Infectious Diseases, Vol: 71, Pages: 2553-2560, ISSN: 1058-4838

BACKGROUND: Early and accurate treatment of infections due to carbapenem-resistant organisms is facilitated by rapid diagnostics but rare resistance mechanisms can compromise detection. One year after a GES-5 carbapenemase-positive Klebsiella oxytoca infection was identified by whole genome sequencing (WGS) (later found to be part of a cluster of three cases), a cluster of 11 patients with GES-5-positive K. oxytoca was identified over 18 weeks in the same hospital.METHODS: Bacteria were identified by MALDI-TOF, antimicrobial susceptibility testing followed EUCAST guidelines. Ertapenem-resistant isolates were referred to Public Health England for characterization using PCR detection of GES, pulse-field gel electrophoresis (PFGE) and WGS for the second cluster.RESULTS: The identification of the first GES-5 K. oxytoca isolate was delayed, being identified on WGS. A GES-gene PCR informed the occurrence of the second cluster in real-time. In contrast to PFGE, WGS phylogenetic analysis refuted an epidemiological link between the two clusters; it also suggested a cascade of patient-to-patient transmission in the later cluster. A novel GES-5-encoding plasmid was present in K. oxytoca,E. coli and E. cloacae isolates from unlinked patients within the same hospital group and in human and wastewater isolates from three hospitals elsewhere in the UK.CONCLUSIONS: Genomic sequencing revolutionized the epidemiological understanding of the clusters, it also underlined the risk of covert plasmid propagation in healthcare settings and revealed the national distribution of the resistance-encoding plasmid. Sequencing results also informed and led to the ongoing use of enhanced diagnostic tests for detecting carbapenemases locally and nationally.

Journal article

Pouwels KB, Vansteelandt S, Batra R, Edgeworth J, Wordsworth S, Robotham JV, Improving the uptake and SusTainability of Effective interventions to promote Prudent antibiotic Use and Primary care STEP-UP Teamet al., 2020, Estimating the effect of healthcare-associated infections on excess length of hospital stay using inverse probability-weighted survival curves, Clinical Infectious Diseases, Vol: 71, Pages: e415-e420, ISSN: 1058-4838

BACKGROUND: Studies estimating excess length of stay (LOS) attributable to nosocomial infections have failed to address time-varying confounding, likely leading to overestimation of their impact. We present a methodology based on inverse probability-weighted survival curves to address this limitation. METHODS: A case study focusing on intensive care unit-acquired bacteremia using data from 2 general intensive care units (ICUs) from 2 London teaching hospitals were used to illustrate the methodology. The area under the curve of a conventional Kaplan-Meier curve applied to the observed data was compared with that of an inverse probability-weighted Kaplan-Meier curve applied after treating bacteremia as censoring events. Weights were based on the daily probability of acquiring bacteremia. The difference between the observed average LOS and the average LOS that would be observed if all bacteremia cases could be prevented was multiplied by the number of admitted patients to obtain the total excess LOS. RESULTS: The estimated total number of extra ICU days caused by 666 bacteremia cases was estimated at 2453 (95% confidence interval [CI], 1803-3103) days. The excess number of days was overestimated when ignoring time-varying confounding (2845 [95% CI, 2276-3415]) or when completely ignoring confounding (2838 [95% CI, 2101-3575]). CONCLUSIONS: ICU-acquired bacteremia was associated with a substantial excess LOS. Wider adoption of inverse probability-weighted survival curves or alternative techniques that address time-varying confounding could lead to better informed decision making around nosocomial infections and other time-dependent exposures.

Journal article

Yu L-S, Rodriguez-Manzano J, Moser N, Moniri A, Malpartida-Cardenas K, Miscourides N, Sewell T, Kochina T, Brackin A, Rhodes J, Holmes AH, Fisher MC, Georgiou Pet al., 2020, Rapid detection of azole-resistant Aspergillus fumigatus in clinical and environmental isolates using lab-on-a-chip diagnostic system, Journal of Clinical Microbiology, Vol: 58, Pages: 1-11, ISSN: 0095-1137

Aspergillus fumigatus has widely evolved resistance to the most commonly used class of antifungal chemicals, the azoles. Current methods for identifying azole resistance are time-consuming and depend on specialized laboratories. There is an urgent need for rapid detection of these emerging pathogens at point-of-care to provide the appropriate treatment in the clinic and to improve management of environmental reservoirs to mitigate the spread of antifungal resistance. Our study demonstrates the rapid and portable detection of the two most relevant genetic markers linked to azole resistance, the mutations TR34 and TR46, found in the promoter region of the gene encoding the azole target, cyp51A. We developed a lab-on-a-chip platform consisting of: (1) tandem-repeat loop-mediated isothermal amplification, (2) state-of-the-art complementary metal-oxide-semiconductor microchip technology for nucleic-acid amplification detection and, (3) and a smartphone application for data acquisition, visualization and cloud connectivity. Specific and sensitive detection was validated with isolates from clinical and environmental samples from 6 countries across 5 continents, showing a lower limit-of-detection of 10 genomic copies per reaction in less than 30 minutes. When fully integrated with a sample preparation module, this diagnostic system will enable the detection of this ubiquitous fungus at the point-of-care, and could help to improve clinical decision making, infection control and epidemiological surveillance.

Journal article

Charani E, Singh S, Mendelson M, Veepanattu P, Nampoothiri V, Edathadatil F, Surendran S, Bonaconsa C, Mbamalu O, Ahuja S, Sevdalis N, Tarrant C, Birgand G, Castro-SAnchez E, Ahmad R, Holmes Aet al., 2020, Building resilient and responsive research collaborations to tackle antimicrobial resistance – lessons learnt from India, South Africa and UK, International Journal of Infectious Diseases, Vol: 100, Pages: 278-282, ISSN: 1201-9712

Research, collaboration and knowledge exchange are critical to global efforts to tackle antimicrobial resistance (AMR). Different healthcare economies are faced with different challenges in implementing effective strategies to address AMR. Building effective capacity for research to inform AMR related strategies and policies AMR is recognised as an important contributor to success. Interdisciplinary, inter-sector, as well as inter-country collaboration is needed to span AMR efforts from the global to local. Developing reciprocal, long-term, partnerships between collaborators in high-income and low- and middle-income countries (LMICs) needs to be built on principles of capacity building. Using case-studies spanning local to international research collaborations to co-design, implement and evaluate strategies to tackle AMR, we evaluate and build upon the ESSENCE criteria for capacity building in LMICs. The first case-study describes the local co-design and implementation of antimicrobial stewardship in the state of Kerala in India. The second case-study describes an international research collaboration investigating AMR across surgical pathways in India, UK and South Africa. We describe the steps undertaken to develop robust, agile, and flexible antimicrobial stewardship research and implementation teams. Notably, investing in capacity building ensured that the programmes described in these case-studies were sustained through the current severe acute respiratory syndrome corona virus pandemic. Describing the strategies adopted by a local and an international collaboration to tackle AMR, we provide a model for capacity building in LMICs that can support sustainable and agile antimicrobial stewardship programmes.

Journal article

Rawson TM, Wilson R, Holmes A, 2020, Understanding the role of bacterial and fungal infection in COVID-19, Clinical Microbiology and Infection, ISSN: 1198-743X

Journal article

Moniri A, Miglietta L, Holmes A, Georgiou P, Rodriguez Manzano Jet al., 2020, High-level multiplexing in digital PCR with intercalating dyes by coupling real-time kinetics and melting curve analysis., Analytical Chemistry, Vol: 92, Pages: 14181-14188, ISSN: 0003-2700

Digital polymerase chain reaction (dPCR) is a mature technique that has enabled scientific breakthroughs in several fields. However, this technology is primarily used in research environments with high-level multiplexing representing a major challenge. Here, we propose a novel method for multiplexing, referred to as amplification and melting curve analysis (AMCA), which leverages the kinetic information in real-time amplification data and the thermodynamic melting profile using an affordable intercalating dye (EvaGreen). The method trains a system comprised of supervised machine learning models for accurate classification, by virtue of the large volume of data from dPCR platforms. As a case study, we develop a new 9-plex assay to detect mobilised colistin resistant (mcr) genes as clinically relevant targets for antimicrobial resistance. Over 100,000 amplification events have been analysed, and for the positive reactions, the AMCA approach reports a classification accuracy of 99.33 ± 0.13%, an increase of 10.0% over using melting curve analysis. This work provides an affordable method of high-level multiplexing without fluorescent probes, extending the benefits of dPCR in research and clinical settings.

Journal article

Moniri A, Miglietta L, Malpartida Cardenas K, Pennisi I, Cacho Soblechero M, Moser N, Holmes A, Georgiou P, Rodriguez Manzano Jet al., 2020, Amplification curve analysis: Data-driven multiplexing using real-time digital PCR, Analytical Chemistry, Vol: 92, Pages: 13134-13143, ISSN: 0003-2700

Information about the kinetics of PCR reactions are encoded in the amplification curve. However, in digital PCR (dPCR), this information is typically neglected by collapsing each amplification curve into a binary output (positive/negative). Here, we demonstrate that the large volume of raw data obtained from realtime dPCR instruments can be exploited to perform data-driven multiplexing in a single fluorescent channel using machine learning methods, by virtue of the information in the amplification curve. This new approach, referred to as amplification curve analysis (ACA), was shown using an intercalating dye (EvaGreen), reducing the cost and complexity of the assay and enabling the use of melting curve analysis for validation. As a case study, we multiplexed 3 carbapenem-resistant genes to show the impact of this approach on global challenges such as antimicrobial resistance. In the presence of single targets, we report a classification accuracy of 99.1% (N = 16188) which represents a 19.7% increase compared to multiplexing based on the final fluorescent intensity. Considering all combinations of amplification events (including coamplifications), the accuracy was shown to be 92.9% (N = 10383). To support the analysis, we derived a formula to estimate the occurrence of co-amplification in dPCR based on multivariate Poisson statistics, and suggest reducing the digital occupancy in the case of multiple targets in the same digital panel. The ACA approach takes a step towards maximizing the capabilities of existing real-time dPCR instruments and chemistries, by extracting more information from data to enable data-driven multiplexing with high accuracy. Furthermore, we expect that combining this method with existing probe-based assays will increase multiplexing capabilities significantly. We envision that once emerging point-of-care technologies can reliably capture real-time data from isothermal chemistries, the ACA method will facilitate the implementation of dPCR outs

Journal article

Conly J, Seto WH, Pittet D, Holmes A, Chu M, Hunter PRet al., 2020, Use of medical face masks versus particulate respirators as a component of personal protective equipment for health care workers in the context of the COVID-19 pandemic (vol 9, 126, 2020), ANTIMICROBIAL RESISTANCE AND INFECTION CONTROL, Vol: 9, ISSN: 2047-2994

Journal article

Peiffer-Smadja N, Allison R, Jones LF, Holmes A, Patel P, Lecky DM, Ahmad R, McNulty CAMet al., 2020, Preventing and Managing Urinary Tract Infections: Enhancing the Role of Community Pharmacists-A Mixed Methods Study, ANTIBIOTICS-BASEL, Vol: 9, ISSN: 2079-6382

Journal article

Otter JA, Mookerjee S, Davies F, Bolt F, Dyakova E, Shersing Y, Boonyasiri A, Weisse AY, Gilchrist M, Galletly TJ, Brannigan ET, Holmes AHet al., 2020, Detecting carbapenemase-producing Enterobacterales (CPE): an evaluation of an enhanced CPE infection control and screening programme in acute care, JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY, Vol: 75, Pages: 2670-2676, ISSN: 0305-7453

Journal article

Borek AJ, Anthierens S, Allison R, McNulty CAM, Lecky DM, Costelloe C, Holmes A, Butler CC, Walker AS, Tonkin-Crine Set al., 2020, How did a Quality Premium financial incentive influence antibiotic prescribing in primary care? Views of Clinical Commissioning Group and general practice professionals, JOURNAL OF ANTIMICROBIAL CHEMOTHERAPY, Vol: 75, Pages: 2681-2688, ISSN: 0305-7453

Journal article

Boyd SE, Vasudevan A, Moore LSP, Brewer C, Gilchrist M, Costelloe C, Gordon AC, Holmes AHet al., 2020, Validating a prediction tool to determine the risk of nosocomial multidrug-resistant Gram-negative bacilli infection in critically ill patients: A retrospective case-control study, Journal of Global Antimicrobial Resistance, Vol: 22, Pages: 826-831, ISSN: 2213-7165

BACKGROUND: The Singapore GSDCS score was developed to enable clinicians predict the risk of nosocomial multidrug-resistant Gram-negative bacilli (RGNB) infection in critically ill patients. We aimed to validate this score in a UK setting. METHOD: A retrospective case-control study was conducted including patients who stayed for more than 24h in intensive care units (ICUs) across two tertiary National Health Service hospitals in London, UK (April 2011-April 2016). Cases with RGNB and controls with sensitive Gram-negative bacilli (SGNB) infection were identified. RESULTS: The derived GSDCS score was calculated from when there was a step change in antimicrobial therapy in response to clinical suspicion of infection as follows: prior Gram-negative organism, Surgery, Dialysis with end-stage renal disease, prior Carbapenem use and intensive care Stay of more than 5 days. A total of 110 patients with RGNB infection (cases) were matched 1:1 to 110 geotemporally chosen patients with SGNB infection (controls). The discriminatory ability of the prediction tool by receiver operating characteristic curve analysis in our validation cohort was 0.75 (95% confidence interval 0.65-0.81), which is comparable with the area under the curve of the derivation cohort (0.77). The GSDCS score differentiated between low- (0-1.3), medium- (1.4-2.3) and high-risk (2.4-4.3) patients for RGNB infection (P<0.001) in a UK setting. CONCLUSION: A simple bedside clinical prediction tool may be used to identify and differentiate patients at low, medium and high risk of RGNB infection prior to initiation of prompt empirical antimicrobial therapy in the intensive care setting.

Journal article

Zhu J, Ahmad R, Holmes A, Robotham J, Lebcir R, Atun Ret al., 2020, System dynamics modelling to formulate policy interventions to optimise antibiotic prescribing in hospitals, Journal of the Operational Research Society, ISSN: 0160-5682

Multiple strategies have been used in the National Health System (NHS) in England to reduce inappropriate antibiotic prescribing and consumption in order to tackle antimicrobial resistance. These strategies have included, among others, restricting dispensing, introduction of prescribing guidelines, use of clinical audit, and performance reviews as well as strategies aimed at changing the prescribing behaviour of clinicians. However, behavioural interventions have had limited effect in optimising doctors’ antibiotic prescribing practices. This study examines the determinants of decision-making for antibiotic prescribing in hospitals in the NHS. A system dynamics model was constructed to capture structural and behavioural influences to simulate doctors’ prescribing practices. Data from the literature, patient records, healthcare professional interviews and survey responses were used to parameterise the model. The scenario simulation shows maximum improvements in guideline compliance are achieved when compliance among senior staff is increased, combined with fast laboratory turnaround of blood cultures, and microbiologist review. Improving guideline compliance of junior staff alone has limited impact. This first use of system dynamics modelling to study antibiotic prescribing decision-making demonstrates the applicability of the methodology for design and evaluation of future policies and interventions.

Journal article

Conly J, Seto WH, Pittet D, Holmes A, Chu M, Hunter PRet al., 2020, Use of medical face masks versus particulate respirators as a component of personal protective equipment for health care workers in the context of the COVID-19 pandemic, ANTIMICROBIAL RESISTANCE AND INFECTION CONTROL, Vol: 9, ISSN: 2047-2994

Journal article

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