Publications
440 results found
Charani E, McKee M, Ahmad R, et al., 2021, Optimising antimicrobial use in humans-review of current evidence and an interdisciplinary consensus on key priorities for research, The Lancet Regional Health - Europe, Vol: 7, Pages: 1-10, ISSN: 2666-7762
Addressing the silent pandemic of antimicrobial resistance (AMR) is a focus of the 2021 G7 meeting. A major driver of AMR and poor clinical outcomes is suboptimal antimicrobial use. Current research in AMR is inequitably focused on new drug development. To achieve antimicrobial security we need to balance AMR research efforts between development of new agents and strategies to preserve the efficacy and maximise effectiveness of existing agents.Combining a review of current evidence and multistage engagement with diverse international stakeholders (including those in healthcare, public health, research, patient advocacy and policy) we identified research priorities for optimising antimicrobial use in humans across four broad themes: policy and strategic planning; medicines management and prescribing systems; technology to optimise prescribing; and context, culture and behaviours. Sustainable progress depends on: developing economic and contextually appropriate interventions; facilitating better use of data and prescribing systems across healthcare settings; supporting appropriate and scalable technological innovation. Implementing this strategy for AMR research on the optimisation of antimicrobial use in humans could contribute to equitable global health security.
Petersen E, Lee SS, Blumberg L, et al., 2021, International Journal of Infectious Diseases: from the past quarter-century to the next, INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES, Vol: 109, Pages: 36-37, ISSN: 1201-9712
Zhu NJ, Rawson TM, Mookerjee S, et al., 2021, Changing patterns of bloodstream infections in the community and in acute care across two COVID-19 epidemic waves: a retrospective analysis
<jats:title>Abstract</jats:title> <jats:p><jats:bold>Introduction </jats:bold>We examined the epidemiology of community- and hospital-acquired bloodstream infections (BSIs) in COVID-19 and non-COVID-19 patients across two epidemic waves. <jats:bold>Methods </jats:bold>We analysed blood cultures, SARS-CoV-2 tests, and hospital episodes of patients presenting and admitted to a London hospital group between January 2020 and February 2021. We reported BSI incidence, as well as changes in sampling, case mix, bed and staff capacity, and COVID-19 variants. <jats:bold>Results </jats:bold>34,044 blood cultures were taken. We identified 1,047 BSIs; 653 (62.4%) defined epidemiologically as community-acquired and 394 (37.6%) as hospital-acquired. BSI rates and community / hospital ratio were similar to those pre-pandemic. However, important changes in patterns were seen. Among community-acquired BSIs, <jats:italic>Escherichia coli</jats:italic> BSIs remained lower than pre-pandemic level during the two COVID-19 waves, however peaked following lockdown easing in May 2020, deviating from the historical trend of peaking in August. The hospital-acquired BSI rate was 100.4 per 100,000 patient-days across the pandemic, increasing to 132.3 during the first COVID-19 wave and 190.9 during the second, with significant increase seen in elective non-COVID-19 inpatients. Patients who developed a hospital-acquired BSI, including those without COVID-19, experienced 20.2 excess days of hospital stay and 26.7% higher mortality, higher than reported in pre-pandemic literature. In intensive care units (ICUs), the overall BSI rate was 311.8 per 100,000 patient-ICU days, increasing to 421.0 during the second wave, compared to 101.3 pre-COVID. The BSI incidence in those infected with the SARS-CoV-2 Alpha variant was similar to that seen with earlier variants. <jats:bold>Conclusion </jats:bold>The pandemic and nation
Ahmad R, Atun R, Birgand G, et al., 2021, Macro level influences on strategic responses to the COVID-19 pandemic – an international survey and tool for national assessments, Journal of Global Health, Vol: 11, Pages: 1-11, ISSN: 2047-2978
Background Variation in the approaches taken to contain the SARS-CoV-2 (COVID-19) pandemic at country level has been shaped by economic and political considerations, technical capacity, and assumptions about public behaviours. To address the limited application of learning from previous pandemics, this study aimed to analyse perceived facilitators and inhibitors during the pandemic and to inform the development of an assessment tool for pandemic response planning.Methods A cross-sectional electronic survey of health and non-healthcare professionals (5 May - 5 June 2020) in six languages, with respondents recruited via email, social media and website posting. Participants were asked to score inhibitors (-10 to 0) or facilitators (0 to +10) impacting country response to COVID-19 from the following domains – Political, Economic, Sociological, Technological, Ecological, Legislative, and wider Industry (the PESTELI framework). Participants were then asked to explain their responses using free text. Descriptive and thematic analysis was followed by triangulation with the literature and expert validation to develop the assessment tool, which was then compared with four existing pandemic planning frameworks.Results 928 respondents from 66 countries (57% healthcare professionals) participated. Political and economic influences were consistently perceived as powerful negative forces and technology as a facilitator across high- and low-income countries. The 103-item tool developed for guiding rapid situational assessment for pandemic planning is comprehensive when compared to existing tools and highlights the interconnectedness of the 7 domains. Conclusions The tool developed and proposed addresses the problems associated with decision making in disciplinary silos and offers a means to refine future use of epidemic modelling.
Zhu J, Ferlie E, Castro-Sánchez E, et al., 2021, Macro level factors influencing strategic responses to emergent pandemics: a scoping review, Journal of Global Health, Vol: 11, Pages: 1-16, ISSN: 2047-2978
Background: Strategic planning is critical for successful pandemic management. This study aimed to identify and review the scope and analytic depth of situation analyses conducted to understand their utility, and capture the documented macro-level factors impacting4pandemic management. Methods: To synthesise this disparate body of literature, we adopted a two-step search and 6review process. A systematic search of the literature was conducted to identify all studies since 2000, that have 1) employed a situation analysis;and2) examined contextual factors influencing pandemic management. The included studies are analysed using a seven-domain systems approach rom the discipline of strategic management. Findings: Nineteen studies were included in the final review ranging from single country (6) to regional, multi-country studies (13). Fourteen studies had a single disease focus, with 5 studies evaluating responses to one or more of COVID-19, Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS),Influenza A (H1N1),Ebola virus disease, and Zika virus disease pandemics. Six studies examined a single domain from political, economic, sociological, technological, ecological or wider industry(PESTELI), 5 studies examined two to four domains, and8studies examined five or more domains. Methods employed were predominantly literature reviews. The recommendations focus predominantly on addressing inhibitors in the sociological and technological domains with few recommendations articulated in the political domain. Overall, the legislative domain is least represented. Conclusions: Ex-post analysis using the seven-domain strategic management framework provides further opportunities for a planned systematic response to pandemics which remains critical as the current COVID-19 pandemic evolves.
Sangkaew S, Ming D, Boonyasiri A, et al., 2021, Risk predictors of progression to severe disease during the febrile phase of dengue: a systematic review and meta-analysis, Lancet Infectious Diseases, Vol: 21, Pages: 1014-1026, ISSN: 1473-3099
BACKGROUND: The ability to accurately predict early progression of dengue to severe disease is crucial for patient triage and clinical management. Previous systematic reviews and meta-analyses have found significant heterogeneity in predictors of severe disease due to large variation in these factors during the time course of the illness. We aimed to identify factors associated with progression to severe dengue disease that are detectable specifically in the febrile phase. METHODS: We did a systematic review and meta-analysis to identify predictors identifiable during the febrile phase associated with progression to severe disease defined according to WHO criteria. Eight medical databases were searched for studies published from Jan 1, 1997, to Jan 31, 2020. Original clinical studies in English assessing the association of factors detected during the febrile phase with progression to severe dengue were selected and assessed by three reviewers, with discrepancies resolved by consensus. Meta-analyses were done using random-effects models to estimate pooled effect sizes. Only predictors reported in at least four studies were included in the meta-analyses. Heterogeneity was assessed using the Cochrane Q and I2 statistics, and publication bias was assessed by Egger's test. We did subgroup analyses of studies with children and adults. The study is registered with PROSPERO, CRD42018093363. FINDINGS: Of 6643 studies identified, 150 articles were included in the systematic review, and 122 articles comprising 25 potential predictors were included in the meta-analyses. Female patients had a higher risk of severe dengue than male patients in the main analysis (2674 [16·2%] of 16 481 vs 3052 [10·5%] of 29 142; odds ratio [OR] 1·13 [95% CI 1·01-1·26) but not in the subgroup analysis of studies with children. Pre-existing comorbidities associated with severe disease were diabetes (135 [31·3%] of 431 with vs 868 [16·0%] of 5421 witho
Stirrup OT, Boshier FAT, Venturini C, et al., 2021, SARS-CoV-2 lineage B.1.1.7 is associated with greater disease severity among hospitalised women but not men
<jats:title>Abstract</jats:title><jats:sec><jats:title>Background</jats:title><jats:p>Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage B.1.1.7 has been associated with an increased rate of transmission and disease severity among subjects testing positive in the community. Its impact on hospitalised patients is less well documented.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>We collected viral sequences and clinical data of patients admitted with SARS-CoV-2 and hospital-onset COVID-19 infections (HOCIs), sampled 16/11/2020 - 10/01/2021, from eight hospitals participating in the COG-UK-HOCI study. Associations between the variant and the outcomes of all-cause mortality and intensive therapy unit (ITU) admission were evaluated using mixed effects Cox models adjusted by age, sex, comorbidities, care home residence, pregnancy and ethnicity.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Sequences were obtained from 2341 inpatients (HOCI cases = 786) and analysis of clinical outcomes was carried out in 2147 inpatients with all data available. The hazard ratio (HR) for mortality of B.1.1.7 compared to other lineages was 1.01 (95% CI 0.79-1.28, P=0.94) and for ITU admission was 1.01 (95% CI 0.75-1.37, P=0.96). Analysis of sex-specific effects of B.1.1.7 identified increased risk of mortality (HR 1.30, 95% CI 0.95-1.78) and ITU admission (HR 1.82, 95% CI 1.15-2.90) in females infected with the variant but not males (mortality HR 0.82, 95% CI 0.61-1.10; ITU HR 0.74, 95% CI 0.52-1.04).</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>In common with smaller studies of patients hospitalised with SARS-CoV-2 we did not find an overall increase in mortality or ITU admission associated with B.1.1.7 compared to other lineages. However, women with B.1.1
Rawson TM, Hernandez B, Moore L, et al., 2021, A real-world evaluation of a case-based reasoning algorithm to support antimicrobial prescribing decisions in acute care, Clinical Infectious Diseases, Vol: 72, Pages: 2103-2111, ISSN: 1058-4838
BackgroundA locally developed Case-Based Reasoning (CBR) algorithm, designed to augment antimicrobial prescribing in secondary care was evaluated.MethodsPrescribing recommendations made by a CBR algorithm were compared to decisions made by physicians in clinical practice. Comparisons were examined in two patient populations. Firstly, in patients with confirmed Escherichia coli blood stream infections (‘E.coli patients’), and secondly in ward-based patients presenting with a range of potential infections (‘ward patients’). Prescribing recommendations were compared against the Antimicrobial Spectrum Index (ASI) and the WHO Essential Medicine List Access, Watch, Reserve (AWaRe) classification system. Appropriateness of a prescription was defined as the spectrum of the prescription covering the known, or most-likely organism antimicrobial sensitivity profile.ResultsIn total, 224 patients (145 E.coli patients and 79 ward patients) were included. Mean (SD) age was 66 (18) years with 108/224 (48%) female gender. The CBR recommendations were appropriate in 202/224 (90%) compared to 186/224 (83%) in practice (OR: 1.24 95%CI:0.392-3.936;p=0.71). CBR recommendations had a smaller ASI compared to practice with a median (range) of 6 (0-13) compared to 8 (0-12) (p<0.01). CBR recommendations were more likely to be classified as Access class antimicrobials compared to physicians’ prescriptions at 110/224 (49%) vs. 79/224 (35%) (OR: 1.77 95%CI:1.212-2.588 p<0.01). Results were similar for E.coli and ward patients on subgroup analysis.ConclusionsA CBR-driven decision support system provided appropriate recommendations within a narrower spectrum compared to current clinical practice. Future work must investigate the impact of this intervention on prescribing behaviours more broadly and patient outcomes.
Rodriguez-Bano J, Rossolini GM, Schultsz C, et al., 2021, Antimicrobial resistance research in a post-pandemic world: Insights on antimicrobial resistance research in the COVID-19 pandemic, JOURNAL OF GLOBAL ANTIMICROBIAL RESISTANCE, Vol: 25, Pages: 5-7, ISSN: 2213-7165
- Author Web Link
- Cite
- Citations: 22
Myall AC, Peach RL, Weiße AY, et al., 2021, Network memory in the movement of hospital patients carrying drug-resistant bacteria, Applied Network Science, Vol: 6, ISSN: 2364-8228
Hospitals constitute highly interconnected systems that bring into contact anabundance of infectious pathogens and susceptible individuals, thus makinginfection outbreaks both common and challenging. In recent years, there hasbeen a sharp incidence of antimicrobial-resistance amongsthealthcare-associated infections, a situation now considered endemic in manycountries. Here we present network-based analyses of a data set capturing themovement of patients harbouring drug-resistant bacteria across three largeLondon hospitals. We show that there are substantial memory effects in themovement of hospital patients colonised with drug-resistant bacteria. Suchmemory effects break first-order Markovian transitive assumptions andsubstantially alter the conclusions from the analysis, specifically on noderankings and the evolution of diffusive processes. We capture variable lengthmemory effects by constructing a lumped-state memory network, which we then useto identify overlapping communities of wards. We find that these communities ofwards display a quasi-hierarchical structure at different levels of granularitywhich is consistent with different aspects of patient flows related to hospitallocations and medical specialties.
Zhu N, Aylin P, Rawson T, et al., 2021, Investigating the impact of COVID-19 on primary care antibiotic prescribing in North West London across two epidemic waves, Clinical Microbiology and Infection, Vol: 27, Pages: 762-768, ISSN: 1198-743X
ObjectivesWe investigated the impact of COVID-19 and national pandemic response on primary care antibiotic prescribing in London.MethodsIndividual 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.ResultsRecords 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.DiscussionA sustained reduction in community antibiotic prescribing has been observed since the first lockdown. Investigation of community-onset infectious diseases and potential unintended consequences of reduced prescribing is urgently needed.
Huttner A, Bricheux A, Buurmeijer-van Dijk CJM, et 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, CLINICAL MICROBIOLOGY AND INFECTION, Vol: 27, Pages: 704-707, ISSN: 1198-743X
- Author Web Link
- Cite
- Citations: 3
Miglietta L, Moniri A, Pennisi I, et al., 2021, Coupling machine learning and high throughput multiplex digital PCR enables accurate detection of carbapenem-resistant genes in clinical isolates, Publisher: Cold Spring Harbor Laboratory
<jats:p>Background: The emergence and spread of carbapenemase-producing organisms (CPO) are a significant clinical and public health concern. Rapid and accurate identification of patients colonised with CPO is essential to adopt prompt prevention measures in order to reduce the risk of transmission. Recent proof-of-concept studies have demonstrated the ability to combine machine learning (ML) algorithms with real-time digital PCR (dPCR) instruments to increase classification accuracy of multiplex assays. From this, we sought to determine if this ML based methodology could accurately identify five major carbapenem-resistant genes in clinical CPO-isolates.Methods: We collected 253 clinical isolates (including 221 CPO-positive samples) and developed a novel 5-plex assay for detection of blaVIM, blaOXA-48, blaNDM, blaIMP and blaKPC. Combining the recently reported ML method "Amplification and Melting Curve Analysis" (AMCA) with the abovementioned multiplex assay, we assessed the performance of the methodology in detecting these five carbapenem-resistant genes. The classification accuracy relies on the usage of real-time data from a single fluorescent channel and benefits from the kinetic and thermodynamic information encoded in the thousands of amplification events produced by high throughput dPCR.Results: The 5-plex showed a lower limit of detection of 100 DNA copies per reaction for each primer set and no cross-reactivity with other carbapenemase genes. The AMCA classifier demonstrated excellent predictive performance with 99.6% (CI 97.8-99.9%) accuracy (only one misclassified sample out of the 253, with a total of 163,966 positive amplification events), which represents a 7.9% increase compared to the conventional ML-based melting curve analysis (MCA) method.Conclusion: This work demonstrates the utility of the AMCA method to increase the throughput and performance of state-of-the-art molecular diagnostic platforms, reducing costs without any changes
Myall A, Peach RL, Wan Y, et al., 2021, Characterising contact in disease outbreaks via a network model of spatial-temporal proximity
<jats:title>ABSTRACT</jats:title><jats:p>Contact tracing is a key tool in epidemiology to identify and control outbreaks of infectious diseases. Existing contact tracing methodologies produce contact maps of individuals based on a binary definition of contact which can be hampered by missing data and indirect contacts. Here, we present a Spatial-temporal Epidemiological Proximity (StEP) model to recover contact maps in disease outbreaks based on movement data. The StEP model accounts for imperfect data by considering probabilistic contacts between individuals based on spatial-temporal proximity of their movement trajectories, creating a robust movement network despite possible missing data and unseen transmission routes. Using real-world data we showcase the potential of StEP for contact tracing with outbreaks of multidrug-resistant bacteria and COVID-19 in a large hospital group in London, UK. In addition to the core structure of contacts that can be recovered using traditional methods of contact tracing, the StEP model reveals missing contacts that connect seemingly separate outbreaks. Comparison with genomic data further confirmed that these recovered contacts indeed improve characterisation of disease transmission and so highlights how the StEP framework can inform effective strategies of infection control and prevention.</jats:p>
Petersen E, Lucey D, Blumberg L, et al., 2021, Answer to Paredes et al. commenting on "COVID-19 vaccines under the International Health Regulations - We must use the WHO International Certificate of Vaccination or Prophylaxis", INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES, Vol: 105, Pages: 409-410, ISSN: 1201-9712
Rawson TM, Hernandez B, Wilson R, et 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.
Petersen E, Lucey D, Blumberg L, et al., 2021, COVID-19 vaccines under the International Health Regulations - We must use the WHO International Certificate of Vaccination or Prophylaxis, INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES, Vol: 104, Pages: 175-177, ISSN: 1201-9712
- Author Web Link
- Cite
- Citations: 17
Rodriguez-Manzano J, Malpartida-Cardenas K, Moser N, et al., 2021, Handheld point-of-care system for rapid detection of SARS-CoV-2 extracted RNA in under 20 min, ACS Central Science, Vol: 7, Pages: 307-317, 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.
Ahmad R, Atun R, Birgand G, et al., 2021, Macro Level Influences on Strategic Responses to the COVID-19 Pandemic - A Tool for National Assessments, Journal of Global Health, ISSN: 2047-2978
Borek AJ, Campbell A, Dent E, et al., 2021, Implementing interventions to reduce antibiotic use: a qualitative study in high-prescribing practices, BMC Family Practice, Vol: 22, ISSN: 1471-2296
BackgroundTrials have shown that delayed antibiotic prescriptions (DPs) and point-of-care C-Reactive Protein testing (POC-CRPT) are effective in reducing antibiotic use in general practice, but these were not typically implemented in high-prescribing practices. We aimed to explore views of professionals from high-prescribing practices about uptake and implementation of DPs and POC-CRPT to reduce antibiotic use.MethodsThis was a qualitative focus group study in English general practices. The highest antibiotic prescribing practices in the West Midlands were invited to participate. Clinical and non-clinical professionals attended focus groups co-facilitated by two researchers. Focus groups were audio-recorded, transcribed verbatim and analysed thematically.ResultsNine practices (50 professionals) participated. Four main themes were identified. Compatibility of strategies with clinical roles and experience – participants viewed the strategies as having limited value as ‘clinical tools’, perceiving them as useful only in ‘rare’ instances of clinical uncertainty and/or for those less experienced. Strategies as ‘social tools’ – participants perceived the strategies as helpful for negotiating treatment decisions and educating patients, particularly those expecting antibiotics. Ambiguities – participants perceived ambiguities around when they should be used, and about their impact on antibiotic use. Influence of context – various other situational and practical issues were raised with implementing the strategies.ConclusionsHigh-prescribing practices do not view DPs and POC-CRPT as sufficiently useful ‘clinical tools’ in a way which corresponds to the current policy approach advocating their use to reduce clinical uncertainty and improve antimicrobial stewardship. Instead, policy attention should focus on how these strategies may instead be used as ‘social tools’ to reduce unnecessary antibio
Price JR, Mookerjee S, Dyakova E, et 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.
Zhu NJ, McLeod M, McNulty CAM, et 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
- Author Web Link
- Cite
- Citations: 16
Abbas M, Abbas M, Zhu NJ, et al., 2021, Hospital-onset COVID-19 infection surveillance systems: a systematic review, Journal of Hospital Infection
Bawab N, Moullin JC, Bugnon O, et al., 2020, Proceedings of the Virtual 3rd UK Implementation Science Research Conference : Virtual conference. 16 and 17 July 2020., Implement Sci, Vol: 15
Ahuja S, Godwin G, Birgand G, et 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
Mbamalu O, Bonaconsa C, Boutall A, et al., 2020, 'A special antibiotic for that virus' - Patient understanding and participation in antibiotic and infection-related care in surgical teams, Publisher: ELSEVIER SCI LTD, Pages: 99-99, ISSN: 1201-9712
Zhu N, Sanchez EC, Zhen X, et al., 2020, Addressing antimicrobial resistance in China: progress and challenges in translating political commitment into national action, Publisher: ELSEVIER SCI LTD, Pages: 212-212, ISSN: 1201-9712
Castro-Sanchez E, Surendran S, Nampoothiri V, et 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
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
Bonaconsa C, Mbamalu O, Boutall A, et al., 2020, Investigating team dynamics and communication in surgical teams in relation to antibiotic prescribing and infection control, Publisher: ELSEVIER SCI LTD, Pages: 90-90, ISSN: 1201-9712
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.