Comparing the Analysis and Results of a Modified Social Accounting Matrix Framework with Conventional Methods of Reporting Indirect Non-Medical Costs

Background Assessing the societal perspective in economic evaluations of new interventions requires estimates of indirect non-medical costs caused by the disease. Different methods exist for measuring the labor input function as a surrogate for these costs. They rarely specify the effect of health on labor and who gains and who loses money. Social accounting matrix (SAM) is an established framework that evaluates public policies with multiple perspectives that could help. Objectives We evaluated the use of a modified SAM to assess money flows between different economic agents resulting in economic transactions following policy changes of medical interventions. Methods We compared conventional methods of measuring indirect non-medical costs related to rotavirus vaccination in the Netherlands with a modified SAM framework. To compare the outcome of each method, we calculated returns on investment (ROI) as the net amount of money per euro invested in the vaccine. One-way and probabilistic sensitivity analyses were carried out for each method, focusing on critical variables with the largest impact on indirect cost estimates. Results The ROI was higher for the modified SAM (1.33) than for the conventional methods assessing income calculations (range - 0.178 to 1.22). Probabilistic sensitivity analyses showed wide distributions in the ROI estimates, with variation in the variable impact on the indirect cost results per method selected. Conclusions In contrast to conventional methods, the SAM approach provides detailed and comprehensive assessments of the impact of new interventions on the indirect non-medical costs and the financial interactions between agents, disclosing useful information for different stakeholders.</p

Feasibility of informing syndrome-level empiric antibiotic recommendations using publicly available antibiotic resistance datasets.

Background: Antibiotics are often prescribed empirically to treat infection syndromes before causative bacteria and their susceptibility to antibiotics are identified. Guidelines on empiric antibiotic prescribing are key to effective treatment of infection syndromes, and need to be informed by likely bacterial aetiology and antibiotic resistance patterns. We aimed to create a clinically-relevant composite index of antibiotic resistance for common infection syndromes to inform recommendations at the national level. Methods: To create our index, we used open-access antimicrobial resistance (AMR) surveillance datasets, including the ECDC Surveillance Atlas, CDDEP ResistanceMap, WHO GLASS and the newly-available Pfizer ATLAS dataset. We integrated these with data on aetiology of common infection syndromes, existing empiric prescribing guidelines, and pricing and availability of antibiotics. Results:  The ATLAS dataset covered many more bacterial species (287) and antibiotics (52) than other datasets (ranges = 8-11 and 16-32 respectively), but had a similar number of samples per country per year. Using these data, we were able to make empiric prescribing recommendations for bloodstream infection, pneumonia and cellulitis/skin abscess in up to 44 countries. There was insufficient data to make national-level recommendations for the other six syndromes investigated. Results are presented in an interactive web app, where users can visualise underlying resistance proportions to first-line empiric antibiotics for infection syndromes and countries of interest. Conclusions: We found that whilst the creation of a composite resistance index for empiric antibiotic therapy was technically feasible, the ATLAS dataset in its current form can only inform on a limited number of infection syndromes. Other open-access AMR surveillance datasets are largely limited to bloodstream infection specimens and cannot directly inform treatment of other syndromes. With improving availability of international AMR data and better understanding of infection aetiology, this approach may prove useful for informing empiric prescribing decisions in settings with limited local AMR surveillance data

Intraoperative MRI for the microsurgical resection of meningiomas close to eloquent areas or dural sinuses: patient series

BACKGROUND: Meningiomas are the most commonly encountered nonglial primary intracranial tumors. The authors report on the usefulness of intraoperative magnetic resonance imaging (iMRI) during microsurgical resection of meningiomas located close to eloquent areas or dural sinuses and on the feasibility of further radiation therapy. OBSERVATIONS: Six patients benefited from this approach. The mean follow-up period after surgery was 3.3 (median 3.2, range 2.1–4.6) years. Five patients had no postoperative neurological deficit, of whom two with preoperative motor deficit completely recovered. One patient with preoperative left inferior limb deficit partially recovered. The mean interval between surgery and radiation therapy was 15.8 (median 16.9, range 1.4–40.5) months. Additional radiation therapy was required in five cases after surgery. The mean preoperative tumor volume was 38.7 (median 27.5, range 8.6–75.6) mL. The mean postoperative tumor volume was 1.2 (median 0.8, range 0–4.3) mL. At the last follow-up, all tumors were controlled. LESSONS: The use of iMRI was particularly helpful to (1) decide on additional tumor resection according to iMRI findings during the surgical procedure; (2) evaluate the residual tumor volume at the end of the surgery; and (3) judge the need for further radiation and, in particular, the feasibility of single-fraction radiosurgery

Magnetic Screening of NbN Multilayers Samples

6 pagesInternational audienceIn 2006 Gurevich proposed to use nanoscale layers of superconducting materials with high values of Hc > Hc^Nb for magnetic shielding of bulk niobium to increase the breakdown magnetic field inside SC RF cavities [1]. We have deposited high quality "model" samples by magnetron sputtering on monocrystalline sapphire substrates. A 250 nm layer of niobium figures the bulk Nb. It was coated with a single and multi-stacks of NbN layers (25 or12 nm) separated by 15 nm MgO barriers, and characterized by X-Ray reflectivity and DC transport measurements. DC or AC measurement of HC1 is an important goal for multilayer evaluation during the sample evaluation phase. A clear increase of HC1 at low frequency is promising indication since HC1 is expected to increase with frequency (see e.g. [2] and references therein). We have measured the first penetration field (HP~HC1) on DC magnetization curves in a SQUID system. HP of NbN covered sample is increased compared to Nb alone. We have also developed a set-up that allows measuring a large range of field and temperature with a local probe method based on 3rd harmonic analysis. We have confirmed the screening behavior of a single 25 nm NbN layer placed on the top of a Nb Layer

Quantifying patient- and hospital-level antimicrobial resistance dynamics in Staphylococcus aureus from routinely collected data

Introduction. Antimicrobial resistance (AMR) to all antibiotic classes has been found in the pathogen Staphylococcus aureus . The reported prevalence of these resistances varies, driven by within-host AMR evolution at the patient level, and between-host transmission at the hospital level. Without dense longitudinal sampling, pragmatic analysis of AMR dynamics at multiple levels using routine surveillance data is essential to inform control measures. Gap Statement. The value and limitations of routinely collected hospital data to gain insight into AMR dynamics at the hospital and individual levels simultaneously are unclear. Methodology. We explored S. aureus AMR diversity in 70 000 isolates from a UK paediatric hospital between 2000–2021, using electronic datasets containing multiple routinely collected isolates per patient with phenotypic antibiograms and information on hospitalization and antibiotic consumption. Results. At the hospital level, the proportion of isolates that were meticillin-resistant (MRSA) increased between 2014–2020 from 25–50 %, before sharply decreasing to 30%, likely due to a change in inpatient demographics. Temporal trends in the proportion of isolates resistant to different antibiotics were often correlated in MRSA, but independent in meticillin-susceptible S. aureus . Ciprofloxacin resistance in MRSA decreased from 70–40 % of tested isolates between 2007–2020, likely linked to a national policy to reduce fluoroquinolone usage in 2007. At the patient level, we identified frequent AMR diversity, with 4 % of patients ever positive for S. aureus simultaneously carrying, at some point, multiple isolates with different resistances. We detected changes over time in AMR diversity in 3 % of patients ever positive for S. aureus . These changes equally represented gain and loss of resistance. Conclusion. Within this routinely collected dataset, we found that 65 % of changes in resistance within a patient’s S. aureus population could not be explained by antibiotic exposure or between-patient transmission of bacteria, suggesting that within-host evolution via frequent gain and loss of AMR genes may be responsible for these changing AMR profiles. Our study highlights the value of exploring existing routine surveillance data to determine underlying mechanisms of AMR. These insights may substantially improve our understanding of the importance of antibiotic exposure variation, and the success of single S. aureus clones

Modelling the synergistic effect of bacteriophage and antibiotics on bacteria: Killers and drivers of resistance evolution.

Bacteriophage (phage) are bacterial predators that can also spread antimicrobial resistance (AMR) genes between bacteria by generalised transduction. Phage are often present alongside antibiotics in the environment, yet evidence of their joint killing effect on bacteria is conflicted, and the dynamics of transduction in such systems are unknown. Here, we combine in vitro data and mathematical modelling to identify conditions where phage and antibiotics act in synergy to remove bacteria or drive AMR evolution. We adapt a published model of phage-bacteria dynamics, including transduction, to add the pharmacodynamics of erythromycin and tetracycline, parameterised from new in vitro data. We simulate a system where two strains of Staphylococcus aureus are present at stationary phase, each carrying either an erythromycin or tetracycline resistance gene, and where multidrug-resistant bacteria can be generated by transduction only. We determine rates of bacterial clearance and multidrug-resistant bacteria appearance, when either or both antibiotics and phage are present at varying timings and concentrations. Although phage and antibiotics act in synergy to kill bacteria, by reducing bacterial growth antibiotics reduce phage production. A low concentration of phage introduced shortly after antibiotics fails to replicate and exert a strong killing pressure on bacteria, instead generating multidrug-resistant bacteria by transduction which are then selected for by the antibiotics. Multidrug-resistant bacteria numbers were highest when antibiotics and phage were introduced simultaneously. The interaction between phage and antibiotics leads to a trade-off between a slower clearing rate of bacteria (if antibiotics are added before phage), and a higher risk of multidrug-resistance evolution (if phage are added before antibiotics), exacerbated by low concentrations of phage or antibiotics. Our results form hypotheses to guide future experimental and clinical work on the impact of phage on AMR evolution, notably for studies of phage therapy which should investigate varying timings and concentrations of phage and antibiotics

What settings have been linked to SARS-CoV-2 transmission clusters?

Background: Concern about the health impact of novel coronavirus SARS-CoV-2 has resulted in widespread enforced reductions in people's movement ("lockdowns"). However, there are increasing concerns about the severe economic and wider societal consequences of these measures. Some countries have begun to lift some of the rules on physical distancing in a stepwise manner, with differences in what these "exit strategies" entail and their timeframes. The aim of this work was to inform such exit strategies by exploring the types of indoor and outdoor settings where transmission of SARS-CoV-2 has been reported to occur and result in clusters of cases. Identifying potential settings that result in transmission clusters allows these to be kept under close surveillance and/or to remain closed as part of strategies that aim to avoid a resurgence in transmission following the lifting of lockdown measures. Methods: We performed a systematic review of available literature and media reports to find settings reported in peer reviewed articles and media with these characteristics. These sources are curated and made available in an editable online database. Results: We found many examples of SARS-CoV-2 clusters linked to a wide range of mostly indoor settings. Few reports came from schools, many from households, and an increasing number were reported in hospitals and elderly care settings across Europe. Conclusions: We identified possible places that are linked to clusters of COVID-19 cases and could be closely monitored and/or remain closed in the first instance following the progressive removal of lockdown restrictions. However, in part due to the limits in surveillance capacities in many settings, the gathering of information such as cluster sizes and attack rates is limited in several ways: inherent recall bias, biased media reporting and missing data

Antimicrobial resistance and COVID-19: Intersections and implications

Before the coronavirus 2019 (COVID-19) pandemic began, antimicrobial resistance (AMR) was among the top priorities for global public health. Already a complex challenge, AMR now needs to be addressed in a changing healthcare landscape. Here, we analyse how changes due to COVID-19 in terms of antimicrobial usage, infection prevention, and health systems affect the emergence, transmission, and burden of AMR. Increased hand hygiene, decreased international travel, and decreased elective hospital procedures may reduce AMR pathogen selection and spread in the short term. However, the opposite effects may be seen if antibiotics are more widely used as standard healthcare pathways break down. Over 6 months into the COVID-19 pandemic, the dynamics of AMR remain uncertain. We call for the AMR community to keep a global perspective while designing finely tuned surveillance and research to continue to improve our preparedness and response to these intersecting public health challenges

Analysis of temporal trends in potential COVID-19 cases reported through NHS Pathways England.

The National Health Service (NHS) Pathways triage system collates data on enquiries to 111 and 999 services in England. Since the 18th of March 2020, these data have been made publically available for potential COVID-19 symptoms self-reported by members of the public. Trends in such reports over time are likely to reflect behaviour of the ongoing epidemic within the wider community, potentially capturing valuable information across a broader severity profile of cases than hospital admission data. We present a fully reproducible analysis of temporal trends in NHS Pathways reports until 14th May 2020, nationally and regionally, and demonstrate that rates of growth/decline and effective reproduction number estimated from these data may be useful in monitoring transmission. This is a particularly pressing issue as lockdown restrictions begin to be lifted and evidence of disease resurgence must be constantly reassessed. We further assess the correlation between NHS Pathways reports and a publicly available NHS dataset of COVID-19-associated deaths in England, finding that enquiries to 111/999 were strongly associated with daily deaths reported 16 days later. Our results highlight the potential of NHS Pathways as the basis of an early warning system. However, this dataset relies on self-reported symptoms, which are at risk of being severely biased. Further detailed work is therefore necessary to investigate potential behavioural issues which might otherwise explain our conclusions