Influencing attitudes towards antimicrobial use and resistance in companion animals-the impact on pet owners of a short animation in a randomized controlled trial.

Objectives: Antimicrobial resistance (AMR) is a vital One Health issue; the rational use of antimicrobials is essential to preserve their efficacy. Veterinarians cite pressure from pet owners as a contributor to antimicrobial prescription. Engaging pet owners in antimicrobial stewardship could reduce this pressure. A short educational animation could facilitate communication of this message. The impact of the animation on participant's opinions relating to antimicrobial prescribing and awareness of AMR was assessed via a randomized controlled trial. Methods: A survey was created based on the health belief model. Owners attending six UK veterinary centres were randomized to the intervention or control group (ratio 1:1). All owners completed an agreement level survey of two questions followed by 18 statements scored using a Likert agreement scale. The control group responded without interruption, whereas the animation group was shown the animation after answering the first two questions and five statements. Results: In total, 647 owners participated in the study; 350 complete responses were analysed. Responses to 10 of 13 statements asked after the animation were significantly different (all P < 0.050) between groups, whereas there was no significant difference between groups in response to any of the statements asked before the animation. The animation group were more likely to agree that lower antimicrobial use would help maintain future efficacy (P < 0.001) and that requesting antimicrobials from their vet could increase unnecessary use (P < 0.001). The animation group were more likely to disagree that they would expect antimicrobials if their pet had diarrhoea (P = 0.048). Conclusions: Pet owners that watched a short AMR engagement animation displayed greater awareness of the impact of AMR and were more likely to support measures in line with antimicrobial stewardship. This behavioural-nudge resource could support owners towards contributing to a multi-faceted approach to AMR.

Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

BACKGROUND: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies. OBJECTIVE: The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back-worn inertial sensors. METHODS: Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back-worn inertial sensors. RESULTS: The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids. CONCLUSIONS: Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health. TRIAL REGISTRATION: ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-050785.

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device.

This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and - 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application.Trial registration: ISRCTN - 12246987.

Risk factors for tick attachment in companion animals in Great Britain: a spatiotemporal analysis covering 2014-2021.

BACKGROUND: Ticks are an important driver of veterinary health care, causing irritation and sometimes infection to their hosts. We explored epidemiological and geo-referenced data from > 7 million electronic health records (EHRs) from cats and dogs collected by the Small Animal Veterinary Surveillance Network (SAVSNET) in Great Britain (GB) between 2014 and 2021 to assess the factors affecting tick attachment in an individual and at a spatiotemporal level. METHODS: EHRs in which ticks were mentioned were identified by text mining; domain experts confirmed those with ticks on the animal. Tick presence/absence records were overlaid with a spatiotemporal series of climate, environment, anthropogenic and host distribution factors to produce a spatiotemporal regression matrix. An ensemble machine learning spatiotemporal model was used to fine-tune hyperparameters for Random Forest, Gradient-boosted Trees and Generalized Linear Model regression algorithms, which were then used to produce a final ensemble meta-learner to predict the probability of tick attachment across GB at a monthly interval and averaged long-term through 2014-2021 at a spatial resolution of 1 km. Individual host factors associated with tick attachment were also assessed by conditional logistic regression on a matched case-control dataset. RESULTS: In total, 11,741 consultations were identified in which a tick was recorded. The frequency of tick records was low (0.16% EHRs), suggesting an underestimation of risk. That said, increased odds for tick attachment in cats and dogs were associated with younger adult ages, longer coat length, crossbreeds and unclassified breeds. In cats, males and entire animals had significantly increased odds of recorded tick attachment. The key variables controlling the spatiotemporal risk for tick attachment were climatic (precipitation and temperature) and vegetation type (Enhanced Vegetation Index). Suitable areas for tick attachment were predicted across GB, especially in forests and grassland areas, mainly during summer, particularly in June. CONCLUSIONS: Our results can inform targeted health messages to owners and veterinary practitioners, identifying those animals, seasons and areas of higher risk for tick attachment and allowing for more tailored prophylaxis to reduce tick burden, inappropriate parasiticide treatment and potentially TBDs in companion animals and humans. Sentinel networks like SAVSNET represent a novel complementary data source to improve our understanding of tick attachment risk for companion animals and as a proxy of risk to humans.

A mixed-methods approach utilising electronic health records to examine antimicrobial prescription surrounding gastrointestinal clinical presentations in dogs and cats.

Introduction: Systemically-administered antimicrobials are often prescribed in canine and feline gastrointestinal clinical presentations. Responsible use of antimicrobials, particularly those considered Highest Priority Critically Important Antimicrobials (HPCIAs) is vital to tackle antimicrobial resistance. Although practice-level prescription guidance is available, further strategies based on a greater understanding of antimicrobial prescription at the population-level are needed. Here, we used a mixed-methods approach, harnessing veterinary electronic health records (EHRs) to characterise the use of antimicrobials in canine and feline gastrointestinal presentations, and to explore justification and reasoning around antimicrobial prescribing, particularly of HPCIAs. Methods: This observational study used 23,337 EHRs complemented with veterinary practitioner-completed questionnaires, from canine and feline gastrointestinal consultations from 225 volunteer UK veterinary practices between April 2014 and September 2018. Results: A total of 83.4% (95% confidence interval (CI) 82.6-84.3) gastrointestinal presentations were reported as mild, with non-haemorrhagic diarrhoea and vomiting the most frequently reported clinical signs. Systemically-administered antimicrobials occurred in 28.6% of canine (95% CI 26.9-30.3) and 22.4% of feline (95% CI 20.4-24.4) gastrointestinal consultations, with HPCIA prescription occurring more frequently in cats. Results of multivariable analysis showed the presence of non-haemorrhagic diarrhoea (canine Odds Ratio (OR) 2.1, 95% CI 1.9-2.3; feline OR 1.8, 95% CI 1.5-2.1), haemorrhagic diarrhoea (canine OR 4.2, 95% CI 3.8-4.7; feline OR 3.1, 95% CI 2.4-3.8), and moderate/severe presentations (canine OR 1.9, 95% CI 1.7-2.8; feline OR 2.0, 95% CI 1.7-2.5) were positively associated with receiving a systemically-administered antimicrobial. Thematic analysis of clinical narrative content of 516 gastrointestinal consultations where HPCIAs were prescribed allowed the identification of ten factors underpinning reasoning or decision-making for HPCIA prescription: perceived animal/owner compliance; owner's expectations; perceived risk of infection; clinical signs; recent clinical history; perceived positive previous response to antimicrobial therapy; geriatric patients and euthanasia; concomitant conditions; diagnostic testing and the behavioral trend to trial antimicrobial therapy empirically in gastrointestinal cases. No explicit justification for HPCIA prescription was recorded in 77% of cases. Discussion: Improving recorded justification represents a clear target for stewardship programmes. By utilising a complementary mixed-methods approach to EHRs, this study unlocks previously untapped data recorded within EHRs. These results can help inform targeted interventions, contributing towards enhanced antimicrobial stewardship.

Exploiting genomics for antimicrobial resistance surveillance at One Health interfaces.

The intersection of human, animal, and ecosystem health at One Health interfaces is recognised as being of key importance in the evolution and spread of antimicrobial resistance (AMR) and represents an important, and yet rarely realised opportunity to undertake vital AMR surveillance. A working group of international experts in pathogen genomics, AMR, and One Health convened to take part in a workshop series and online consultation focused on the opportunities and challenges facing genomic AMR surveillance in a range of settings. Here we outline the working group's discussion of the potential utility, advantages of, and barriers to, the implementation of genomic AMR surveillance at One Health interfaces and propose a series of recommendations for addressing these challenges. Embedding AMR surveillance at One Health interfaces will require the development of clear beneficial use cases, especially in low-income and middle-income countries. Evidence of directionality, risks to human and animal health, and potential trade implications were also identified by the working group as key issues. Addressing these challenges will be vital to enable genomic surveillance technology to reach its full potential for assessing the risk of transmission of AMR between the environment, animals, and humans at One Health interfaces.

Ecological validity of a deep learning algorithm to detect gait events from real-life walking bouts in mobility-limiting diseases.

Introduction: The clinical assessment of mobility, and walking specifically, is still mainly based on functional tests that lack ecological validity. Thanks to inertial measurement units (IMUs), gait analysis is shifting to unsupervised monitoring in naturalistic and unconstrained settings. However, the extraction of clinically relevant gait parameters from IMU data often depends on heuristics-based algorithms that rely on empirically determined thresholds. These were mainly validated on small cohorts in supervised settings. Methods: Here, a deep learning (DL) algorithm was developed and validated for gait event detection in a heterogeneous population of different mobility-limiting disease cohorts and a cohort of healthy adults. Participants wore pressure insoles and IMUs on both feet for 2.5 h in their habitual environment. The raw accelerometer and gyroscope data from both feet were used as input to a deep convolutional neural network, while reference timings for gait events were based on the combined IMU and pressure insoles data. Results and discussion: The results showed a high-detection performance for initial contacts (ICs) (recall: 98%, precision: 96%) and final contacts (FCs) (recall: 99%, precision: 94%) and a maximum median time error of -0.02 s for ICs and 0.03 s for FCs. Subsequently derived temporal gait parameters were in good agreement with a pressure insoles-based reference with a maximum mean difference of 0.07, -0.07, and <0.01 s for stance, swing, and stride time, respectively. Thus, the DL algorithm is considered successful in detecting gait events in ecologically valid environments across different mobility-limiting diseases.

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium.

BACKGROUND: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection, foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates. METHODS: Twenty healthy older adults, 20 people with Parkinson's disease, 20 with multiple sclerosis, 19 with proximal femoral fracture, 17 with chronic obstructive pulmonary disease and 12 with congestive heart failure were monitored for 2.5 h in the real-world, using a single wearable device worn on the lower back. A reference system combining inertial modules with distance sensors and pressure insoles was used for comparison of DMOs from the single wearable device. We assessed and validated three algorithms for gait sequence detection, four for ICD, three for CAD and four for SL by concurrently comparing their performances (e.g., accuracy, specificity, sensitivity, absolute and relative errors). Additionally, the effects of walking bout (WB) speed and duration on algorithm performance were investigated. RESULTS: We identified two cohort-specific top performing algorithms for gait sequence detection and CAD, and a single best for ICD and SL. Best gait sequence detection algorithms showed good performances (sensitivity > 0.73, positive predictive values > 0.75, specificity > 0.95, accuracy > 0.94). ICD and CAD algorithms presented excellent results, with sensitivity > 0.79, positive predictive values > 0.89 and relative errors < 11% for ICD and < 8.5% for CAD. The best identified SL algorithm showed lower performances than other DMOs (absolute error < 0.21 m). Lower performances across all DMOs were found for the cohort with most severe gait impairments (proximal femoral fracture). Algorithms' performances were lower for short walking bouts; slower gait speeds (< 0.5 m/s) resulted in reduced performance of the CAD and SL algorithms. CONCLUSIONS: Overall, the identified algorithms enabled a robust estimation of key DMOs. Our findings showed that the choice of algorithm for estimation of gait sequence detection and CAD should be cohort-specific (e.g., slow walkers and with gait impairments). Short walking bout length and slow walking speed worsened algorithms' performances. Trial registration ISRCTN - 12246987.

Cross-sectional health centre and community-based evaluation of the impact of pneumococcal and malaria vaccination on antibiotic prescription and usage, febrile illness and antimicrobial resistance in young children in Malawi: the IVAR study protocol.

INTRODUCTION: Vaccination is a potentially critical component of efforts to arrest development and dissemination of antimicrobial resistance (AMR), though little is known about vaccination impact within low-income and middle-income countries. This study will evaluate the impact of vaccination on reducing carriage prevalence of resistant Streptococcus pneumoniae and extended spectrum beta-lactamase-producing Escherichia coli and Klebsiella species. We will leverage two large ongoing cluster-randomised vaccine evaluations in Malawi assessing; first, adding a booster dose to the 13-valent pneumococcal conjugate vaccine (PCV13) schedule, and second, introduction of the RTS,S/AS01 malaria vaccine. METHODS AND ANALYSIS: Six cross-sectional surveys will be implemented within primary healthcare centres (n=3000 users of outpatient facilities per survey) and their local communities (n=700 healthy children per survey): three surveys in Blantyre district (PCV13 component) and three surveys in Mangochi district (RTS,S/AS01 component). We will evaluate antibiotic prescription practices and AMR carriage in children ≤3 years. For the PCV13 component, surveys will be conducted 9, 18 and 33 months following a 3+0 to 2+1 schedule change. For the RTS,S/AS01 component, surveys will be conducted 32, 44 and 56 months post-RTS,S/AS01 introduction. Six health centres in each study component will be randomly selected for study inclusion. Between intervention arms, the primary outcome will be the difference in penicillin non-susceptibility prevalence among S. pneumoniae nasopharyngeal carriage isolates in healthy children. The study is powered to detect an absolute change of 13 percentage points (ie, 35% vs 22% penicillin non-susceptibility). ETHICS AND DISSEMINATION: This study has been approved by the Kamuzu University of Health Sciences (Ref: P01-21-3249), University College London (Ref: 18331/002) and University of Liverpool (Ref: 9908) Research Ethics Committees. Parental/caregiver verbal or written informed consent will be obtained prior to inclusion or recruitment in the health centre-based and community-based activities, respectively. Results will be disseminated via the Malawi Ministry of Health, WHO, peer-reviewed publications and conference presentations.

A multi-sensor wearable system for the assessment of diseased gait in real-world conditions.

Introduction: Accurately assessing people's gait, especially in real-world conditions and in case of impaired mobility, is still a challenge due to intrinsic and extrinsic factors resulting in gait complexity. To improve the estimation of gait-related digital mobility outcomes (DMOs) in real-world scenarios, this study presents a wearable multi-sensor system (INDIP), integrating complementary sensing approaches (two plantar pressure insoles, three inertial units and two distance sensors). Methods: The INDIP technical validity was assessed against stereophotogrammetry during a laboratory experimental protocol comprising structured tests (including continuous curvilinear and rectilinear walking and steps) and a simulation of daily-life activities (including intermittent gait and short walking bouts). To evaluate its performance on various gait patterns, data were collected on 128 participants from seven cohorts: healthy young and older adults, patients with Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, congestive heart failure, and proximal femur fracture. Moreover, INDIP usability was evaluated by recording 2.5-h of real-world unsupervised activity. Results and discussion: Excellent absolute agreement (ICC >0.95) and very limited mean absolute errors were observed for all cohorts and digital mobility outcomes (cadence ≤0.61 steps/min, stride length ≤0.02 m, walking speed ≤0.02 m/s) in the structured tests. Larger, but limited, errors were observed during the daily-life simulation (cadence 2.72-4.87 steps/min, stride length 0.04-0.06 m, walking speed 0.03-0.05 m/s). Neither major technical nor usability issues were declared during the 2.5-h acquisitions. Therefore, the INDIP system can be considered a valid and feasible solution to collect reference data for analyzing gait in real-world conditions.

Bacterial benz(a)anthracene catabolic networks in contaminated soils and their modulation by other co-occurring HMW-PAHs.

Polycyclic aromatic hydrocarbons (PAHs) are major environmental pollutants in a number of point source contaminated sites, where they are found embedded in complex mixtures containing different polyaromatic compounds. The application of bioremediation technologies is often constrained by unpredictable end-point concentrations enriched in recalcitrant high molecular weight (HMW)-PAHs. The aim of this study was to elucidate the microbial populations and potential interactions involved in the biodegradation of benz(a)anthracene (BaA) in PAH-contaminated soils. The combination of DNA stable isotope probing (DNA-SIP) and shotgun metagenomics of 13C-labeled DNA identified a member of the recently described genus Immundisolibacter as the key BaA-degrading population. Analysis of the corresponding metagenome assembled genome (MAG) revealed a highly conserved and unique genetic organization in this genus, including novel aromatic ring-hydroxylating dioxygenases (RHD). The influence of other HMW-PAHs on BaA degradation was ascertained in soil microcosms spiked with BaA and fluoranthene (FT), pyrene (PY) or chrysene (CHY) in binary mixtures. The co-occurrence of PAHs resulted in a significant delay in the removal of PAHs that were more resistant to biodegradation, and this delay was associated with relevant microbial interactions. Members of Immundisolibacter, associated with the biodegradation of BaA and CHY, were outcompeted by Sphingobium and Mycobacterium, triggered by the presence of FT and PY, respectively. Our findings highlight that interacting microbial populations modulate the fate of PAHs during the biodegradation of contaminant mixtures in soils.

Seasonality and other risk factors for fleas infestations in domestic dogs and cats.

Fleas in the genus Ctenocephalides are the most clinically important parasitic arthropods of dogs and cats worldwide yet risk factors that might increase the risk of infestation in small animals remains unclear. Here we developed a supervised text mining approach analysing key aspects of flea epidemiology using electronic health records from domestic cats and dogs seen at a sentinel network of 191 voluntary veterinary practices across Great Britain between March 2014 and July 2020. Our methods identified fleas as likely to have been present during 22,276 of 1,902,016 cat consultations (1.17%) and 12,168 of 4,844,850 dog consultations (0.25%). Multivariable logistic regression modelling found that animals originating from areas of least deprivation were associated with 50% reductions in odds of veterinary-recorded flea infestation compared to the most deprived regions in England. Age of the animal was significantly associated with flea presentation in both cats and dogs, with cases peaking before animals reached 12 months. Cases were recorded through each study years, peaking between July and October, with fluctuations between each year. Our findings can be used towards healthcare messaging for veterinary practitioners and owners.

Design and validation of a multi-task, multi-context protocol for real-world gait simulation.

BACKGROUND: Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a protocol for simulating real-world gait accounting for all these factors within a single set of observations, while ensuring minimisation of participant burden and safety. METHODS: The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants' strategy of walking. It was deployed in a convenience sample of 108 participants recruited from six cohorts that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson's disease (PD), multiple sclerosis (MS), proximal femoral fracture (PFF), chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks. RESULTS: The protocol proved to be safe and feasible (all participants could complete it and no adverse events were recorded) and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a representation of a variety of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life. CONCLUSIONS: The protocol allowed for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy. TRIAL REGISTRATION: ISRCTN-12246987.

Connecting real-world digital mobility assessment to clinical outcomes for regulatory and clinical endorsement-the Mobilise-D study protocol.

BACKGROUND: The development of optimal strategies to treat impaired mobility related to ageing and chronic disease requires better ways to detect and measure it. Digital health technology, including body worn sensors, has the potential to directly and accurately capture real-world mobility. Mobilise-D consists of 34 partners from 13 countries who are working together to jointly develop and implement a digital mobility assessment solution to demonstrate that real-world digital mobility outcomes have the potential to provide a better, safer, and quicker way to assess, monitor, and predict the efficacy of new interventions on impaired mobility. The overarching objective of the study is to establish the clinical validity of digital outcomes in patient populations impacted by mobility challenges, and to support engagement with regulatory and health technology agencies towards acceptance of digital mobility assessment in regulatory and health technology assessment decisions. METHODS/DESIGN: The Mobilise-D clinical validation study is a longitudinal observational cohort study that will recruit 2400 participants from four clinical cohorts. The populations of the Innovative Medicine Initiative-Joint Undertaking represent neurodegenerative conditions (Parkinson's Disease), respiratory disease (Chronic Obstructive Pulmonary Disease), neuro-inflammatory disorder (Multiple Sclerosis), fall-related injuries, osteoporosis, sarcopenia, and frailty (Proximal Femoral Fracture). In total, 17 clinical sites in ten countries will recruit participants who will be evaluated every six months over a period of two years. A wide range of core and cohort specific outcome measures will be collected, spanning patient-reported, observer-reported, and clinician-reported outcomes as well as performance-based outcomes (physical measures and cognitive/mental measures). Daily-living mobility and physical capacity will be assessed directly using a wearable device. These four clinical cohorts were chosen to obtain generalizable clinical findings, including diverse clinical, cultural, geographical, and age representation. The disease cohorts include a broad and heterogeneous range of subject characteristics with varying chronic care needs, and represent different trajectories of mobility disability. DISCUSSION: The results of Mobilise-D will provide longitudinal data on the use of digital mobility outcomes to identify, stratify, and monitor disability. This will support the development of widespread, cost-effective access to optimal clinical mobility management through personalised healthcare. Further, Mobilise-D will provide evidence-based, direct measures which can be endorsed by regulatory agencies and health technology assessment bodies to quantify the impact of disease-modifying interventions on mobility. TRIAL REGISTRATION: ISRCTN12051706.

Shared sources and mechanisms of healthcare worker distress in COVID-19: a comparative qualitative study in Canada and the UK.

Background: COVID-19 has had a significant impact on the wellbeing of healthcare workers, with quantitative studies identifying increased stress, anxiety, depression, insomnia, and PTSD in a wide range of settings. Limited qualitative data so far has offered in-depth details concerning what underlies these challenges, but none provide comprehensive comparison across different healthcare systems. Objective: To explore qualitative findings relating to healthcare worker distress from two different countries to understand the nuanced similarities and differences with respect to the sources and impact of distress relating to COVID-19. Method: A comparative interpretive thematic analysis was carried out between two qualitative data sets examining healthcare workers' experiences of distress during the COVID-19 pandemic. Data from Canada and the UK were collected in parallel and analyzed in an iterative, collaborative process. Results: A number of sources of distress cut across both study settings including concerns about safety and patient care, challenges at home or in one's personal life, communication issues, work environment, media and public perception, and government responses to the pandemic. These sit on a spectrum from individual to institutional sources and were mutually reinforcing. Our analysis also suggested that common mechanisms such as exacerbations in uncertainty, hypervigilance, and moral injury underpinned these sources, which contributed to how they were experienced as distressing. Conclusion: This is the first international collaboration utilising qualitative data to examine this pressing issue. Despite differences in the political, social, health service, and pandemic-related context, the sources and mechanisms of distress experienced by healthcare workers in Canada and the UK were remarkably similar. HIGHLIGHTS This international comparative qualitative study explores how mechanisms that lead to distress are shared across different geographies and cultures, even as the local context shapes the sources of distress themselves.

Antecedentes: La COVID-19 ha tenido un impacto significativo en el bienestar de los trabajadores de la salud, con estudios cuantitativos que identifican un aumento del estrés, la ansiedad, la depresión, el insomnio, y el TEPT en una amplia variedad de entornos. Hasta ahora, los datos cualitativos son limitados y han ofrecido un profundo detalle sobre lo que subyace a estos desafíos, pero ninguno proporciona una comparación exhaustiva entre los diferentes sistemas de atención de salud.Objetivo: Explorar los hallazgos cualitativos relacionados con la angustia de los trabajadores de la salud de dos países diferentes para comprender las sutiles similitudes y diferencias con respecto a las fuentes y el impacto de la angustia relacionada con la COVID-19.Método: Se llevó a cabo un análisis temático interpretativo comparativo entre dos conjuntos de datos cualitativos que examinaron las experiencias de angustia de los trabajadores de la salud durante la pandemia de la COVID-19. Los datos de Canadá y el Reino Unido se recopilaron en paralelo y se analizaron en un proceso colaborativo iterativo.Resultados: Una serie de fuentes de angustia atraviesan ambos entornos de estudio, incluidas las preocupaciones sobre la seguridad y el cuidado del paciente, los desafíos en el hogar o en la vida personal, los problemas de comunicación, el entorno laboral, la percepción pública y de los medios de comunicación, y las respuestas gubernamentales a la pandemia. Estos se ubican en un espectro desde fuentes individuales hasta institucionales y se reforzaron mutuamente. Nuestro análisis también sugirió que mecanismos comunes como las exacerbaciones de la incertidumbre, la hipervigilancia, y el daño moral sustentaban estas fuentes, lo que contribuyó a que se experimentaran como angustiosas.Conclusión: Esta es la primera colaboración internacional que utiliza datos cualitativos para examinar este apremiante problema. A pesar de las diferencias en el contexto político, social, de servicios de salud y relacionado con la pandemia, las fuentes y los mecanismos de angustia experimentados por los trabajadores de la salud en Canadá y el Reino Unido fueron notablemente similares.

Impacts of COVID-19 on Owner's Veterinary Healthcare Seeking Behavior for Dogs With Chronic Conditions: An Exploratory Mixed-Methods Study With a Convenience Sample.

This mixed-method study explored the impacts of the COVID-19 pandemic on owners' veterinary healthcare seeking, with particular focus on dogs with chronic conditions. A convenience sample of 719 UK dog owners completed an online survey (December 2020-January 2021). Differences in treatment provision and respondents' decisions to seek care across acute, preventative, chronic conditions and for end-of-life care were explored. Multivariable logistic regression models were used to identify factors associated with seeking care for any health issue compared to deciding against it, and urgency to seek care given symptom that could indicate chronic conditions. Open-ended questions were analyzed by thematic analysis. Significant (p-value < 0.05) differences in care seeking decisions were identified regarding access to veterinary care and the way treatment was provided across all health issues. The top reasons for not seeking care across all health issues were a lack of access to a veterinarian (30%, n = 56/187) and a reluctance for a dog to go to the clinic unaccompanied (20%, n = 38/187). Variables related to stronger dog-owner relationship, higher confidence in seeking care, perception of: benefits of veterinary care, dog's high susceptibility to illness and high severity of dog's condition, increased the odds of seeking, and urgency to seek, care. A dog's chronic illness diagnosis reduced the odds of seeking care during the pandemic, reportedly due to difficulties in accessing care for non-urgent issues. Qualitative analysis showed that limited access to routine consultations, delays in test results and restricted access to complementary treatments, led some owners of dogs with chronic conditions to believe that their dog's welfare had deteriorated during the pandemic. Pandemic control measures necessitated changes to how consultations were run. These changes were often viewed favorably, but dog-client separation during consultations were considered problematic, sometimes delaying veterinary advice-seeking, including for euthanasia. Separating owners from their dogs during veterinary consultations should be avoided wherever possible due to impacts on dogs, owners and healthcare seeking. Interventions to improve veterinary healthcare seeking could target attitudes toward benefits of seeking care, improve owners' self-efficacy and capitalize on the dog-owner bond. Such interventions should be implemented alongside interventions aimed at removing structural barriers to accessing healthcare.

Predictive values of time-dense SARS-CoV-2 wastewater analysis in university campus buildings.

Wastewater-based SARS-CoV-2 surveillance on college campuses has the ability to detect individual clinical COVID-19 cases at the building-level. High concordance of wastewater results and clinical cases has been observed when calculated over a time window of four days or longer and in settings with high incidence of infection. At Duke University, twice a week clinical surveillance of all resident undergraduates was carried out in the spring 2021 semester. We conducted simultaneous wastewater surveillance with daily frequency on selected residence halls to assess wastewater as an early warning tool during times of low transmission with the hope of scaling down clinical test frequency. We evaluated the temporal relationship of the two time-dense data sets, wastewater and clinical, and sought a strategy to achieve the highest wastewater predictive values using the shortest time window to enable timely intervention. There were 11 days with clinical cases in the residence halls (80-120 occupants) under wastewater surveillance with 5 instances of a single clinical case and 3 instances of two clinical cases which also corresponded to a positive wastewater SARS-CoV-2 signal. While the majority (71%) of our wastewater samples were negative for SARS-CoV-2, 29% resulted in at least one positive PCR signal, some of which did not correlate with an identified clinical case. Using a criteria of two consecutive days of positive wastewater signals, we obtained a positive predictive value (PPV) of 75% and a negative predictive value of 87% using a short 2 day time window for agreement. A conventional concordance over a much longer 4 day time window resulted in PPV of only 60%. Our data indicated that daily wastewater collection and using a criteria of two consecutive days of positive wastewater signals was the most predictive approach to timely early warning of COVID-19 cases at the building level.

Do socioeconomic factors impact management of suspected canine multicentric lymphoma in UK first opinion practice?

BACKGROUND: This study aimed to describe the management of cases of suspected and confirmed canine multicentric lymphoma (ML) in first opinion practice (FOP) and investigate whether socioeconomic factors are associated with initial management. METHODS: Clinical narratives from electronic health records collected by the Small Animal Veterinary Surveillance Network (SAVSNET) were searched to identify dogs with peripheral lymphadenomegaly in which ML was the major differential. Cases were grouped as either ML confirmed (ML-C) or ML suspected but not confirmed (ML-S). Associations between initial management and socioeconomic factors were assessed via multivariable logistic regression. RESULTS: Two hundred and sixty-four cases with ML-C and 410 with ML-S were identified. There was an increased probability that owners of ML-C cases resided in less deprived areas. Moreover, a diagnosis was made more commonly in insured dogs. Only insured pets were more likely to be treated with chemotherapy following diagnosis. The majority of dogs in both groups were treated with corticosteroids alone (ML-S, n = 256/410; ML-C, n = 123/264). A small minority were referred (n = 30/674). CONCLUSION: Socioeconomic inequalities appear to be associated with the diagnosis and management of dogs with suspected or confirmed ML in FOP. Most dogs with suspected multicentric lymphoma (in the UK) are managed in FOP (n = 644/674). Consequently, expanding the knowledge base relevant to this setting offers an opportunity to improve the management of canine lymphoma.