Application of user-centered co-design principles to address barriers in therapeutic drug monitoring.

BACKGROUND: Different software applications have been developed to support healthcare professionals in individualized drug dosing. However, their translation into clinical practice is limited, partly because of poor usability and integration into workflow, which can be attributed to the limited involvement of healthcare professionals in the development and implementation of drug dosing software. This study applied co-design principles to inform the design of a drug dosing software to address barriers in therapeutic drug monitoring (TDM) using vancomycin as an example. METHODS: Three workshops (face-to-face and online) were conducted by design researchers with pharmacists and prescribers. User journey storyboards, user personas, and prototyping tools were used to explore existing barriers to practice and opportunities for innovation through drug dosing software design. A prototype of the software interface was developed for further evaluation. RESULTS: Healthcare professionals (11 hospital pharmacists and 6 prescribers) with ≥2 years of clinical experience were recruited. Confidence and software usability emerged as the main themes. Participants identified a lack of confidence in vancomycin dosing and pharmacokinetic understanding and difficulty in accessing practice guidelines as key barriers that could be addressed through software implementation. Accessibility to information (e.g., guidelines and pharmacokinetic resources) and information presentation (e.g., graphical) within the dosing software were dependent on the needs and experience of the user. A software prototype with a speedometer-dial visual to convey optimal doses was well received by participants. CONCLUSION: The perspectives of healthcare professionals highlight the need for drug dosing software to be user-centred and adaptable to the needs and workflow of end users. Continuous engagement with stakeholders on tool usability, training, and education is needed to promote the implementation in practice.

Predicting locations of cryptic pockets from single protein structures using the PocketMiner graph neural network.

Cryptic pockets expand the scope of drug discovery by enabling targeting of proteins currently considered undruggable because they lack pockets in their ground state structures. However, identifying cryptic pockets is labor-intensive and slow. The ability to accurately and rapidly predict if and where cryptic pockets are likely to form from a structure would greatly accelerate the search for druggable pockets. Here, we present PocketMiner, a graph neural network trained to predict where pockets are likely to open in molecular dynamics simulations. Applying PocketMiner to single structures from a newly curated dataset of 39 experimentally confirmed cryptic pockets demonstrates that it accurately identifies cryptic pockets (ROC-AUC: 0.87) >1,000-fold faster than existing methods. We apply PocketMiner across the human proteome and show that predicted pockets open in simulations, suggesting that over half of proteins thought to lack pockets based on available structures likely contain cryptic pockets, vastly expanding the potentially druggable proteome.

Telemental health in emergency care settings: A qualitative analysis of considerations for sustainability and spread.

OBJECTIVES: Following rapid uptake of telehealth during the COVID-19 pandemic, we examined barriers and facilitators for sustainability and spread of telemental health video (TMH-V) as policies regarding precautions from the pandemic waned. METHODS: We conducted a qualitative study using semistructured interviews and observations guided by RE-AIM. We asked four groups, local clinicians, facility leadership, Veterans, and external partners, about barriers and facilitators impacting patient willingness to engage in TMH-V (reach), quality of care (effectiveness), barriers and facilitators impacting provider uptake (adoption), possible adaptations to TMH-V (implementation), and possibilities for long-term use of TMH-V (maintenance). Interviews were recorded, transcribed, and analyzed using framework analysis. We also observed TMH-V encounters in one emergency department (ED) and one urgent care (UC) to understand how clinicians and Veterans engaged with the technology. RESULTS: We conducted 35 interviews with ED/UC clinicians and staff (n = 10), clinical and facility leadership (n = 7), Veterans (n = 5), and external partners (n = 13), January-May 2022. We completed 10 observations. All interviewees were satisfied with the TMH-V program, and interviewees highlighted increased comfort discussing difficult topics for Veterans (reach). Clinicians identified that TMH-V allowed for cross-coverage across sites as well as increased safety and flexibility for clinicians (adoption). Opportunities for improvement include alleviating technological burdens for on-site staff, electronic health record (EHR) modifications to accurately capture workload and modality (telehealth vs. in-person), and standardizing protocols to streamline communication between on-site and remote clinical staff (implementation). Finally, interviewees encouraged its spread (maintenance) and thought there was great potential for service expansion. CONCLUSIONS: Interviewees expressed support for continuing TMH-V locally and spread to other sites. Ensuring adequate infrastructure (e.g., EHR integration and technology support) and workforce capacity are key for successful spread. Given the shortage of mental health (MH) clinicians in rural settings, TMH-V represents a promising intervention to increase the access to high-quality emergency MH care.

Early warning signals for Omicron outbreaks in China: a retrospective study.

The Omicron variant has become the dominant COVID-19 variant worldwide due to its rapid and cryptic spread; therefore, successful early warning is of great importance to be able to control epidemics in their early phase, before developing into large outbreaks. COVID-19-related Baidu search index, which reflects human behavior to a certain degree, was used to retrospectively detect the warning signs for Omicron variant outbreaks in China in 2022. The characteristics and effects of warning signs were analyzed in detail. We detected the presence of early warning signs (both high and low thresholds) and found that these occurred 4-7 days earlier than traditional epidemiological surveillance and >20 days earlier than the implementation of the local "lockdown" policy. Compared with the "high threshold" warning, the early warning effect of the "low threshold" is also vital because it indicates a complacency about epidemic prevention and control. However, there is obvious heterogeneity in the optimal threshold for detecting early warning signs and their distribution in different cities. Multi-source and multi-point early warning systems should be established via combining internet-based big data in the future to conduct effective and early real-time warning. This would create precious time for the early control of COVID-19 outbreaks. This article is protected by copyright. All rights reserved.

Emerging canine leptospirosis in Sydney and the role of population demographics.

An outbreak of canine leptospirosis commenced in Sydney, Australia in 2017. The aim of this retrospective study was to determine if clusters of leptospirosis occurred during this outbreak, and if these were associated with host factors, to assist investigation of the drivers of emerging leptospirosis at this location. Within the City of Sydney local government area, 13 cases were reported during the outbreak. Administrative data on the canine population were collected and mapped. Clusters of leptospirosis cases were detected using a retrospective space-time analysis and a discrete Poisson probability statistical model. Sydney dog population registration [55.6%, 95% confidence interval (CI) 51.8-58.1%] was lower than the Australian national average (80%). The distribution of dog types, based on the United Kennel Club standards, was significantly (p < .0001) different to that of the national profile: there was a distinct preference in Sydney for companion dogs. The age distribution of dogs in Sydney did not reflect a typical right-skewed curve; instead, a relatively uniform distribution was observed between the age group of 1 to 8 years. A primary disease cluster (radius 1.1 km) in the eastern area of the Sydney City Council was identified (4 cases observed between 24 May and 9 August 2019 vs. 0.10 cases expected), p = .0450. When adjusted for the age, breed type and sex distribution of the population, similar clusters were identified; in the case of age-adjustment, the spatiotemporal cluster identified was larger and of longer duration (seven cases observed between 28 June and 11 November 2019 versus 0.34 cases expected), p = .0025. The presence of clusters of canine leptospirosis in the City of Sydney during this outbreak, which persisted after adjustment for demographics (age, sex, breed type), suggest that environmental factors - rather than host or pathogen factors - might be responsible for the emergence of leptospirosis. Environmental factors that potentially might be linked to this outbreak of canine leptospirosis and the clusters observed require investigation.

Potentially avoidable interfacility transfers following reduced emergency department volumes due to COVID-19 "Safer-at-Home" orders.

OBJECTIVES: We sought to assess if a state-wide lockdown implemented due to COVID-19 was associated with increased odds of being a potentially avoidable transfer (PAT). METHODS: We conducted a retrospective observational analysis using hospital administrative data of interfacility ED-to-ED transfers to a single, quaternary care adult ED after "Safer at Home" orders were issued March 23rd, 2020 in [Blinded for submission]. Using the PAT classification to identify transfers rapidly discharged from the ED or hospital and may not require in-person care, we used a multivariable logistic regression model to examine the association of the lockdown order with odds of a transfer being a PAT. We compared the period January 1, 2018 to March 23, 2020 with March 24, 2020 to September 30, 2020, adjusting for seasonality, patient, and situational factors. RESULTS: There were 20,978 ED-to-ED transfers from during this period that were eligible and 4806 (23%) that met PAT criteria. While the first month post-lockdown saw a decrease in PATs (28%), this was not sustained. In the multivariable model there was a significant seasonal effect; May through September had the highest number of transfers as well as PATs. After adjusting for seasonality, the lockdown was not associated with PATs (adjusted odds ratio [aOR] 0.99, 95% CI 0.2, 5.2) and PATs decreased over time. CONCLUSIONS: We did not find an effect of the COVID-19 lockdown on PATs though there was a considerable seasonal effect and an overall downward trend in PATs over time.

Inherent virus characteristics and host range drive the zoonotic and emerging potential of viruses.

Understanding the zoonotic and emerging potential of viruses is critical to prevent and control spread that can cause disease epidemics or pandemics. We developed a database using the most up-to-date information from the International Committee on Taxonomy of Viruses (4958 virus species) and identified 1479 vertebrate virus species and their host ranges. Viral traits and host ranges were then used as predictors in generalized linear mixed models for three host-associated outcomes - confirmed zoonotic, potential zoonotic and disease emergence. We identified significant interactions between host range and viral characteristics, not previously reported, that influence the zoonotic and emergence potential of viruses. Bat- and livestock-adapted viruses posed high risk, and the risk increased substantially if these viruses were also present in other vertebrates or were not reported from invertebrates. Our model predicted 39 viruses of interest that have never been reported to have zoonotic potential (27) or to potentially become emerging human viruses (12). We conclude that nucleic acid type is important in identifying the zoonotic and emerging potential of viruses. We recommend enhanced surveillance and monitoring of these virus species identified with a zoonotic and emerging potential to mitigate disease outbreaks and future epidemics.

Rabies in the Tropics.

Purpose of Review: Rabies is an ancient yet still neglected tropical disease (NTD). This review focuses upon highlights of recent research and peer-reviewed communications on the underestimated tropical burden of disease and its management due to the complicated dynamics of virulent viral species, diverse mammalian reservoirs, and tens of millions of exposed humans and animals - and how laboratory-based surveillance at each level informs upon pathogen spread and risks of transmission, for targeted prevention and control. Recent Findings: While both human and rabies animal cases in enzootic areas over the past 5 years were reported to PAHO/WHO and OIE by member countries, still there is a huge gap between these "official" data and the need for enhanced surveillance efforts to meet global program goals. Summary: A review of the complex aspects of rabies perpetuation in human, domestic animal, and wildlife communities, coupled with a high fatality rate despite the existence of efficacious biologics (but no therapeutics), warrants the need for a One Health approach toward detection via improved laboratory-based surveillance, with focal management at the viral source. More effective methods to prevent the spread of rabies from enzootic to free zones are needed.

Low and No-Contact Euthanasia: Associated Ethical Challenges Experienced by Veterinary Team Members during the Early Months of the COVID-19 Pandemic.

BACKGROUND: During the ongoing COVID-19 pandemic, many veterinary practices around the world have shifted to a low or no-contact consultation model to ensure the safety of their team members and clients, and comply with public health orders, while continuing to provide veterinary care. METHODS: We performed reflexive thematic analysis on a subset of data collected using a mixed-methods survey of veterinary team members globally. RESULTS: There were 540 valid responses available for analysis. Low and no-contact euthanasia we raised as a common and/or stressful ethical challenge for 22.8% of respondents. We identified five key themes: no-contact euthanasia as a unique ethical challenge; balancing veterinary team safety with the emotional needs of clients; low and no-contact protocols may cause or exacerbate fear, anxiety and distress in veterinary patients; physical distancing was more challenging during euthanasia consultations; and biosecurity measures complicated communication around euthanasia and end-of-life decision making. RECOMMENDATIONS: In light of concerns highlighted by respondents, we recommend the development of a toolkit of protocols that will assist veterinary team members in performing low-contact euthanasia in a range of circumstances, in alignment with their values and professional ethical codes. Professional bodies may be involved in developing, updating and disseminating this information, and ensuring a continuous supply chain of PPE.

Development of a Robust Manufacturing Route for Molnupiravir, an Antiviral for the Treatment of COVID-19

Herein is described the development of a large-scale manufacturing process for molnupiravir, an orally dosed antiviral that was recently demonstrated to be efficacious for the treatment of patients with COVID-19. The yield, robustness, and efficiency of each of the five steps were improved, ultimately culminating in a 1.6-fold improvement in overall yield and a dramatic increase in the overall throughput compared to the baseline process.

Challenges in the control of COVID-19 outbreaks caused by the delta variant during periods of low humidity: an observational study in Sydney, Australia.

BACKGROUND: Since the appearance of severe acute respiratory coronavirus 2 (SARS-CoV-2) and the coronavirus disease 2019 (COVID-19) pandemic, a growing body of evidence has suggested that weather factors, particularly temperature and humidity, influence transmission. This relationship might differ for the recently emerged B.1.617.2 (delta) variant of SARS-CoV-2. Here we use data from an outbreak in Sydney, Australia that commenced in winter and time-series analysis to investigate the association between reported cases and temperature and relative humidity. METHODS: Between 16 June and 10 September 2021, the peak of the outbreak, there were 31,662 locally-acquired cases reported in five local health districts of Sydney, Australia. The associations between daily 9:00 am and 3:00 pm temperature (°C), relative humidity (%) and their difference, and a time series of reported daily cases were assessed using univariable and multivariable generalized additive models and a 14-day exponential moving average. Akaike information criterion (AIC) and the likelihood ratio statistic were used to compare different models and determine the best fitting model. A sensitivity analysis was performed by modifying the exponential moving average. RESULTS: During the 87-day time-series, relative humidity ranged widely (< 30-98%) and temperatures were mild (approximately 11-17 °C). The best-fitting (AIC: 1,119.64) generalized additive model included 14-day exponential moving averages of 9:00 am temperature (P < 0.001) and 9:00 am relative humidity (P < 0.001), and the interaction between these two weather variables (P < 0.001). Humidity was negatively associated with cases no matter whether temperature was high or low. The effect of lower relative humidity on increased cases was more pronounced below relative humidity of about 70%; below this threshold, not only were the effects of humidity pronounced but also the relationship between temperature and cases of the delta variant becomes apparent. CONCLUSIONS: We suggest that the control of COVID-19 outbreaks, specifically those due to the delta variant, is particularly challenging during periods of the year with lower relative humidity and warmer temperatures. In addition to vaccination, stronger implementation of other interventions such as mask-wearing and social distancing might need to be considered during these higher risk periods.

SARS-CoV-2 Nsp16 activation mechanism and a cryptic pocket with pan-coronavirus antiviral potential.

Coronaviruses have caused multiple epidemics in the past two decades, in addition to the current COVID-19 pandemic that is severely damaging global health and the economy. Coronaviruses employ between 20 and 30 proteins to carry out their viral replication cycle, including infection, immune evasion, and replication. Among these, nonstructural protein 16 (Nsp16), a 2'-O-methyltransferase, plays an essential role in immune evasion. Nsp16 achieves this by mimicking its human homolog, CMTr1, which methylates mRNA to enhance translation efficiency and distinguish self from other. Unlike human CMTr1, Nsp16 requires a binding partner, Nsp10, to activate its enzymatic activity. The requirement of this binding partner presents two questions that we investigate in this manuscript. First, how does Nsp10 activate Nsp16? Although experimentally derived structures of the active Nsp16/Nsp10 complex exist, structures of inactive, monomeric Nsp16 have yet to be solved. Therefore, it is unclear how Nsp10 activates Nsp16. Using over 1 ms of molecular dynamics simulations of both Nsp16 and its complex with Nsp10, we investigate how the presence of Nsp10 shifts Nsp16's conformational ensemble to activate it. Second, guided by this activation mechanism and Markov state models, we investigate whether Nsp16 adopts inactive structures with cryptic pockets that, if targeted with a small molecule, could inhibit Nsp16 by stabilizing its inactive state. After identifying such a pocket in SARS-CoV2 Nsp16, we show that this cryptic pocket also opens in SARS-CoV1 and MERS but not in human CMTr1. Therefore, it may be possible to develop pan-coronavirus antivirals that target this cryptic pocket.

Impact of the coronavirus disease 2019 interventions on the incidence of hand, foot, and mouth disease in mainland China.

BACKGROUND: In early 2020, non-pharmaceutical interventions (NPIs) were implemented in China to reduce and contain the coronavirus disease 2019 (COVID-19) transmission. These NPIs might have also reduced the incidence of hand, foot, and mouth disease (HFMD). METHODS: The weekly numbers of HFMD cases and meteorological factors in 31 provincial capital cities and municipalities in mainland China were obtained from Chinese Center for Disease Control and Prevention (CCDC) and National Meteorological Information Center of China from 2016 to 2020. The NPI data were collected from local CDCs. The incidence rate ratios (IRRs) were calculated for the entire year of 2020, and for January-July 2020 and August-December 2020. The expected case numbers were estimated using seasonal autoregressive integrated moving average models. The relationships between kindergarten closures and incidence of HFMD were quantified using a generalized additive model. The estimated associations from all cities were pooled using a multivariate meta-regression model. FINDINGS: Stringent NPIs were widely implemented for COVID-19 control from January to July 2020, and the IRRs for HFMD were less than 1 in all 31 cities, and less than 0·1 for 23 cities. Overall, the proportion of HFMD cases reduced by 52·9% (95% CI: 49·3-55·5%) after the implementation of kindergarten closures in 2020, and this effect was generally consistent across subgroups. INTERPRETATION: The decrease in HFMD incidence was strongly associated with the NPIs for COVID-19. HFMD epidemic peaks were either absent or delayed, and the final epidemic size was reduced. Kindergarten closure is an intervention to prevent HFMD outbreaks. FUNDING: This research was supported by the National Natural Science Foundation of China (81973102 & 81773487), Public Health Talents Training Program of Shanghai Municipality (GWV-10.2-XD21), the Shanghai New Three-year Action Plan for Public Health (GWV-10.1-XK16), the Major Project of Scientific and Technical Winter Olympics from National Key Research and Development Program of China (2021YFF0306000), 13th Five-Year National Science and Technology Major Project for Infectious Diseases (2018ZX10725-509) and Key projects of the PLA logistics Scientific research Program (BHJ17J013).

Implementation of Telehealth for Psychiatric Care in VA Emergency Departments and Urgent Care Clinics.

Objective: To conduct a mixed-methods evaluation of an emergency telehealth intervention in unscheduled settings (emergency department [ED] and urgent care clinic [UCC]) within the Veterans Health Administration (VHA). Materials and Methods: We used the Reach, Effectiveness, Adoption, Implementation, Maintenance (RE-AIM) framework to conduct a mixed-methods evaluation of a novel telehealth program implemented in the VHA (Hospital System) in March 2020. We compared the 3 months preimplementation (December 1, 2019 through February 29, 2020) with the 3 months postimplementation (April 1, 2020 through June 30, 2020), then followed sustainability through January 31, 2021. Qualitative data were obtained from surveys and semistructured interviews of staff and providers and analyzed with thematic analysis. Results: Patient demographics and dispositions were similar pre- and postimplementation. The telemental health intervention was used in 319 (83%) unscheduled mental health consultations in the postimplementation phase. After implementation, we did not detect adverse trends in length of stay, 7-day revisits, or 30-day mortality. Use remained high with 82% (n = 1,010) of all unscheduled mental health consultations performed by telemental health in the sustainability phase. Staff and clinician interviews identified the following themes in the use of telemental health: (1) enhanced efficiency without compromising quality and safety, (2) initial apprehension, (3) the COVID-19 pandemic, and (4) sustainability after resolution of the COVID-19 pandemic. Conclusions: This mixed-methods evaluation of unscheduled telemental health implementation found that its use was feasible, did not impact the safety and efficacy of mental health consultations, and was highly acceptable and sustainable in unscheduled settings.

Citizen Scientists Create an Exascale Computer to Combat COVID-19

The SARS-CoV-2/COVID-19 pandemic continues to threaten global health and socioeconomic stability. Experiments have revealed snapshots of many of the viral components but remain blind to moving parts of these molecular machines. To capture these essential processes, over a million citizen scientists have banded together through the Folding@home distributed computing project to create the world's first Exascale computer and simulate protein dynamics. An unprecedented 0.1 seconds of simulation of the viral proteome reveal how the spike complex uses conformational masking to evade an immune response, conformational changes implicated in the function of other viral proteins, and 'cryptic' pockets that are absent in experimental snapshots. These structures and mechanistic insights present new targets for the design of therapeutics. This living document will be updated as we perform further analysis and make the data publicly accessible.

Risk Factors Associated With Increased Ethically Challenging Situations Encountered by Veterinary Team Members During the COVID-19 Pandemic.

Ethically challenging situations (ECS) are commonly encountered in veterinary settings. The number of ECS encountered by some veterinary team members may increase during a crisis, such as the COVID-19 pandemic. This study aimed to determine the risk factors for experiencing an increase in the frequency of ECS in the months following the beginning of the COVID-19 pandemic, utilizing data from a global survey of veterinarians, veterinary nurses and animal health technicians collected from May to July 2020. In this study, descriptive analyses were performed to characterize veterinary team members who responded to the survey (n = 540). Binomial logistic regression analyses were performed to determine factors associated with an increase in ECS encountered since the beginning of the COVID-19 pandemic. Being a veterinary nurse or animal health technician, working with companion animals, working in the USA or Canada, and being not confident or underconfident in dealing with ECS in the workplace were factors associated with an increase in ECS encountered since the beginning of the COVID-19 pandemic. Results suggest a need to explore the ECS encountered by veterinary team members, particularly veterinary nurses and animal health technicians working in companion animal practice, in depth. Identification of risk factors may facilitate better preparation of veterinary team members for managing ECS, and minimizing the negative impact of ECS on the well-being of those who care for animals.

Diurnal Variation in SARS-CoV-2 PCR Test Results: Test Accuracy May Vary by Time of Day.

False negative tests for SARS-CoV-2 are common and have important public health and medical implications. We tested the hypothesis of diurnal variation in viral shedding by assessing the proportion of positive versus negative SARS-CoV-2 reverse transcription polymerase chain reaction (RT-PCR) tests and cycle time (Ct) values among positive samples by the time of day. Among 86,342 clinical tests performed among symptomatic and asymptomatic patients in a regional health care network in the southeastern United States from March to August 2020, we found evidence for diurnal variation in the proportion of positive SARS-CoV-2 tests, with a peak around 1400 h and 1.7-fold variation over the day after adjustment for age, sex, race, testing location, month, and day of week and lower Ct values during the day for positive samples. These findings have important implications for public health testing and vaccination strategies.

Deep learning the structural determinants of protein biochemical properties by comparing structural ensembles with DiffNets.

Understanding the structural determinants of a protein's biochemical properties, such as activity and stability, is a major challenge in biology and medicine. Comparing computer simulations of protein variants with different biochemical properties is an increasingly powerful means to drive progress. However, success often hinges on dimensionality reduction algorithms for simplifying the complex ensemble of structures each variant adopts. Unfortunately, common algorithms rely on potentially misleading assumptions about what structural features are important, such as emphasizing larger geometric changes over smaller ones. Here we present DiffNets, self-supervised autoencoders that avoid such assumptions, and automatically identify the relevant features, by requiring that the low-dimensional representations they learn are sufficient to predict the biochemical differences between protein variants. For example, DiffNets automatically identify subtle structural signatures that predict the relative stabilities of ß-lactamase variants and duty ratios of myosin isoforms. DiffNets should also be applicable to understanding other perturbations, such as ligand binding.