Characterisation of professional pharmacy association resources and recommendations on COVID-19 pandemic

Background: As one of the most accessible healthcare workers, pharmacists are at the frontlines during emergencies such as the COVID-19 pandemic. Professional pharmacy associations provide resources and recommendations for pharmacists on COVID-19. Yet, the extent and repository of resources are currently not categorised. Purpose(s): To identify COVID-19 resources for pharmacists provided by associations in the United States of America and the International Pharmaceutical Federation (FIP) and characterise these resources to better serve pharmacists' needs to combat the pandemic. Method(s): A review of 17 pharmacy association websites was conducted to identify available resources. Search terms included 'resource, policy and recommendation'. Specific criteria were applied to categorise results in six areas. Descriptive statistics were used for data analysis. Result(s): Of the 16 US pharmacy associations and the FIP websites, 94% provided COVID-19 resources, 53% developed policies, and 94% had specific recommendations. Those were characterised into 6 types of recommendations, including 94% on general recommendations, 65% on education/training, 53% on supply chain management/drug shortages, 47% on guidelines/protocols, 71% on scope of practice, and 24% on the emergence of tele-health. Conclusion(s): Whilst the majority of associations provide COVID-19 related resources on general recommendations, scope of practice, and education/training, there are opportunities for more specific areas on guidelines/protocols and telehealth. With the dynamic nature of COVID-19, it is important for pharmacists to stay updated to provide optimal care for diverse patients and populations while combating the current pandemic and beyond.

Feasibility of virtual mock trials as a parallel teaching-assessment activity for student pharmacists at two American pharmacy programmes during the COVID-19 pandemic and beyond

Background: Student-pharmacists forced into remote-learning by the COVID-19 pandemic participated in a Virtual Mock Trial (VMT). Objective(s): Feasibility of VMTs was assessed by evaluating student VMT performance, student perceptions on technology and overall experiences. Method(s): The VMT was implemented via video conferencing technology in April 2020. Faculty-judges and student-jurors observed/rated student performance using pre-established rubrics. A post-VMT survey was administered electronically. Descriptive analyses were performed, and Wilcoxon-Mann-Whitney tests were conducted to compare programmes. Result(s): Forty-six students from Programme A (East Coast, USA) and 89 from Programme B (West Coast, USA) participated in the VMTs. The faculty-judges' evaluation scores for student performance ranged from 85.0% to 96.7%, while the student-jurors' evaluation scores ranged from 68.3% to 100%. Student perceptions on the four categories regarding technology use all had means > 5 on a 7-Point Likert Scale. More than 79.0% of students rated their VMT experience positively (i.e. 6 or 7). Conclusion(s): VMT is feasible for the current pandemic remote-learning environment, and it could be replicated in other pharmacy or healthcare programmes to enrich students' active learning in virtual education. Copyright © 2021 FIP.

Telehealth education and music therapy for nursing-home residents during COVID19

Objective: This project evaluated the effect of patient education and music therapy delivered by telehealth on depression related to COVID19 among rural nursing home residents. Method(s): This was a prospective, pilot intervention involving 56 residents from three rural nursing homes. The study included a convenience sample of residents at three rural nursing homes. The mean age for the three groups ranged from 67-81 years of age. Participants received either patient education or combined patient education and music therapy as depression interventions. The primary outcome was the change in PHQ-9 scores from baseline to the end of an eight-week period. The secondary outcome was resident satisfaction as measured through an evaluation survey. Result(s): Of the 56 participants enrolled, 28 completed the study and were included in data analysis. Low pretreatment PHQ-9 implied minimal depression. Summary statistics show a 1.53 mean PHQ-9 change for those receiving education-only (53.6%) and a -1.16 PHQ-9 for those receiving combined therapy (46.4%) (p = 0.092). Results did not demonstrate positive outcomes on depression. A potential difference was noted among each facility. Two-thirds of participants rated their experiences as good to excellent. Conclusions and Implications: It appears that education played a positive role, yet music therapy delivered as telehealth did not show improvement in depression. Further studies are needed to determine the potential impact of non-pharmacological interventions in rural nursing home residents during the pandemic.

Potential cost of not vaccinating against COVID19 in the United States

Introduction: As of April 2022, the COVID19 global pandemic has resulted in over six million deaths globally, and over 81 million cases of COVID19 in the United States. Objective(s): The objective of the presentation is to share estimated direct and indirect costs due to COVID19 infection juxtaposed with the costs of COVID19 vaccine administration in the United States. Method(s): A literature review was conducted to identify potential cost savings from being immunized against COVID19. The costs of COVID19 vaccinations, direct costs related to healthcare and types of indirect costs were noted. Result(s): After reviewing over 40 resources, several costs were identified. The cost of COVID19 vaccine series, as defined by the Centers of Medicare and Medicaid Services (CMS), is currently USD40 for single-dose and USD40 per dose in a multiple-dose series. It is estimated that the average hospitalisation stay of an uninsured inpatient was ~USD7000-USD10,000 per day. The average cost of 12 major metropolitan cities in the United States were estimated for primary care facilities, urgent care facilities, and emergency room visits at USD195, USD239, USD1,425, respectively. As of April 2, 2022, 77% of the US have received at least one dose of COVID19 vaccine and 66% are considered to be fully vaccinated against COVID19 primary series. Conclusion(s): According to the data, the cost reduction in healthcare is consequential and cost-effective in vaccinating the population. This analysis contributes to the limited reports of a national cost-benefit analysis.

A Novel Approach of Using Neural Circuit Policies for COVID-19 Classification on CT-Images

Fully connected (FC) layers as a classifier to categorize data have been practiced widely by the deep learning community. The dense wiring topology might lead to redundant complexity and overfitting during training. To overcome the disadvantages, we investigate neural circuit policies (NCP) to alternate the FC layers in this paper. NCP networks enable sparse and polarized connections between layers. Neurons within one layer can interact with themselves as well. However, NCP can handle only sequential data. To be compatible with the image classification task, we use sequence modeling techniques to simulate sequential data within the images. The ultimate comparison between NCP and FC models relies on the performance in classifying COVID-19 CT-slides. With our novel modeling technique, Z-NCP, the NCP models obtain the most stable scores. The FC models are comparably good and less resource-demanding. However, they are much less efficient considering the accuracy-complexity trade-off. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Intention to Adopt E-Grocery Shopping Service in Vietnam During Covid-19 Pandemic

The purpose of this study is to determine the factors that influence the intention to adopt e-grocery shopping service of Vietnamese consumers during Covid-19 Pandemic. The sample size includes 235 responses collected from e-grocery shoppers in Vietnam. The research methodology includes Cronbach's Alpha analysis, EFA analysis and multiple regression analysis. Data is analysed in SPSS 20 software. The results have identified four factors that directly affect the intention to adopt e-grocery shopping service which are social influence, perceived ease of use, brand image and perceived usefulness. Social influence is the most significant factor that impacting the intention to adopt e-grocery shopping service among consumers during Covid-19 Pandemic in Vietnam. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Improving Business Process Resilience to Long-tailed Business Events via Low-code

Among different types of changes, a specific type named long-tailed change (LTC), induced by wide-spectrum and sporadic events (hereafter long-tailed business events (LBEs), poses fresh challenges to available change management solutions in business process management. The disorder in economic and social life caused by the competition of COVID-19 epidemics and countermeasures all over the world fully demonstrates the impact of this new change management problem. Based on the principle of separation of concerns, this paper proposes a systematic framework to solve the above problem. The solution consists of a low-code mechanism for process adaptation and business policy conformance. As a result, front-line practitioners can quickly react to changes by using a domain-specific language (DSL) while a corresponding verification of functional and non-functional attributes maintains compliance with business constraints. We validate the solution through a case study of an e-commerce scenario during the COVID-19 pandemic. © 2022 IEEE.

The Effect of the COVID-19 Pandemic on Inward FDI in Vietnam

Using monthly inward foreign direct investment (FDI) data for the period from January 2020 to September 2021, our study aims to investigate how the COVID-19 burden (cases and deaths) and policy responses of Vietnam and 40 investment partners affected Vietnam’s FDI attraction. Estimates for the baseline models as well as for different types of income levels show that Vietnam’s COVID-19 burden negatively affects its inward FDI, while no evidence reveals the effect of investment partners’ COVID-19 burden. We find that Vietnam’s COVID-19 cases negatively affect its inward FDI from the European region, while no evidence reveals an effect from the Asian region. When including policy responses in the estimation, we find a disadvantageous impact of investment partners’ COVID-19 cases and deaths as well as Vietnam’s COVID-19 deaths on Vietnam’s inward FDI. In general, the effects of COVID-19 cases are significantly lower than those of COVID-19 deaths. Estimates show that stringent measures in Vietnam and investment partners negatively affect FDI flows into Vietnam, while containment and health measures have a positive effect. The study suggests that efforts should focus on reducing the number of COVID-19 deaths rather than the number of COVID-19 cases, minimizing the application of stringency measures by Vietnam and investment partners, applying health methods, and expanding trade agreements networks. © 2022 International Management Institute, New Delhi.

COVID-19 Diagnosis from Cough Acoustics using ConvNets and Data Augmentation

With the periodic rise and fall of COVID-19 and countries being inflicted by its waves, an efficient, economic, and effortless diagnosis procedure for the virus has been the utmost need of the hour. Amongst the infected subjects, the asymptomatic ones need not be entirely free of symptoms caused by the virus. They might not show any observable symptoms like the symptomatic subjects, but they may differ from uninfected ones in the way they cough. These differences in the coughing sounds are minute and indiscernible to the human ear, however, these can be captured using machine learning models. In this paper, we present a deep learning approach to analyze the acoustic dataset provided in Track 1 of the DiCOVA 2021 Challenge containing cough sound recordings belonging to both COVID-19 positive and negative examples. To perform the classification we propose a ConvNet model. It achieved an AUC score percentage of 72.23 on a blind test set provided in the challenge for an unbiased evaluation of the models. Moreover, the ConvNet model incorporated with Data Augmentation further increased the AUC score percentage from 72.23 to 87.07. It also outperformed the DiCOVA 2021 Challenge's baseline model by 23% thus, claiming the top position on the DiCOVA 2021 Challenge leaderboard. This paper proposes the use of Mel Frequency Cepstral Coefficients as the input features to the proposed model. © 2021 IEEE.

Bayesian emulation and history matching of JUNE.

We analyze JUNE: a detailed model of COVID-19 transmission with high spatial and demographic resolution, developed as part of the RAMP initiative. JUNE requires substantial computational resources to evaluate, making model calibration and general uncertainty analysis extremely challenging. We describe and employ the uncertainty quantification approaches of Bayes linear emulation and history matching to mimic JUNE and to perform a global parameter search, hence identifying regions of parameter space that produce acceptable matches to observed data, and demonstrating the capability of such methods. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

A Novel Approach For CT-Based COVID-19 Classification and Lesion Segmentation Based On Deep Learning

The coronavirus disease 2019 (COVID-19) pandemic has been a globally dangerous crisis that causes an increasingly high death rate. Applying machine learning to the computed-tomography (CT)-based COVID-19 diagnosis is essential and attracts the attention of the research community. This paper introduces an approach for simultaneously identifying COVID-19 disease and segmenting its manifestations on lung images. The proposed method is an asymmetric U-Net-like model improved with skip connections. The experiment was conducted on a light-weighted feature extractor called CRNet with a feature enhancement technique called atrous spatial pyramid pooling. Classifying between COVID-19 and non-COVID-19 cases recorded the highest mean scores of 97.1, 94.4, and 97.0% for accuracy, dice similarity coefficient (DSC) and F1 score, respectively. Alternatively, the respective highest mean scores of the classification between COVID-19 and community-acquired pneumonia were 99.89, 99.79, and 99.97%. The lesion segmentation performance was with the highest mean of 99.6 and 84.7% for, respectively, accuracy and DSC.

Risks and supply chain performance: globalization and COVID-19 perspectives

Purpose: This article aims to examine the simultaneous effect of risks on physical and intangible dimensions of supply chain performance under the globalization and Covid-19 perspectives. Design/methodology/approach: The manipulation of literature reviews together with the combination of Q-sort and empirical data in the construction industry to identify and assess risks and supply chain performance, is a novel approach in the supply chain risk management area. The analysis of Structural Equation Modeling that is able to calculate the simultaneous impact of various risks on supply chain performance, is used to validate this relationship. Findings: Global supply chains are currently facing interruptions caused by several sources of inherent uncertainties, e.g. natural disasters, war and terrorism, external legal issues, economic and political instability, social and cultural grievances, and diseases. The weaknesses of the current global supply chain have been revealed, resulting in delays, supply unfulfillment, labor shortages and demand fluctuation. These supply chain risks have a great on supply chain performance indicators, and the magnitude of their impact tends to increasingly impact in the context of globalization and the Covid-19 pandemic. Findings showed that the proposed risk models can be explained with Variance of supplier performance (25.5%), Innovation and learning (21.2%), Internal business (61.9%), Customer service (39.4%) and Finance (39.7%). Research limitations/implications: Supply chain managers should keep in mind acceptable cost/benefit trade-offs in corporate risk mitigation efforts associated with major contingency risks. In doing so, the proposed hypothesized model can be “a road map” to achieve this purpose. Our research favors the adoption of supply chain management strategies, e.g. postponement, speculation and avoidance. Originality/value: The trend toward globalization and the emergence of the Covid-19 pandemic increasing supply chain complexity are regarded as key drivers of supply chain risk and therefore enhance vulnerability to supply chain. © 2022, Emerald Publishing Limited.

Earlier extubation in a tertiary hospital micu: A quality improvement initiative

INTRODUCTION/HYPOTHESIS: Complications of Mechanical Ventilation (MV) are well-described and related to duration of exposure to the intervention. A protocolized approach to MV liberation is recommended by Critical Care society guidelines and avoidance of delay to MV liberation was recently selected as one of five 2021 Choosing Wisely® for Critical Care recommendations. Baseline data in our tertiary hospital Medical Intensive Care Unit (MICU) showed that the average time of extubation was 1:30PM, with only 16% of patients extubated in the morning before 10AM. These findings prompted a Quality Improvement (QI) initiative aimed at achieving earlier extubation of eligible patients. METHODS: A multidisciplinary QI project team was formed, with representation from attending physicians, respiratory therapists, nurses, and physicians-in-training. A SMART Aim was created in September of 2020, with a goal set for the rate of morning (6AM to 10AM) extubation for eligible patients to increase from 16% to 20% or greater by June of 2021. Countermeasures were developed based on root cause analysis and targeted early morning initiation of Spontaneous Breathing Trials (SBTs), limiting overnight sedation, and staff education on hospital SBT and extubation protocols. A novel telemedicine Respiratory Therapy service, initially formed in response to the COVID-19 pandemic, was leveraged to ensure early SBTs and sedation minimization. PDSA cycles were performed to optimize educational and telemedicine countermeasures. RESULTS: 334 patients were extubated during the study period. The cumulative rate of extubation between 6AM - 10AM increased from 16% in the pre-intervention period to 27% in the post-intervention period and an upward shift in the run chart baseline was observed. Reintubation rate within 48 hours was monitored as a balancing measure and did not increase in the post-intervention period. There was no shift in median ICU length of stay or median MV duration in the postintervention period. CONCLUSIONS: A multidisciplinary QI initiative was able to increase the rate of morning extubations in a tertiary hospital MICU. The initiative demonstrated the value of a novel telemedicine Respiratory Therapy service to ensure adherence to best practices and achieve improvements in quality of care.