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1.
Aging Medicine and Healthcare ; 13(3):139-146, 2022.
Article in English | EMBASE | ID: covidwho-2067647

ABSTRACT

Background/Purpose: As a result of the COVID-19 pandemic, changes in data collection methods have been introduced in research to ensure continuity despite physical distancing and lockdown restrictions. Our objective was to compare differences in physical and mental health of older adults participating in falls research using data collection methods pre-covid-19 pandemic (face-to-face) and during the pandemic (hybrid). Method(s): Individuals aged 60 years and over with at least one fall in the past 12 months, and controls with no history of falls in the past 12 months were recruited. Pre-pandemic, individuals were interviewed face-to-face exclusively, those interviews after the start of the pandemic were conducted virtually with physical assessments conducted face-to-face to minimize physical contact. Cognitive status, physical performance, psychological status, quality of life, physical activity, and social participation were measured. Result(s): Of the 145 participants of similar socio-demographic backgrounds, 69 were interviewed face-to-face, while 76 were assessed using a hybrid method. Differences were observed in presence of fall characteristics, with fewer fallers seeing a doctor and more fallers attending the emergency department after the start of the pandemic. After adjustment for baseline differences, participants interviewed using hybrid status had lower depression scores (OR (95%CI)=0.29(0.14-0.61)) and stress scores (OR(95%CI)=0.33(0.15-0.72)), but greater fear of falling (OR(95%CI)=2.16(1.04-4.48)) and reduced social participation (OR(95%CI)=2.64(1.20-5.79)). Conclusion(s): Alterations in data collection methods to overcome pandemic restrictions should take into consideration potential differences in individuals who agree to participate as well as the influence of major life events on the psychological status of participants. Copyright © 2022, Full Universe Integrated Marketing Limited. All rights reserved.

2.
Sustainability (Switzerland) ; 14(18), 2022.
Article in English | Scopus | ID: covidwho-2055362

ABSTRACT

In 2020, COVID-19 swept across the globe. To reduce the social harms caused by this public health event, nonprofit organizations (NPOs) cooperated with medical enterprises to produce reserves of emergency medical supplies. In practice, this cooperation was challenged by the different goals of NPOs and medical enterprises and the asymmetry of information between these parties. Enterprises are prone to irregularities or speculative behaviors that can result in insufficient production capacity during public health events, which increase disaster risks. Based on the principal–agent relationship of NPOs and enterprises, this study analyzed a game model between NPOs and enterprises under information asymmetry;constructed an incentive model for reserve emergency medical supply production capacity;and solved the optimal reward and punishment coefficients of NPOs, optimal effort level of enterprises, and benefits of disaster reduction. The study also verified the validity of the model using numerical examples and a sensitivity analysis. In taking up the findings of the study, this paper discusses the effects of several important exogenous variables on the optimal decision strategies of NPOs and enterprises and offers management-related insights for NPOs. © 2022 by the authors.

3.
Journal of the Intensive Care Society ; 23(1):80-81, 2022.
Article in English | EMBASE | ID: covidwho-2043047

ABSTRACT

Introduction: Logbooks are now ubiquitous in medical practice, aiding in provision of evidence of competency for training progression and revalidation processes. The Faculty of Intensive Care Medicine (FICM) recommends all practitioners keep a logbook, but does not mandate a particular one. During COVID19, redeployment from other specialties into ICU has meant many training opportunities have been difficult to evidence.1,2 Logbooks provide an evidence base for documenting educational experiences, identifying opportunities and learning from good practice.3 Objectives: The NorthWest Intensive Care Unit Logbook (NW ICU Logbook) provides a digital, spread-sheet based, easy-to-use, mobile-compatible personal logbook for ICU practitioners of all grades. Originally created for personal use, it has been made available for free for all. We used analytical software to track its use and spread so as to better understand the desire for such logbooks. Methods: Google Analytics were built into the logbook download website to track views and downloads. Data is collected anonymously and provides evidence of its appeal. Extrapolation of its spread suggests an increased focused on governance within global ICM. Prospective, real-time data is continuously collected regarding website traffic, number of downloads, geographical and device data. This provides a rich source of anonymised data to better understand the use of a product. Already, many businesses use such software, but this method is still relatively new within medicine. Results: The logbook has been downloaded over 3000 times from over 30 countries. Although interest is heavily centred in the UK, hotspots of downloads have also occurred in India, Egypt and Middle East. This is likely due to existing links and partnerships between hospitals. The logbook has been responsive to change, and several versions have been created based on feedback from users. The global appeal suggests an increased focus on educational governance and therefore presents many opportunities for further data collection and understanding of educational capacity and quality. Furthermore, expansion of the dataset may enable better understanding of human resources for health, caseload and global critical care trends. Conclusion: There continues to be an interest for an easyto-use and fit-for-purpose logbook for ICU practitioners. This logbook may form a template for further development. For example, an app would allow anonymised big data to be collected which can provide an evidence-base for regional variation in educational opportunities and achievements. Also, the global interest already shown may allow anonymised data which can add to evidence regarding human resources for health in low resource settings, further contributing to the understanding and advancing larger global health agendas within acute and emergency care.4 This provides a powerful opportunity for organisations to collect data for further research.

5.
British Columbia Medical Journal ; 64(3):125-125, 2022.
Article in English | Web of Science | ID: covidwho-1976291
6.
Vox Sanguinis ; 117(SUPPL 1):109-110, 2022.
Article in English | EMBASE | ID: covidwho-1916318

ABSTRACT

Background: Globally, the COVID-19 pandemic has caused reduced donor attendance and disrupted blood collection activities. This has impacted the blood supply of many blood transfusion services (BTS). To secure the nation's blood supply, BTS resort to media appeal as an additional measure to call on potential and existing donors to come forward to donate when the blood supply is low. Singapore's Health Sciences Authority (HSA) partners with the Singapore Red Cross (SRC) to drive the awareness of blood donation and recruit donors. HSA and SRC had launched media appeals prior to the pandemic. During the pandemic, there were two media reports proactively run by the media reporters. Aims: This study aimed to gain insights into donor profiles, behaviours and blood donation trends before and during the COVID-19 pandemic, and during media appeals/media reports. This was to enable HSA and SRC to develop new measures and strategies to improve donor recruitment and retention. Methods: Blood donation records from 1st January 2018 to 31st December 2020 were extracted from HSA's blood bank computer system and de-identified. Data transformation was performed using Python (version 3.7.0). Only whole blood donors with successful donations were included in this analysis. Donors were classified according to donor type and donor behaviour. Geospatial analysis was conducted to identify geographical patterns of blood donation. Descriptive analyses were carried out using Tableau Desktop (version 2021.4.3) for data visualization. Results: A total of 72,536 and 74,683 donors donated in 2018 and 2019 respectively. This declined by 4.9% to 71,054 donors in 2020. Despite this, the number of whole blood donations increased from 116,789 in 2019 to 117,272 in 2020. Donation frequency increased from 1.56 in 2019 to 1.65 in 2020, with an 1.4% increase in new donors in 2020. The proportion of donors of Chinese ethnicity increased in 2020. Donors aged 16 to 19 years old drastically declined by 34% in 2020. There was a shift in donor behaviour with majority (78.3%) donating at blood banks as compared to the pre-pandemic period (64.4% in 2019). There were two media appeals (Sep 2018, Dec 2019) and two media reports (Feb 2020, Jun 2020). There was a spike in donors by 65.7% and 72.9% in 2018 and 2019, respectively after media appeals. There was a large spike in donors by 215% after the February 2020 media report and a 27.3% increase after the June 2020 media report. 49.7% and 39.7% of new donors who responded to media appeals returned to donate the following year. The data analytics insights and recommendations from this study were presented at the HSA-SRC Steering Committee and the Donor Recruitment & Retention Workgroup in March 2022. These included a recruitment and retention focus on youth donors, encouraging appointment bookings after donation, leveraging fixed sites and donor mobile app to retain donors etc. Summary/Conclusions: Data analytics is pivotal in helping HSA and SRC to better understand blood donation trends during the COVID- 19 pandemic and following media appeals/reports. New measures and strategies were developed to better engage donors so that they would return to donate and donate more regularly. Predictive analytics and data modelling could be explored as additional tools to secure the nation's blood supply. These will increase the resilience of the Singapore's National Blood Programme and ensure a sustainable blood supply to meet the increasing blood demand.

7.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research ; 25(7):S460-S460, 2022.
Article in English | EuropePMC | ID: covidwho-1904923
8.
Frontiers in Environmental Science ; 10:10, 2022.
Article in English | Web of Science | ID: covidwho-1887097

ABSTRACT

This work is reporting the advocation of a public Malaysia University for the environmental protection through sustainable waste practices ever since its ban on the use of the "White Coffin " initiative in circa 2008, a flagship for environmental activism on its different campuses targeting to get rid of polystyrene containers. This initiative was not halted but served as a spark of flare for a sustainability journey up to this very day. The effort to realise a sustainable tomorrow as the vision of higher education sector, including the studied Malaysian University has been integrating efforts from various parties. This includes the formation of "Kampus Sejahtera " (wellness campus), regional centre of expertise, sustainability course, and more recently the sustainability month, sustainability network, and most importantly, the local NGO-industrial-academia collaboration in the path toward a sustainable tomorrow. The work in this article delineates a case study in implementing sustainable waste practice from the start to the status, in one of the Malaysian public universities which is ranked 39th in Times Higher Education University in Global Impact Ranking 2021, and top in Malaysia. More emphasis will be placed on the current initiative of the local NGO-industrial-academia collaboration as case study in the midst of the COVID-19 pandemic.

9.
Philippine Journal of Science ; 150(5):999-1015, 2021.
Article in English | CAB Abstracts | ID: covidwho-1870814

ABSTRACT

Coronavirus disease 2019 (COVID-19) continues to devastate the world's health and economy, affecting all aspects of life leading to widespread social disruption. Even as several vaccines have been developed, their availability in developing countries is limited and their efficacy against the variants of SARS-CoV-2 (severe acute respiratory syndrome-coronavirus 2) needs to be continuously assessed. The World Health Organization (WHO) has acknowledged that vaccines alone will not overcome the global challenges of COVID-19. Medicinal plants may provide the needed support. Herein, we identify Philippine medicinal plants that possess phytochemicals with potential anti-SARS-CoV-2 activity and/or immunomodulatory properties that may strengthen one's immune system against COVID-19. These plants were selected from 100 of the best-studied Philippine medicinal plants with antiviral and immunomodulatory properties. The general antiviral and specific anti-SARS-CoV-2 activities and immunomodulatory properties of the phytochemicals that these plants contained were searched. While many compounds assessed individually using in vitro and in silico techniques suggest potential anti-SARS-CoV-2 or immunomodulatory effects, this review sought to identify the medicinal plants which contain these compounds and which, based on literature, have the best potential application against COVID-19. These plants are Allium spp. bulbs (bawang), Andrographis paniculata (Burm.f.) Nees leaves (sinta), Cocos nucifera L. oil (niyog), Euphorbia hirta L. leaves (tawa-tawa), Euphorbia neriifolia L. leaves (sorosoro), Moringa oleifera Lam. leaves (malunggay), Ocimum basilicum L. leaves (balanoy), Piper nigrum L. seeds (paminta), Vitex negundo L. leaves (lagundi), and Zingiber officinale Roscoe rhizome (luya). This review provides a shortlist that can guide research on possible solutions to COVID-19 using Philippine medicinal plants.

10.
Diabetic Medicine ; 39(SUPPL 1):116-117, 2022.
Article in English | EMBASE | ID: covidwho-1868635

ABSTRACT

Background and Aims: During the covid-19 pandemic revisions were recommended to the gestational diabetes diagnostic criteria. Given the characteristics of our inner city multi-ethnic cohort, we continued with the NICE 2015 criteria. We aimed to determine the incidence of gestational diabetes during the first wave of the covid-19 pandemic. Methods: Women diagnosed with gestational diabetes in March-July 2020 were retrospectively reviewed and compared to two separate historical time-matched cohorts (03-07/ 2018 and 03-07/ 2017). Maternal demographics, gestational diabetes incidence and fetal outcomes were compared. Results: 953 pregnancies were registered in 2020, 963 in 2018 and 1162 in 2017. The highest gestational diabetes incidence was observed in the covid-19 cohort (12.6% (n = 120), 7.3% (n = 70) and 4.4% (n = 52) respectively, p < 0.001). On average, women were diagnosed with GDM later in 2020 (mean gestational age (GA) 28.6 weeks, 27.0 and 27.0 weeks, p < 0.001). Mean ( ± SD) age, height, and early pregnancy weight/ body mass index were similar. Proportional differences in women with gestational diabetes of non-white ethnicity were exhibited, with the lowest proportion in 2020 (77.0%, 86.4% and 82.9% respectively, p < 0.001). Mean ( ± SD) fetal birth weight varied across the groups (3237.5 ( ± 473)g, 3117 ( ± 647)g and 2981 ( ± 845)g, p < 0.001). There were no differences in adjusted fetal birth weight centiles. Mean (SD) GA at birth was higher in 2020 (38.8 ( ± 1.26), 38.4 ( ± 2.38), 37.60 ( ± 5.1) weeks, p = 0.03). Conclusions: A significant increase in the diagnosis of gestational diabetes during the covid-19 epidemic was observed. The implementation of national lockdowns may have resulted in reduced physical activity and excess gestational weight gain, which could explain this.

11.
Australasian Journal of Dermatology ; 63:89-89, 2022.
Article in English | Web of Science | ID: covidwho-1848752
12.
16th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2021 ; : 458-463, 2021.
Article in English | Scopus | ID: covidwho-1846124

ABSTRACT

As COVID-19 continues to spread around the world, and non-pharmacological interventions (NPIs) continue to be strengthened, the impact of COVID-19 on the film industry has not yet been clearly quantified. In this study, the Difference-in-Difference model is used to quantify the impact of the COVID-19 pandemic on the box office. Results indicate that the COVID-19 pandemic has a significant negative effect on the daily global box office. Additionally, based on a research dataset containing information on movies and COVID-19, ten machine learning methods were used to build a prediction model of the cumulative global box office. The experimental results showed that Extremely Randomized Trees had the best predictive performance, and it was found that COVID-19 features helped improve the predictive performance of several models. © 2021 IEEE.

13.
16th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2021 ; : 697-702, 2021.
Article in English | Scopus | ID: covidwho-1846121

ABSTRACT

The greatest threat to global health is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-Cov-2) currently. COVID-19 was declared as a global pandemic on March 11, 2020. For this highly contagious disease, the way of human-to-human transmission has forced us to implement large-scale COVID-19 testing worldwide. On February 21, 2021, 120 million people have already undergone COVID-19 testing. The large scale of COVID-19 testing has driven innovation in strategies, technologies, and concepts for managing public health testing. It is an unprecedented global testing program. In this study, we describe the role of COVID-19 testing while establishing a comprehensive and validated research dataset that includes data from 189 countries and 893 regions between August 8, 2019, and March 3, 2021. Through our analysis, we observed that the more COVID-19 testings provided, the more confirmed cases were detected. The availability of large-scale COVID-19 testing is indispensable to fully control the outbreak, as it is the main way to cut off the source of COVID-19 transmission. Then we used this dataset to predict the COVID-19 detection capabilities of each country by Machine Learning, Ensemble Learning, and Broad Learning System. Experimental results show that Broad Learning System significantly outperformed the Machine Learning. The R2 of predicted the ability of the COVID-19 testing can reach 0.999921. © 2021 IEEE.

14.
Acupuncture & Electro-Therapeutics Research ; 47(2):195-201, 2022.
Article in English | Web of Science | ID: covidwho-1810380

ABSTRACT

Objective : Summarize the experience of transporting patients in the pre-hospital emergency center of our hospital from January 20, 2020 to May 2020 during the outbreak of novel coronavirus pneumonia in Zhuzhou City, and formulate a series of transport strategics. Methods: During the novel coronavirus pneumonia epidemic, review the relevant experience of the medical staff and drivers in the pre-hospital emergency center of Zhuzhou Central Hospital to improve the procedures for the transfer of patients during the epidemic. Results: As of the time when patients with novel coronavirus pneumonia in our city are cleared, none of the medical staff in the pre-hospital emergency center of Zhuzhou Central Hospital has been infected, and the city's patients in need of pre-hospital emergency treatment have been treated in an orderly manner. In conjunction with our hospital's epidemic prevention and control expert team, combined with the actual situation in the region, we jointly formulated a series of transfer procedures for Zhuzhou Central Hospital to comply with the region during the epidemic. Conclusion: During the novel coronavirus pneumonia epidemic, all patients received by the pre-hospital emergency center of our hospital were transferred in a timely and safe manner, and a series of transfer procedures were developed.

15.
Environmental Science-Nano ; : 11, 2022.
Article in English | Web of Science | ID: covidwho-1778647

ABSTRACT

Hydrogen peroxide (H2O2) solution and its aerosols are common disinfectants, especially for urgent reuse of personal protective equipment during the COVID-19 pandemic. Highly sensitive and selective evaluation of the H2O2 concentration is key to customizing the sufficient disinfection process and avoiding disinfection overuse. Amperometric electrochemical detection is an effective means but poses challenges originated from the precarious state of H2O2. Here, an atomic Co-N-x-C site anchored neuronal-like carbon modified amperometric sensor (denoted as the CoSA-N/C@rGO sensor) is designed, which exhibits a broad detection range (from 250 nM to 50 mM), superior sensitivity (743.3 mu A mM(-1) cm(-2), the best among carbon-based amperometric sensors), strong selectivity (no response to interferents), powerful reliability (only 2.86% decay for one week) and fast response (just 5 s) for residual H2O2 detection. We validated the accuracy and practicability of the CoSA-N/C@rGO sensor in the actual H2O2 disinfection process of personal protective equipment. Further characterization verifies that the electrocatalytic activity and selective reduction of H2O2 is determined by the atomically dispersed Co-N-x-C sites and the high oxygen content of CoSA-N/C@rGO, where the response time and reliability of H2O2 detection is determined by the neuronal-like structure with high nitrogen content. Our findings pave the way for developing a sensor with superior sensitivity, selectivity and stability, rendering promising applications such as medical care and environmental treatment.

17.
11th Annual IEEE Global Humanitarian Technology Conference (IEEE GHTC) ; : 1-7, 2021.
Article in English | Web of Science | ID: covidwho-1759028

ABSTRACT

Data-driven approaches to traffic monitoring have important applications in tracking vehicle mobility in the COVID-19 pandemic lockdowns. We report preliminary results of a pipeline that uses the You Only Look Once (YOLOv3) and the Simple Online and Realtime Tracking (SORT) algorithms to count and classify vehicles in traffic videos. We correlate vehicle counts in Katipunan Avenue, Metro Manila and Google COVID-19 Community Mobility Reports from May to August 2020 and we show that vehicle detection data may be considered for monitoring community response to changes in COVID-19 lockdown stringency levels.

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