Study on the Comparison of Three Typical Gas Flow Standards for Calibrating Low Gas Flowmeter

A gas flowmeter for measuring low flow rate has been widely used in the field of medical, health, environmental protection, energy industry, aerospace, etc. To against Covid-2019, the requirement on the low flow rate has been increasing dramatically. At present, the typical standard devices for calibrating low gas flowmeter mainly include standard bell provers of gas flow, standard piston provers of low gas flow and standard laminar of low gas flow. Different measuring principles are adopted among these typical standard devices. To ensure the consistency of these typical standard devices, a comparison test is performed. The standard devices used in the comparison are of the same accuracy grade, with an extended uncertainty of 0.2%(k=2). The piston-type gas flow calibrator of grade 1.0 is selected as the transfer standard, and three flow points with high flow rate, medium flow rate and low flow rate are selected for test. The consistency of measurement results is evaluated by normalized deviation En. The comparison results are acceptable which show that three typical standard devices are accurate and reliable. © FLOMEKO 2022.All rights reserved

Towards Lifting the Trade-off between Accuracy and Adversarial Robustness of Deep Neural Networks with Application on COVID 19 CT Image Classification and Medical Image Segmentation

Deep neural networks (DNNs) are vulnerable to adversarial noises. Adversarial training is a general strategy to improve DNN robustness. But training a DNN model with adversarial noises may result in a much lower accuracy on clean data, which is termed the trade-off between accuracy and adversarial robustness. Towards lifting this trade-off, we propose an adversarial training method that generates optimal adversarial training samples. We evaluate our methods on PathMNIST and COVID-19 CT image classification tasks, where the DNN model is ResNet-18, and Heart MRI and Prostate MRI image segmentation tasks, where the DNN model is nnUnet. All these four datasets are publicly available. The experiment results show that our method has the best robustness against adversarial noises and has the least accuracy degradation compared to the other defense methods. © 2023 SPIE.

Epidemiological characteristics of four times of community transmission of COVID-19 in Hebei

Objective To analyze the epidemiological characteristics of community transmission of the coronavirus disease 2019 (COVID-19) caused by four imported cases in Hebei Province, and to provide a scientific basis for the prevention and control of the disease. Methods Descriptive epidemiological methods were used to analyze the epidemiological characteristics of four community-transmitted COVID-19 outbreaks reported in the China Disease Control and Prevention Information System from January 1, 2020 to December 31, 2021 in Hebei Province. Results From January 1, 2020 to December 31, 2021, four community-transmitted COVID-19 outbreaks caused by imported COVID-19 occurred in Hebei Province, respectively related of Hubei (Wuhan) Province, Beijing Xinfadi market, Overseas cases and Ejina banner of Inner Mongolia Autonomous Region. Total of 1 656 cases (1 420 confirmed cases and 236 asymptomatic cases) were reported, including 375 cases in phase A (From January 22 to April 16, 2020), and phase B (from June 14 to June 24, 2020) 27 cases were reported, with 1 116 cases reported in the third phase (Phase C, January 2 to February 14, 2021), and 138 cases reported in the fourth phase (Phase D, October 23 to November 14, 2021). The 1 656 cases were distributed in 104 counties of 11 districts (100.00%), accounting for 60.46% of the total number of counties in the province. There were 743 male cases and 913 female cases, with a male to female ratio of 0.81:1. The minimum age was 13 days, the maximum age was 94 years old, and the average age (median) was 40.3 years old. The incidence was 64.01% between 30 and 70 years old. Farmers and students accounted for 54.41% and 14.73% of the total cases respectively. Of the 1 420 confirmed cases, 312 were mild cases, accounting for 21.97%;Common type 1 095 cases (77.11%);There was 1 severe case and 12 critical cases, accounting for 0.07% and 0.85%, respectively. 7 patients died from 61.0 to 85.7 years old. The mean (median) time from onset to diagnosis was 1.9 days (0-31 days), and the mean (median) time of hospital stay was 15 days (1.5-56 days). Conclusions Four times in Hebei province COVID-19 outbreak in scale, duration, population, epidemic and type of input source, there are some certain difference, but there are some common characteristics, such as the outbreak occurs mainly during the legal holidays or after starting and spreading epidemic area is mainly in rural areas, aggregation epidemic is the main mode of transmission, etc. To this end, special efforts should be made to strengthen the management of people moving around during holidays, and strengthen the implementation of epidemic prevention and control measures in places with high concentration of people. To prevent the spread of the epidemic, we will step up surveillance in rural areas, farmers' markets, medical workers and other key areas and groups, and ensure early detection and timely response.Copyright © 2022 China Tropical Medicine. All rights reserved.

Role of toll-like receptors in the pathogenesis of COVID-19: Current and future perspectives

The coronavirus disease 2019 (COVID-19) pandemic underlines a persistent threat of respiratory tract infectious diseases and warrants preparedness for a rapid response. At present, COVID-19 has had a serious social impact and imposed a heavy global burden on public health. The exact pathogenesis of COVID-19 has not been fully elucidated. Since the outbreak of COVID-19, a renewed attention has been brought to Toll-like receptors (TLRs). Available data and new findings have demonstrated that the interaction of human TLRs and SARS-CoV-2 is a vital mediator of COVID-19 immunopathogenesis. TLRs such as TLR2, 4, 7 and 8 are potentially important in viral combat and activation of immunity in patients with COVID-19. Therapeutics targeting TLRs are currently considered promising options against the pandemic. A number of TLR-targeting immunotherapeutics are now being investigated in preclinical studies and different phases of clinical trials. In addition, innovative vaccines based on TLRs under development could be a promising approach for building a new generation of vaccines to solve the current challenges. In this review, we summarize recent progress in the role of TLRs in COVID-19, focusing the new candidate drugs targeting TLRs, the current technology and potential paths forward for employing TLR agonists as vaccine adjuvants.Copyright © 2023 The Scandinavian Foundation for Immunology.

Role of the neighborhood environment in psychological resilience

Psychological resilience of residents is an important but often neglected component of community and urban resilience. This study explores what neighborhood environment features contribute to better psychological resilience. Using a survey conducted in Greater Melbourne during a COVID-19 pandemic lockdown, we examined the role of the neighborhood physical and social environments in mitigating the psychological shock of the pandemic. Overall, we found that suburban residents are more resilient in mental health than those in the inner city. In particular, the mental health of residents living in middle-density suburbs is least likely to be severely impacted. We further found that neighborhood walkability, vegetation cover, and social cohesion all contribute to better psychological resilience. Walkability and social cohesion influence psychological resilience indirectly through affecting the perceived risks of COVID-19 infection and satisfaction with neighborhood during the lockdown, whereas neighborhood greenery has a direct and beneficial effect on psychological resilience. These findings imply that planning interventions to improve neighborhood walkability and greenness, and foster social cohesion may help improve the psychological resilience of local residents, and hence promote urban resilience. These findings also support middle-density development, which promotes walkability and proximity to nature, as well as a close-knit community. © 2023 Elsevier B.V.

An Empirical Study of the Impact of COVID-19 on OSS Development

In this paper, we propose an analytical model that can analyze the impact of emergencies on open source software (OSS) development. As the core of this model, a metric system is used to comprehensively describe the OSS development process, which includes three dimensions: team activity, development activity, and development risk, with a total of 30 metrics. To demonstrate the effectiveness of the model, we construct an empirical study analyzing the impact of COVID-19 on OSS development. This study is based on the development process events between January 2019 and April 2022 belonging to 50 selected open source projects on GitHub. The results show that more than 72.4% of projects were negatively impacted following the COVID-19 outbreak. Interestingly, we observe that variants of covide-19 did not exacerbate its impact on software development. On the contrary, some project development activities have obviously resumed, indicating that the development team has adapted and gradually got rid of the impact of the epidemic. © 2022 IEEE.

Spectrum changes of pediatric dermatological disorders before and during the COVID-19 pandemic in China: A single national center for children's health experience

Background: The sudden COVID-19 has changed people's living habits, and skin diseases closely related to lifestyle have also changed quietly. We aimed to analyze the changing of pediatric dermatological disorders spectrum before and during the COVID-19 pandemic in China. Method(s): This retrospective study encompasses consecutive patients attending a number of dermatological outpatient clinics in National Center for Children's Health from 1 January 2019 and 31 December 2021. The information about the season, age, number, disease type and origin of the patients was filled in for all the patients. The diseases were sub-classified on etiological basis. Result(s): The total number of patients was 449032, including 323142 newly diagnosed patients, with a male/female ratio of 1.15:1. The patients were mainly school-age children. 91.3% of the patients suffered from a single skin disease. During the epidemic of COVID-19-epidemic, Atopic Dermatitis (AD )and other types of dermatitis constituted the main diseases, followed by infectious skin diseases, urticaria, erythema and drug responsive skin diseases, and finally parasites and bite responsive skin diseases. The top three skin diseases ranked in descending order of incidence from 2019 to 2021 were the same, followed by AD, urticaria and papular urticaria. During the epidemic period, the proportion of patients with molluscum contagiosum, verruca vulgaris and vitiligo increased. Because of wearing masks, the proportion of infectious skin diseases transmitted by respiratory tract has decreased significantly. In addition, pediatric telemedicine can be used to increase timely access and improve practical efficiency during the epidemic. Conclusion(s): The pediatric dermatological disorders spectrum has changed during the epidemic of COVID-19. AD is the most common skin disease, and the proportion of infectious skin diseases has decreased significantly. During the epidemic, pediatric internet medical services were fully used to promote the sustainable development of children's skin health.Copyright © 2023

Evaluating the optimised font size and viewing time of online learning in young children: a multicentre cross-sectional study.

OBJECTIVES: Near viewing distance (VD) and longer viewing times are associated with myopia. This study aimed to identify the font size and viewing time that guarantee the appropriate VD and pixels per degree (PPD) for children's online learning. DESIGN: This cross-sectional study comprised two experiments. In experiment A, participants read text in five font sizes on three backlit displays (a personal computer, a smartphone and a tablet), an E-ink display and paper for 5 min per font size. In experiment B, participants watched videos for 30 min on three backlit displays. SETTING: The Peking University People's Hospital in Beijing (China) and the School of Ophthalmology and Optometry, Wenzhou Medical University (Zhejiang Province, China). PARTICIPANTS: Thirty-five participants completed experiment A. Ten of them participated in experiment B. PRIMARY AND SECONDARY OUTCOME MEASURES: VDs were measured by Clouclip. The corresponding PPD was calculated. RESULTS: In experiment A, font size and display type significantly affected VD (F(4840)=149.44, p<0.001, ES (Effect size)=0.77; F(4840), p<0.001, ES=0.37). VDs were >33 cm for all five font sizes on the PC, the tablet and paper and for 18-pt on the smartphone and 16-pt on E-ink. PPD for 16-pt on the PC, 14-pt on the tablet and all five font sizes on the phone were >60. In experiment B, VD increased over the four previous 5 min periods but decreased slightly on tablets and PCs in the fifth 5 min period. PPD was >60. CONCLUSION: Children demonstrated different VDs and PPDs based on font size and display type. To ensure a 33 cm VD and 60 PPD, the minimum font size for online reading should be 18-pt on smartphones, 16-pt on PCs and E-ink, 10.5-pt on tablets and 9-pt on paper. More attention should be given to children's VD with continuous video viewing of more than 25 min. TRIAL REGISTRATION NUMBER: ChiCTR2100049584.

Conclusion

The health risks of socially vulnerable groups, such as the elderly, the sick, and the disabled, are significantly elevated under the COVID-19 epidemic. Therefore, the different factors affecting the use of information technology by socially vulnerable groups under COVID-19 are explored at the level of the use of emerging information technology. The impact on the information behavior of socially vulnerable groups under COVID-19 is also explored at the level of information behavior, including health information needs, the digital divide phenomenon, and the utilization of public information services. Based on the above findings, the current status of information behavior research for socially vulnerable groups is combined. Future research directions of information technology and information behavior for socially vulnerable groups are proposed. First, to improve the research theory of information behavior of socially vulnerable groups regarding information technology. Second, to apply big data technology and data analysis technology to explore the information technology adoption behavior of socially vulnerable groups in-depth. Third, to construct the information behavior model of socially vulnerable groups based on empirical research cases. Fourth, to use information technology for socially vulnerable groups according to information technology and the barriers faced by socially vulnerable groups in using information technology, and to provide strategies for using information technology that meet the needs of socially vulnerable groups. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Mining the Health Information Needs of COVID-19 Patients Based on Social Q&A Community

COVID-19 has become a global pandemic, and COVID-19 patients are in a medical dilemma with no effective treatment and no effective drugs. The questions and answers in the social Q&A community can reveal the characteristics and evolution rules of the health information needs of COVID-19 patients. Using the Q&A data in Baidu Zhidao (https://zhidao.baidu.com/ ) as the research object, using the web crawlers to capture the data, automatic topic recognition on the acquired data by constructing an LDA topic model, exploring the content of COVID-19 patients' health information needs, and revealing the change rule of Q&A publication volume and health information need topics from the time dimension. Combining statistical information such as the number of answers, the number of likes, and the level of respondents, cluster analysis is used to reveal the changing rules of social characteristics and health information need topics. By analyzing the Q&A data on COVID-19 patients in Baidu Zhidao, it is found that the topic distribution of health information needs topic is relatively concentrated. Moreover, the number of Q&A and the types of health information needs to be changed in different development periods. There are differences in social characteristics that correspond to different topics of health information needs. Through in-depth analysis of the characteristics of health information needs of COVID-19 patients in the social Q&A community, on the one hand, it is beneficial for COVID-19 patients to obtain the required health information content timely. On the other hand, it is beneficial to optimize the community information display mechanism and improve the organization of information resources. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Mining Engineering Education Pre and Post the COVID Pandemic and Some Ideas for the Future

The pandemic forced all businesses globally to rethink operations. Higher education institutions experienced similar disruptions, especially those with large cohorts of foreign students. The technology employed in the mining industries, it is evolving rapidly and requires novel and more specialized expertise in the face of an impending skilled labour shortage. This paper strategizes how mining education could improve and align with the needs of the mining industry and students, post-pandemic. ©

Dual Windows Are Significant: Learning from Mediastinal Window and Focusing on Lung Window

Since the pandemic of COVID-19, several deep learning methods were proposed to analyze the chest Computed Tomography (CT) for diagnosis. In the current situation, the disease course classification is significant for medical personnel to decide the treatment. Most previous deep-learning-based methods extract features observed from the lung window. However, it has been proved that some appearances related to diagnosis can be observed better from the mediastinal window rather than the lung window, e.g., the pulmonary consolidation happens more in severe symptoms. In this paper, we propose a novel Dual Window RCNN Network (DWRNet), which mainly learns the distinctive features from the successive mediastinal window. Regarding the features extracted from the lung window, we introduce the Lung Window Attention Block (LWA Block) to pay additional attention to them for enhancing the mediastinal-window features. Moreover, instead of picking up specific slices from the whole CT slices, we use a Recurrent CNN and analyze successive slices as videos. Experimental results show that the fused and representative features improve the predictions of disease course by reaching the accuracy of 90.57%, against the baseline with an accuracy of 84.86%. Ablation studies demonstrate that combined dual window features are more efficient than lung-window features alone, while paying attention to lung-window features can improve the model's stability. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Double Hydrogen-bonding Reinforced High-Performance Supramolecular Hydrogel Thermocell for Self-powered Sensing Remote-Controlled by Light

Non-contact human-machine interaction is the future trend for wearable technologies. This demand is recently highlighted by the pandemic of coronavirus disease (COVID-19). Herein, an anti-fatigue and highly conductive hydrogel thermocell with photo-thermal conversion ability for non-contact self-powering applications is designed. Double hydrogen-bonding enhanced supramolecular hydrogel is obtained with N-acryloyl glycinamide (NAGA) and diacrylate capped Pluronic F68 (F68-DA) via one-step photo-initiated polymerization. The supramolecular hydrogel can accommodate saturated electrolytes to fulfill the triple function of ionic crosslinking, heat-to-electricity conversion, and light response of thermocell. Eminently, the thermocell stands out by virtue of its high seebeck coefficient (-2.17 mV K−1) and extraordinary toughness (Fatigue threshold ≈ 3120 J m−2). The self-powering ability under the control of light heating is explored, and a model of a non-contact "light-remoted” sensor with self-powered and sensing integrated performance remote-controlled by light is constructed. It is believed that this study will pave the way for the non-contact energy supply of wearable devices. © 2023 Wiley-VCH GmbH.

Epidemiological characteristics of four times of community transmission of COVID-19 in Hebei

Objective To analyze the epidemiological characteristics of community transmission of the coronavirus disease 2019 (COVID-19) caused by four imported cases in Hebei Province, and to provide a scientific basis for the prevention and control of the disease. Methods Descriptive epidemiological methods were used to analyze the epidemiological characteristics of four community-transmitted COVID-19 outbreaks reported in the China Disease Control and Prevention Information System from January 1, 2020 to December 31, 2021 in Hebei Province. Results From January 1, 2020 to December 31, 2021, four community-transmitted COVID-19 outbreaks caused by imported COVID-19 occurred in Hebei Province, respectively related of Hubei (Wuhan) Province, Beijing Xinfadi market, Overseas cases and Ejina banner of Inner Mongolia Autonomous Region. Total of 1 656 cases (1 420 confirmed cases and 236 asymptomatic cases) were reported, including 375 cases in phase A (From January 22 to April 16, 2020), and phase B (from June 14 to June 24, 2020) 27 cases were reported, with 1 116 cases reported in the third phase (Phase C, January 2 to February 14, 2021), and 138 cases reported in the fourth phase (Phase D, October 23 to November 14, 2021). The 1 656 cases were distributed in 104 counties of 11 districts (100.00%), accounting for 60.46% of the total number of counties in the province. There were 743 male cases and 913 female cases, with a male to female ratio of 0.81∶1. The minimum age was 13 days, the maximum age was 94 years old, and the average age (median) was 40.3 years old. The incidence was 64.01% between 30 and 70 years old. Farmers and students accounted for 54.41% and 14.73% of the total cases respectively. Of the 1 420 confirmed cases, 312 were mild cases, accounting for 21.97%;Common type 1 095 cases (77.11%);There was 1 severe case and 12 critical cases, accounting for 0.07% and 0.85%, respectively. 7 patients died from 61.0 to 85.7 years old. The mean (median) time from onset to diagnosis was 1.9 days (0-31 days), and the mean (median) time of hospital stay was 15 days (1.5-56 days). Conclusions Four times in Hebei province COVID-19 outbreak in scale, duration, population, epidemic and type of input source, there are some certain difference, but there are some common characteristics, such as the outbreak occurs mainly during the legal holidays or after starting and spreading epidemic area is mainly in rural areas, aggregation epidemic is the main mode of transmission, etc. To this end, special efforts should be made to strengthen the management of people moving around during holidays, and strengthen the implementation of epidemic prevention and control measures in places with high concentration of people. To prevent the spread of the epidemic, we will step up surveillance in rural areas, farmers′ markets, medical workers and other key areas and groups, and ensure early detection and timely response. © 2022 China Tropical Medicine. All rights reserved.

A Wushu Posture Recognition System Based on MediaPipe

With the development of information technology such as computer vision and human-computer interaction, online physical education has become an active field of current physical education research. Especially with COVID-19, a significant number of people are restricted to learning and exercising motor skills in small spaces, but most of the movement cannot be carried out in narrow environment. Wushu is exempt from this restriction, so it is often used in online physical education in China. In this context, we propose a Wushu posture recognition system based on camera and MediaPipe for tracking hand, head and body movements of users. According to the Landmarks returned by Mediapipe, we designed recognition algorithms for Fist, Palm, Hook, Tiger Talon, Forward Lunge, Horse Stance and Empty Step. By testing 400 photos, the experimental results show that these algorithms can effectively identify these movements. From there, we built a system using Python to help users perform Wushu training independently, safely, and efficiently without a teacher. © 2022 IEEE.

Prediction and evaluation of the SARS-CoV-2 epidemic using an improved SEIR model

The present work propose an improved SEIR model that considers isolation and repeated nucleic acid detection factors. It was applied to the Kashgar Region, Xinjiang, China, to predict the changing trend of the number of confirmed cases and the number of susceptible individuals in Kashgar, and to evaluate and analyze local policy interventions. Model perform four predictive analyses of the epidemic situation in Kashgar. Comprehensive nucleic acid testing, isolation of asymptomatic patients, increasing isolation time and different proportions of the population isolated, control of population flow. Improved kinetic parameters were obtained using the Monte Carlo method. The theoretical estimation of the epidemic using the improved SEIR infectious disease dynamics model was in good agreement with the actuality of the epidemic in Kashgar. The analysis showed that in the areas with large area and dense population, repeat nucleic acid detection, quarantine of asymptomatic individuals and control the contact rate between people can quickly and effectively inhibit development of the local epidemic. © 2022 IEEE.

Differential Evolution Based Simulated Annealing Method for Vaccination Optimization Problem

Infectious diseases pose a severe threat to human health, especially the outbreak of COVID-19. After the infectious disease enters the stage of large-scale epidemics, vaccination is an effective way to control infectious diseases. However, when formulating a vaccination strategy, some restrictions still exist, such as insufficient vaccines or insufficient government funding to afford everyone's vaccination. Therefore, in this paper, we propose a vaccination optimization problem with the lowest total cost based on the susceptible-infected-recovered (SIR) model, which is called the Lowest Cost Of Vaccination Strategy (LCOVS) problem. We first establish a mathematical model of the LCOVS problem. Then we propose a practical Differential Evolution based Simulated Annealing (DESA) method to solve the mathematical optimization problem. We use the simulated annealing algorithm (SA) as a local optimizer for the results obtained by the differential evolution algorithm (DE) and optimized the mutation and crossover steps of DE. Finally, the experimental results on the six data sets demonstrate that our proposed DESA can achieve a more low-cost vaccination strategy than the baseline algorithms. IEEE

Understanding mental stress and skin aging connection among dermatologists and psychologists through real world evidence

Preaging is an emerging concept in China whereby young women are looking for skin aging solutions. Among the intrinsic and extrinsic causes of skin aging, mental stress was highlighted as a possible cause of preaging in young women. The COVID-19 pandemic has further impacted the mental well-being of the younger generation, with 44% of Asian women aged 18 to 34 under poor mental well-being based on WHO-5. While 76.5% of dermatologists agreed that there is a strong connection between stress and skin aging, there is limited evidence on the pathophysiology. The aim of this research is to explore how clinicians understand the impact of stress and the biologic pathways connecting stress and skin aging. A quantitative survey with 60 dermatologists and 60 psychologists from China and Japan was conducted to assess the link between stress and skin aging. Overall, 69.2% of both health care professionals agree that psychological stress has a significant link to skin aging. Three meta-themes were perceived by clinician as possible pathways connecting psychological stress and skin aging, including stress hormone, inflammation, and overactive immune system. While all health care professionals have heard of inflammaging, only 52% are very familiar with the concept. Both groups agree that unresolved acute inflammatory response can accelerate skin aging. Surprisingly, a significant difference was observed in that psychologists believe more strongly than dermatologists that chronic low-grade inflammation accelerates skin aging. This study highlights the need for further fundamental research, which could help clinicians provide appropriate recommendations for patients under psychological stress.

Antibacterial Cellulose Fibers Spun from Ionic Liquid and Enriched with Plant Essential Oils

The COVID-19 outbreak has seen the widespread use of personal protective equipment, especially antibacterial fibers. In this work, ionic liquid (IL) is used as a solvent to fabricate antibacterial fibers combining plant essential oils (PEOs) with cellulose. PEOs are buried in microcapsules first or mixed directly with IL-cellulose spinning dopes to prepare a series of composite fibers. The internal structures, surface and cross morphologies, thermal stability, mechanical properties, antibacterial activity, washing stability, and biocompatibility of these fibers are investigated and analyzed in-depth further. Artemisia microcapsule fiber (AMCRCF) with a break strength of 30.07 MPa is obtained. Besides, the antibacterial activity rates of AMC-RCF against Escherichia coli and Staphylococcus aureus are 89.8 and 97.8%, and the fibers still have a long-lasting antibacterial effect after 30 standard washes. Furthermore, the antibacterial fibers exhibit excellent biocompatibility. This research provides a green approach for the fabrication of the antibacterial fibers with long-lasting antibacterial activity and good biocompatibility.

Hospitalisation During Lockdown – Patients' Bed's-Eye View

Background: Global COVID pandemic and lockdowns have affected the patterns of hospital presentations for non-COVID related illnesses. Apprehension and perceived risk of hospitalisation has been postulated to be a significant deterrent to presentation. This study aims to explore pandemic and lockdown related concerns with regards to hospital admission from a patient’s perspective. Method: A cross sectional study was undertaken in the form of inpatient questionnaire for patients admitted to coronary care unit and the cardiology ward during level 4 lockdown. Questionnaire included six questions designed to gather patient perception of the impact of lockdown on their hospital presentation. Results: Out of 91 patients who completed the questionnaire, 41 (45%) were >70 years old. Twenty (22%) patients answered that lockdown delayed or affected their decision to present to hospital. Within this cohort, there was a statistical difference between those aged 70 years and younger and over 70 years old (16/50 [32%] versus 4/41 [10%], p=0.011). Conclusion: Apprehension and concerns regarding the risk of COVID was prevalent in a significant proportion of patients and affected/delayed their decision to present to hospital. This may partly explain lower rates of presentation during the pandemic.