scholarly journals COVID-19 Social Distance Violation and Face Mask Detection in Workplaces

2021 ◽  
Vol 9 (VII) ◽  
pp. 184-187
Author(s):  
Gurudatt P Kulkarni
Keyword(s):  
Face Mask ◽  
World Health ◽  
Security Measure ◽  
Proposed Model ◽  
Retail Outlets ◽  
High Hazard ◽  
Cctv Surveillance ◽  
Health Organization ◽  
Town Center ◽  
Viewpoint Planning

Social distancing is a suggested arrangement by the World Health Organization (WHO) to limit the spread of COVID-19 in broad daylight places. Most of governments and public wellbeing specialists have set the 2-meter physical removing as a compulsory security measure in retail outlets, schools, and other covered regions. In this exploration, we foster a conventional Deep Neural Network-Based model for mechanized individuals’ identification, following, and between individuals’ distances assessment in the group, utilizing basic CCTV surveillance cameras. The proposed model incorporates a YOLOv4-based system and opposite viewpoint planning for exact individuals’ identification and social removing checking in testing conditions, including individual’s impediment, incomplete perceivability, and lighting varieties. We additionally give an online danger appraisal conspire by factual examination of the Spatio-transient information from the moving directions and the pace of social removing infringement. We distinguish high-hazard zones with the most noteworthy chance of infection spread and diseases. This may assist specialists with updating the design of a public spot or to play it safe activities to relieve high-hazard zones. The effectiveness of the proposed approach is assessed on the Oxford Town Center dataset, with prevalent execution as far as precision and speed contrasted with three bests in class techniques.

scholarly journals Trends in access to anti‐malarial treatment in the formal private sector in Uganda: an assessment of availability and affordability of first‐line anti‐malarials and diagnostics between 2007 and 2018

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Denis Kibira ◽  
Anthony Ssebagereka ◽  
Hendrika A. van den Ham ◽  
Jimmy Opigo ◽  
Henry Katamba ◽  
...  
Keyword(s):  
Private Sector ◽  
Diagnostic Tests ◽  
Malaria Treatment ◽  
World Health ◽  
First Line ◽  
Cross Sectional ◽  
Malaria Rapid Diagnostic Tests ◽  
Retail Outlets ◽  
Health Action ◽  
Health Organization

Abstract Background Malaria is the single largest cause of illness in Uganda. Since the year 2008, the Global Fund has rolled out several funding streams for malaria control in Uganda. Among these are mechanisms aimed at increasing the availability and affordability of artemisinin-based combination therapy (ACT). This paper examines the availability and affordability of first-line malaria treatment and diagnostics in the private sector, which is the preferred first point of contact for 61% of households in Uganda between 2007 and 2018. Methods Cross-sectional surveys were conducted between 2007 and 2018, based on a standardized World Health Organization/Health Action International (WHO/HAI) methodology adapted to assess availability, patient prices, and affordability of ACT medicines in private retail outlets. A minimum of 30 outlets were surveyed per year as prescribed by the standardized methodology co-developed by the WHO and Health Action International. Availability, patient prices, and affordability of malaria rapid diagnostic tests (RDTs) was also tracked from 2012 following the rollout of the test and treat policy in 2010. The median patient prices for the artemisinin-based combinations and RDTs was calculated in US dollars (USD). Affordability was assessed by computing the number of days’ wages the lowest-paid government worker (LPGW) had to pay to purchase a treatment course for acute malaria. Results Availability of artemether/lumefantrine (A/L), the first-line ACT medicine, increased from 85 to100% in the private sector facilities during the study period. However, there was low availability of diagnostic tests in private sector facilities ranging between 13% (2012) and 37% (2018). There was a large reduction in patient prices for an adult treatment course of A/L from USD 8.8 in 2007 to USD 1.1 in 2018, while the price of diagnostics remained mostly stagnant at USD 0.5. The affordability of ACT medicines and RDTs was below one day’s wages for LPGW. Conclusions Availability of ACT medicines in the private sector medicines retail outlets increased to 100% while the availability of diagnostics remained low. Although malaria treatment was affordable, the price of diagnostics remained stagnant and increased the cumulative cost of malaria management. Malaria stakeholders should consolidate the gains made and consider the inclusion of diagnostic kits in the subsidy programme.

scholarly journals IoT and Deep Learning Based Approach for Rapid Screening and Face Mask Detection for Infection Spread Control of COVID-19

2021 ◽  
Vol 11 (8) ◽  
pp. 3495
Author(s):  
Shabir Hussain ◽  
Yang Yu ◽  
Muhammad Ayoub ◽  
Akmal Khan ◽  
Rukhshanda Rehman ◽  
...  
Keyword(s):  
Deep Learning ◽  
Low Cost ◽  
Face Mask ◽  
World Health ◽  
Rapid Screening ◽  
Screening System ◽  
Source Of Infection ◽  
The Face ◽  
Health Organization ◽  
Vaccine Distribution

The spread of COVID-19 has been taken on pandemic magnitudes and has already spread over 200 countries in a few months. In this time of emergency of COVID-19, especially when there is still a need to follow the precautions and developed vaccines are not available to all the developing countries in the first phase of vaccine distribution, the virus is spreading rapidly through direct and indirect contacts. The World Health Organization (WHO) provides the standard recommendations on preventing the spread of COVID-19 and the importance of face masks for protection from the virus. The excessive use of manual disinfection systems has also become a source of infection. That is why this research aims to design and develop a low-cost, rapid, scalable, and effective virus spread control and screening system to minimize the chances and risk of spread of COVID-19. We proposed an IoT-based Smart Screening and Disinfection Walkthrough Gate (SSDWG) for all public places entrance. The SSDWG is designed to do rapid screening, including temperature measuring using a contact-free sensor and storing the record of the suspected individual for further control and monitoring. Our proposed IoT-based screening system also implemented real-time deep learning models for face mask detection and classification. This module classified individuals who wear the face mask properly, improperly, and without a face mask using VGG-16, MobileNetV2, Inception v3, ResNet-50, and CNN using a transfer learning approach. We achieved the highest accuracy of 99.81% while using VGG-16 and the second highest accuracy of 99.6% using MobileNetV2 in the mask detection and classification module. We also implemented classification to classify the types of face masks worn by the individuals, either N-95 or surgical masks. We also compared the results of our proposed system with state-of-the-art methods, and we highly suggested that our system could be used to prevent the spread of local transmission and reduce the chances of human carriers of COVID-19.

scholarly journals Facial Recognition System for People with and without Face Mask in Times of the COVID-19 Pandemic

2021 ◽  
Vol 13 (12) ◽  
pp. 6900
Author(s):  
Jonathan S. Talahua ◽  
Jorge Buele ◽  
P. Calvopiña ◽  
José Varela-Aldás
Keyword(s):  
Facial Recognition ◽  
Face Mask ◽  
Recognition System ◽  
Classification Model ◽  
World Health ◽  
The Face ◽  
Recognition Systems ◽  
Facial Recognition System ◽  
Health Organization ◽  
Face Detector

In the face of the COVID-19 pandemic, the World Health Organization (WHO) declared the use of a face mask as a mandatory biosafety measure. This has caused problems in current facial recognition systems, motivating the development of this research. This manuscript describes the development of a system for recognizing people, even when they are using a face mask, from photographs. A classification model based on the MobileNetV2 architecture and the OpenCv’s face detector is used. Thus, using these stages, it can be identified where the face is and it can be determined whether or not it is wearing a face mask. The FaceNet model is used as a feature extractor and a feedforward multilayer perceptron to perform facial recognition. For training the facial recognition models, a set of observations made up of 13,359 images is generated; 52.9% images with a face mask and 47.1% images without a face mask. The experimental results show that there is an accuracy of 99.65% in determining whether a person is wearing a mask or not. An accuracy of 99.52% is achieved in the facial recognition of 10 people with masks, while for facial recognition without masks, an accuracy of 99.96% is obtained.

scholarly journals Clinical Pharmacist Intervention in Improving Health Outcomes by Reducing Physician’s Burden and Medication Errors: A Proposed Model

2020 ◽  
Vol 1 (2) ◽  
pp. 1-5
Author(s):  
Masood Raza Shahid ◽  
◽  
Ahmer Raza Muhammad ◽  
Aziz Shireen ◽  
Shahzad Sana ◽  
...  
Keyword(s):  
Clinical Pharmacist ◽  
Pharmacist Intervention ◽  
Health Care Team ◽  
World Health ◽  
Special Role ◽  
Team Members ◽  
Healthcare Settings ◽  
Proposed Model ◽  
Health Organization

Healthcare is a team effort. Each healthcare provider is like a member of the team with a special role. Some team members are doctors or technicians who help in diagnosing disease. Others are experts who help in treating disease or care for patients’ physical and emotional needs. Understanding the role of each member in healthcare settings can reduce the burden of duties. According to World Health Organization (WHO) reports, burden of workload on physicians is the main cause of medical errors each day practice and thousands of people die as a result each year. Such errors can be minimized by reducing the workload on physicians and strengthening the role of clinical pharmacists in healthcare settings. Key words: Health care; Team Members; Physicians; Clinical Pharmacist

scholarly journals A Research Study on Digital Transformation Inevitable In Post COVID Era - The New Normal in India

2021 ◽  
pp. 58-62
Author(s):  
Krishna Kulin Trivedi
Keyword(s):  
Research Study ◽  
Emergency Services ◽  
Virus Disease ◽  
Face Mask ◽  
Digital Transformation ◽  
World Health ◽  
New Normal ◽  
Corona Virus ◽  
Fast Pace ◽  
Health Organization

The whole world fights against the Corona Virus Disease which is also known as “COVID-19”. This new virus is an infectious disease which spreads through the droplets from the person infected with this virus coughs or sneezes, thus a person has to protect himself by wearing face mask, wash the hands frequently and maintain social distancing to stop the spread of this newly discovered virus corona virus. The infection is continuously increasing at a very fast pace and thus different countries according to the number of cases imposed complete lockdown where only emergency services like medical, and essentials like food, vegetables and milk was made available. The disease has been declared as the Pandemic by the world health organization due to the spread of the disease in the whole world. Thus, digital transformation was inevitable to adopted by all for the continual existence and control the spread of the disease of business and academic activities. This article is a research study on digital transformation which is inevitable in post Covid era which is the new normal in India.

scholarly journals A Comparative Study of Health Services’ Management of Adolescents and Youth in Selected Developed Countries and Iran: Developing a Model for Iran

2021 ◽  
pp. 5802-5816
Author(s):  
Razieh Moghaddam
Keyword(s):  
Factor Analysis ◽  
Health Service ◽  
Health Services ◽  
Health Indicators ◽  
Health Service Delivery ◽  
Developed Countries ◽  
World Health ◽  
Proposed Model ◽  
Health Organization ◽  
Practical Factors

Introduction: Nowadays, adolescent and youth’s health has become increasingly important. The world health organization (WHO) emphasizes the importance of evaluating the structure, process, and outcome of health services. This study was conducted to design a health services’ management of adolescents and youth model for the Iranian population, to improve young people's health. Method: This study is a comparative, quantitative-qualitative study. Countries were selected by comparing adolescent and youth health indicators based on population and availability of information. By studying the health services’ management of adolescents and youth, essential variables and dimensions in the initial model were identified, and a preliminary questionnaire was developed and approved by experts. One hundred seventy-eight final questionnaires were completed by experts. Exploratory factor analysis was performed to determine the practical factors (SPSS 20), and the model’s fit was examined by confirmatory factor analysis (Amos 24). Results: A total of 6 factors were identified as effective in health services’ management of adolescents and youth, including, health service package, human resources, financial resources, equipment and services’ provision, data & statistics information resources, and health service delivery management of adolescents and youth, With a maximum 0.97 operating load had the highest and equipment and services’ provision (0.53), had the least impact. Conclusion: The proposed model has the most significant impact on the management of health services’ management of adolescents and youth components.

scholarly journals Online National Health Agency Mask Guidance for the Public in Light of COVID-19: Content Analysis (Preprint)

2020 ◽  
Author(s):  
Linnea Laestadius ◽  
Yang Wang ◽  
Ziyad Ben Taleb ◽  
Mohammad Ebrahimi Kalan ◽  
Young Cho ◽  
...  
Keyword(s):  
Content Analysis ◽  
Language Proficiency ◽  
General Public ◽  
English Language ◽  
Health Agency ◽  
Face Mask ◽  
World Health ◽  
Language Version ◽  
The Status ◽  
Health Organization

BACKGROUND The rapid global spread of the coronavirus disease (COVID-19) has compelled national governments to issue guidance on the use of face masks for members of the general public. To date, no work has assessed how this guidance differs across governments. OBJECTIVE This study seeks to contribute to a rational and consistent global response to infectious disease by determining how guidelines differ across nations and regions. METHODS A content analysis of health agency mask guidelines on agency websites was performed in late March 2020 among 25 countries and regions with large numbers of COVID-19 cases. Countries and regions were assigned across the coding team by language proficiency, with Google Translate used as needed. When available, both the original and English language version of guidance were reviewed. RESULTS All examined countries and regions had some form of guidance online, although detail and clarity differed. Although 9 countries and regions recommended surgical, medical, or unspecified masks in public and poorly ventilated places, 16 recommended against people wearing masks in public. There were 2 countries that explicitly recommended against fabric masks. In addition, 12 failed to outline the minimum basic World Health Organization guidance for masks. CONCLUSIONS Online guidelines for face mask use to prevent COVID-19 in the general public are currently inconsistent across nations and regions, and have been changing often. Efforts to create greater standardization and clarity should be explored in light of the status of COVID-19 as a global pandemic.

scholarly journals A Deep Learning Approach to Detect COVID-19 Patients from Chest X-ray Images

AI ◽  
2020 ◽  
Vol 1 (3) ◽  
pp. 418-435
Author(s):  
Khandaker Haque ◽  
Ahmed Abdelgawad
Keyword(s):  
Deep Learning ◽  
World Health ◽  
X Rays ◽  
X Ray ◽  
Global Pandemic ◽  
Proposed Model ◽  
Dental Diseases ◽  
Chest X Ray ◽  
Artery Disease ◽  
Health Organization

Deep Learning has improved multi-fold in recent years and it has been playing a great role in image classification which also includes medical imaging. Convolutional Neural Networks (CNNs) have been performing well in detecting many diseases including coronary artery disease, malaria, Alzheimer’s disease, different dental diseases, and Parkinson’s disease. Like other cases, CNN has a substantial prospect in detecting COVID-19 patients with medical images like chest X-rays and CTs. Coronavirus or COVID-19 has been declared a global pandemic by the World Health Organization (WHO). As of 8 August 2020, the total COVID-19 confirmed cases are 19.18 M and deaths are 0.716 M worldwide. Detecting Coronavirus positive patients is very important in preventing the spread of this virus. On this conquest, a CNN model is proposed to detect COVID-19 patients from chest X-ray images. Two more CNN models with different number of convolution layers and three other models based on pretrained ResNet50, VGG-16 and VGG-19 are evaluated with comparative analytical analysis. All six models are trained and validated with Dataset 1 and Dataset 2. Dataset 1 has 201 normal and 201 COVID-19 chest X-rays whereas Dataset 2 is comparatively larger with 659 normal and 295 COVID-19 chest X-ray images. The proposed model performs with an accuracy of 98.3% and a precision of 96.72% with Dataset 2. This model gives the Receiver Operating Characteristic (ROC) curve area of 0.983 and F1-score of 98.3 with Dataset 2. Moreover, this work shows a comparative analysis of how change in convolutional layers and increase in dataset affect classifying performances.

Face mask detection application and dataset

2021 ◽  
Vol 27 (2) ◽  
Author(s):  
Daniel Matthias ◽  
Chidozie Managwu ◽  
O. Olumide
Keyword(s):  
Disease Transmission ◽  
Face Mask ◽  
World Health ◽  
The World ◽  
The Face ◽  
Monitoring And Enforcement ◽  
Health Organization ◽  
Experimental Findings ◽  
Recognition Software ◽  
Deep Learning Model

The COVID–19 pandemic is, without any doubt, changing our world in ways that are beyond our wildest imagination. In a bid to curb the spiraling negative fallouts from the virus that has resulted in a large number of casualties and security concerns. The World Health Organization, amongst other safety protocols, recommended the compulsory wearing of face masks by individuals in public spaces. The problem with the enforcement of this and other relevant safety protocols, all over the world, is the reluctance and outright refusal of citizens to comply and the inability of relevant agencies to monitor and enforce compliance. This paper explores the development of a CCTV–enabled facial mask recognition software that will facilitate the monitoring and enforcement of this protocol. Such models can be particularly useful for security purposes in checking if the disease transmission is being kept in check. A constructive research methodology was adopted, where a pre-trained deep convolutionary neural network (CNN) (mostly eyes and forehead regions) used and the most probable limit (MPL) was use for the classification process. The designed method uses two datasets to train in order to detect key facial features and apply a decision-making algorithm. Experimental findings on the Real-World-Masked-Face-Dataset indicate high success in recognition. A proof of concept as well as a development base are provided towards reducing the spread of COVID-19 by allowing people to validate the face mask via their webcam. We recommend that the use of the app and to further investigate the development of highly robust detectors by training a deep learning model with respect to specified face-feature categories or to correctly and incorrectly wear mask categories.

Transmission dynamics and quarantine control of COVID-19 in cluster community: A new transmission-quarantine model with case study for diamond princess

2021 ◽  
pp. 1-30
Author(s):  
Qingwu Gao ◽  
Jun Zhuang ◽  
Ting Wu ◽  
Houcai Shen
Keyword(s):  
Real Data ◽  
Transmission Dynamics ◽  
World Health ◽  
Substantial Impact ◽  
Global Pandemic ◽  
Proposed Model ◽  
Conduct Sensitivity Analysis ◽  
Community Transmission ◽  
Health Organization ◽  
And Control

Coronavirus Disease 2019 (COVID-19) is a zoonotic illness which has spread rapidly and widely since December, 2019, and is identified as a global pandemic by the World Health Organization. The pandemic to date has been characterized by ongoing cluster community transmission. Quarantine intervention to prevent and control the transmission are expected to have a substantial impact on delaying the growth and mitigating the size of the epidemic. To our best knowledge, our study is among the initial efforts to analyze the interplay between transmission dynamics and quarantine intervention of the COVID-19 outbreak in a cluster community. In the paper, we propose a novel Transmission-Quarantine epidemiological model by nonlinear ordinary differential equations system. With the use of detailed epidemiologic data from the Cruise ship “Diamond Princess”, we design a Transmission-Quarantine work-flow to determine the optimal case-specific parameters, and validate the proposed model by comparing the simulated curve with the real data. First, we apply a general SEIR-type epidemic model to study the transmission dynamics of COVID-19 without quarantine intervention, and present the analytic and simulation results for the epidemiological parameters such as the basic reproduction number, the maximal scale of infectious cases, the instant number of recovered cases, the popularity level and the final scope of the epidemic of COVID-19. Second, we adopt the proposed Transmission-Quarantine interplay model to predict the varying trend of COVID-19 with quarantine intervention, and compare the transmission dynamics with and without quarantine to illustrate the effectiveness of the quarantine measure, which indicates that with quarantine intervention, the number of infectious cases in 7 days decrease by about 60%, compared with the scenario of no intervention. Finally, we conduct sensitivity analysis to simulate the impacts of different parameters and different quarantine measures, and identify the optimal quarantine strategy that will be used by the decision makers to achieve the maximal protection of population with the minimal interruption of economic and social development.

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