Multi-operator Variant of Differential Evolution and its Application in Classification of COVID-19 CT-scan Images

Novel coronavirus disease (COVID-19), caused by the virus (SARS-CoV-2), has drastically impacted human beings' lives since early 2020. The virus is constantly changing, and with mutations, it becomes diverse and spreads more easily. Several automatic COVID-19 diag-nostic tools are proposed that emphasize feature extraction mechanism from radiographical images using modern deep learning technology. The general idea is to leverage smart solutions of pre-trained networks for deep-feature processing. However, all the extracted features may not essentially contribute to the performance of the COVID-19 diag-nostic model, and hence an optimal subset of features must be discov-ered. Motivated by this, we propose a novel feature selection method based on multi-operator differential evolution (MODE), which helps to acquire optimal feature-subset. To show the efficacy of the proposed algorithm, we focus on applying the COVID-19 classification model through medical imaging. Eight advanced pre-trained architectures have been selected for COVID-19 feature extraction from CT-scan medi-cal imaging. After that, the proposed feature selection technique based on MODE is applied. A customized SVM kernel is implemented that supports feature classification. The result analysis shows the perfor-mance of the existing COVID-19 designs with the proposed feature selection technique, MODE, integrated with a customized SVM kernel. It even beats the existing state-of-the-art frameworks carried forward for COVID-19 diagnosis. We have observed that MODE feature selec-tion is suitable for fast COVID-19 detection, having overall accuracy of 85.27%.

Psychological Impact Among Newly Diagnosed Covid-19 Positive Cases

Background: India was one of the worst affected countries during the second wave of COVID-19 infection. The pandemic brought in a multitude of psychological problems leading to a negative impact on the mental health of affected individuals. Several studies across the globe have assessed the psychological impact of this pandemic in general and vulnerable populations with a scanty data in the assessment of those found positive for this condition. Material(s) and Method(s): This was a cross-sectional, descriptive and observational study conducted at a tertiary health care centre involved in the management of COVID-19 cases. Cases were assessed using a semi structured proforma for socio demographic and clinical details, Impact of Events Scale Revised (IES-R) and Patient Health Questionnaire- 9 S6(PHQ-9) to assess psychological impact. Descriptive and inferential statistics were used for data analysis. Result(s): A total of 60 individuals participated in the study. The mean age of the participants was 50.8 +/- 14.10 years, with a majority of males (65%). More than half (53%) of the individuals had minimal severity on IES-R while about 9% showed moderate to severe levels. About 32% had minimal depression while 25% had moderately severe or severe depression on PHQ-9 score. A significant positive correlation was observed between number of deaths due to COVID-19 infection in the family and IES-R scores. Conclusion(s): Higher levels of stress and depression were found among those found positive for COVID-19. This highlights the need for early assessment of psychological problems and timely intervention to avoid long term psychiatric sequelae to those affected by COVID-19 infection.

Mental health problems in health-care workers of tertiary level COVID-19 care centers in Central India

Background: The health-care workers (HCWs) who are overburdened during the COVID-19 pandemic are at increased risk of developing psychological disorders. Aim: The aim of this study was to assess the magnitude of psychological problems such as depression, anxiety, and fear of COVID-19 among the HCWs and to study their correlates. Material and Methods: The study is an online multicentric cross-sectional survey of mental health problems in the HCWs of three tertiary level COVID care centers in Central India. HCWs were assessed using the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder Scale-7 (GAD-7), and Fear of COVID-19 Scale. Results: Out of 467 HCWs assessed, 25.5% of the participants had depression (defined by PHQ-9 score of more than 5), whereas anxiety was present in 24.4% of the study subjects (defined by GAD-7 score of more than 5). Forty-six percent of the participants had medium-to-high levels of fear of COVID-19. Female gender, working in the nonclinical department, direct involvement in care of COVID-19 patients, perceived worsening of physical health status following the pandemic outbreak, and past history of psychiatric problem were the factors significantly associated with presence of depression as well as anxiety. Age of the participant had a positive correlation with fear of COVID-19 and a negative correlation with depression and anxiety levels. Conclusion: HCWs serving in COVID hospitals are vulnerable to develop mental health problems and appropriate screening measures and interventions should be designed so as to preserve mental health of this vital task force.

Evaluation of Psychological Impact of COVID-19 on Health-Care Workers.

BACKGROUND: Little information is available from India about the psychological impact of COVID-19 on helath-care workers. AIM: The current study aimed to evaluate the psychological issues among the health-care workers (HCW) during the COVID-19 pandemic. MATERIALS AND METHODS: An online survey using Survey Monkey® platform was carried out to evaluate depression (using Patient Health Questionnaire-9), anxiety (using Generalized Anxiety Disorder Questionnaire-7), and other psychological issues (using a self-designed questionnaire). RESULTS: The study sample comprised 303 participants with a mean age of 41.2 (standard deviation: 11.1) years. A majority of them were male (69%) and married (79.9%). Nearly half (46.2%) of the participants had either anxiety disorder or depression or both and 12.9% of HCW had suicidal behavior. Higher level of anxiety and depression scores were associated with being female, having undergone quarantine, directly involved in the care of COVID-19 patients, and younger age (<30 years). Higher prevalence of depression and anxiety disorder was seen in younger (<30 years) age group, being a doctor (compared to paramedics). In addition, higher prevalence of depression was seen in those who were directly involved in the care of patients with COVID-19 infection. CONCLUSION: About half of the HCWs are suffering from psychiatric morbidity, specifically anxiety, in the wake of the COVID-19 pandemic. There is a need to assess all the HCWs for psychiatric morbidity and provide them with psychological support.

A Cross-Sectional Study of Psychological Distress and Fear of COVID-19 in the General Population of India during Lockdown

Context: With relatively high transmission rate and fatal potential, the COVID-19 pandemic is responsible for widespread fear and psychological distress all over the world, including India. Aim: Assessment of these problems in the general population is the first step to address this problem. Settings and Design: We did an online survey using snowball sampling strategy through various social media communication platforms. Materials and Methods: Semi-structured format was used to collect sociodemographic data and COVID-19-related information. The Kessler's Psychological Distress Scale (K10) and the Fear of COVID-19 Scale were used for assessment psychological distress and fear, respectively. Results: A total of 530 study respondents had adequate participation from all socioeconomic strata, diverse educational and professional backgrounds, and from all parts of the country. Majority of the participants were from red zone districts of lockdown (72.8%) and considered the imposed lockdown as essential (98.7%), although many of them reported negative impact on their psychological state (38.9%). A substantial number (38%) of people reported psychological distress significantly (P < 0.05) associated with females, unmarried, students, lower socioeconomic status (SES), caretakers of COVID-19 patients, poor perceived physical health, and higher score on the Fear of COVID-19 Scale. Female participants and those belonging to lower SES and a red zone district also reported significantly (P < 0.05) higher degree of fear of COVID-19. Despite this, only about 10.9% of the respondents sought help through telephonic or online counseling and most (91.4%) of them found it helpful. Conclusions: The impact of COVID-19 pandemic on psychological health is catastrophic. Planned measures at local as well as national level are essential to avert this crisis.

MCNN: A deep learning based rapid diagnosis method for COVID-19 from the X-ray images

Due to the rapidly spreading nature of coronavirus, a pandemic situation has emerged around the world. It is affecting society at large that includes the global economy and public health too. It was found in recent studies that the novel and unknown nature of this virus makes it more difficult to identify and treat the affected patient in the early stage. In this context, a time-consuming method named reverse transcription-polymerase chain reaction (RT-PCR) is being used to detect the positive cases of COVID-19, which requires blood samples of the suspects to diagnose the disease. This paper presents a new deep learning-based method to detect COVID-19 cases using chest X-ray images as the recent studies show that the radiology images have relevant features that can be used to predict the COVID-19. The proposed method is developed for binary classification to identify that a person is infected with COVID-19 or not. A total of 2400 X-ray images are taken for the experimental work. It includes 1000, COVID-19, and 1000, non-COVID-19 images, 200, COVID-19, and 200, non-COVID-19 testing images. The proposed method has been compared with the existing state-of-the-art methods on various statistical parameters which give better results with higher accuracy in diagnosing the COVID-19 cases. The proposed method has obtained 98.25% accuracy, 98.49% precision, 98% sensitivity, 98.50% specificity, and 98.25% F1 score. © 2020 Lavoisier. All rights reserved.

Digital Image Analysis Is a Silver Bullet to COVID-19 Pandemic

The rise in the demand of computational intelligence tools and techniques has been seen as impressive technology to deal with the issues might face in several domains. In most applications, specially confined to medical sphere, its promising results set new benchmark which is hard to beat, and that’s why it emerges as an effective framework in respond to Corona Virus. This deadly virus, first found in China, quickly propagated from its source to entire world through human-to-human transmission, as human is seen as medium of its swift replication. The main challenge before nations is to discover felicitous treatments and suitable medical drugs, besides the uncertain patterns of pathogen. Not only soft intelligence, but it is accompanied by digital image analysis in the studies of lethal virus. Images, in the form of thermal screening or normal body scans, have always been elementary part of medical treatment process. It gives ease to remedial staff as data interpretation and presentation becomes intuitive. So the article is aiming to project how merits of digital image analysis incorporated with computational intelligence lift the barriers up in the way of Corona outbreak. The chapter will be providing the highlights of digital image process at the verge of COVID-19. The fundamentals of soft computing, computer vision and digital image processing will also be discussed. It will be supported by on-going medical studies, scientific experiments and research accounts to solve the complications arisen by novel Corona Virus. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Psychological impact of COVID-19 lockdown: An online survey from India.

BACKGROUND: The COVID-19 pandemic has led to a complete shut-down of the entire world and almost all the countries are presently in a "lockdown" mode. While the lockdown strategy is an essential step to curb the exponential rise of COVID-19 cases, the impact of the same on mental health is not well known. AIM: This study aimed to evaluate the psychological impact of lockdown due to COVID-19 pandemic on the general public with an objective to assess the prevalence of depression, anxiety, perceived stress, well-being, and other psychological issues. MATERIALS AND METHODS: It was an online survey conducted under the aegis of the Indian Psychiatry Society. Using the Survey Monkey platform, a survey link was circulated using the Whatsapp. The survey questionnaire included perceived stress scale, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Warwick-Edinburgh Mental Well-being Scale to assess perceived stress, anxiety, depression, and mental well-being, respectively. The survey link was circulated starting from April 6, 2020 and was closed on April 24, 2020. RESULTS: During the survey, a total of 1871 responses were collected, of which 1685 (90.05%) responses were analyzed. About two-fifth (38.2%) had anxiety and 10.5% of the participants had depression. Overall, 40.5% of the participants had either anxiety or depression. Moderate level of stress was reported by about three-fourth (74.1%) of the participants and 71.7% reported poor well-being. CONCLUSIONS: The present survey suggests that more than two-fifths of the people are experiencing common mental disorders, due to lockdown and the prevailing COVID-19 pandemic. This finding suggests that there is a need for expanding mental health services to everyone in the society during this pandemic situation.