Unsafe at home: the increased trend of domestic violence during the COVID-19 pandemic in Bangladesh

Purpose The pandemic situation has increased the domestic violence rate against women and children significantly around the world. However, it is difficult to measure the accurate rate of increased domestic violence because of restrictions and limited mobility in accessing help and reporting. This paper aims to highlight the current situation of the novel coronavirus 2019 (COVID-19) pandemic and domestic violence in Bangladesh. It also states the challenges of the unprecedented situation and how to encounter increasing domestic violence cases. Design/methodology/approach This paper is a viewpoint of the COVID-19 pandemic and domestic violence situation in Bangladesh. Accordingly, this paper includes a comprehensive literature review that summarises related articles and newspapers on domestic violence. Findings Bangladesh is one of the most vulnerable countries to COVID-19 because of its most dense population. Currently, the COVID-19 virus is spreading rapidly in all parts of Bangladesh. In Bangladesh, the COVID-19 pandemic is increasing domestic violence for women and girls. Because of the lockdown, financial stress and livelihood scarcity, domestic violence rates show an increasing tendency that should not be overlooked to ensure the safety and security of women and girls in Bangladesh. Originality/value This paper delivers information about the current situation of COVID-19 in Bangladesh and the challenges of domestic violence that have risen. This paper will be helpful to policymakers, government and non-government officials for developing effective social safety net interventions.

Coronavirus disease 2019 (COVID-19) pandemic: what is the level of knowledge, attitude, and practice in Kandahar, Afghanistan?

There is a rising concern for the rapid increase of COVID-19 confirmed cases in Kandahar province. From zero reported cases until 17th March 2020, then Kandahar saw a sudden rise in the cases by 16th May 2020. Decreased literacy rates, poor health education, lack of facilities, inconsistent government policies, and defying coronavirus safety advisory by the public have resulted in the rapid spread of COVID-19. The awareness and practices of the people towards the COVID-19 were significantly low. Therefore, the risk of coronavirus in Kandahar province is extremely high due to the aforementioned reasons. To overcome this virus, the local government must declare strict measures and provide the public with information about the severity and prevention mechanisms of this fatal disease. Mass and random diagnostic testing are required to track the actual infection rates, which can give a realistic picture of what is occurring. In this article, the current situation of COVID-19, available medical facilities, and public response to the ongoing pandemic in Kandahar, Afghanistan was highlighted.

Application of machine intelligence technology in the detection of vaccines and medicines for SARS-CoV-2.

Researchers have found many similarities between the 2003 severe acute respiratory syndrome (SARS) virus and SARS-CoV-19 through existing data that reveal the SARS's cause. Artificial intelligence (AI) learning models can be created to predict drug structures that can be used to treat COVID-19. Despite the effectively demonstrated repurposed drugs, more repurposed drugs should be recognized. Furthermore, technological advancements have been helpful in the battle against COVID-19. Machine intelligence technology can support this procedure by rapidly determining adequate and effective drugs against COVID-19 and by overcoming any barrier between a large number of repurposed drugs, laboratory/clinical testing, and final drug authorization. This paper reviews the proposed vaccines and medicines for SARS-CoV-2 and the current application of AI in drug repurposing for COVID-19 treatment.

Deep learning applications to combat the dissemination of COVID-19 disease: a review.

Recent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. Reverse transcription-polymerase chain reaction (RT-PCR) is known as one of the primary diagnostic tools. However, RT-PCR tests are costly and time-consuming; it also requires specific materials, equipment, and instruments. Moreover, most countries are suffering from a lack of testing kits because of limitations on budget and techniques. Thus, this standard method is not suitable to meet the requirements of fast detection and tracking during the COVID-19 pandemic, which motived to employ deep learning (DL)/convolutional neural networks (CNNs) technology with X-ray and CT scans for efficient analysis and diagnostic. This study provides insight about the literature that discussed the deep learning technology and its various techniques that are recently developed to combat the dissemination of COVID-19 disease.

Artificial intelligence technology for diagnosing COVID-19 cases: a review of substantial issues.

Today, the world suffers from the rapid spread of COVID-19, which has claimed thousands of lives. Unfortunately, its treatment is yet to be developed. Nevertheless, this phenomenon can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. In this study, the early diagnosis of this disease through artificial intelligence (AI) technology is explored. AI is a revolutionizing technology that drives new research opportunities in various fields. Although this study does not provide a final solution, it highlights the most promising lines of research on AI technology for the diagnosis of COVID-19. The major contribution of this work is a discussion on the following substantial issues of AI technology for preventing the severe effects of COVID-19: (1) rapid diagnosis and detection, (2) outbreak and prediction of virus spread, and (3) potential treatments. This study profoundly investigates these controversial research topics to achieve a precise, concrete, and concise conclusion. Thus, this study provides significant recommendations on future research directions related to COVID-19.