ABSTRACT
Background: In 2016, the Government of Bangladesh (GoB) established a teleconsultation service called Shastho Batayon to increase access to physicians. During COVID-19 pandemic, health care access became limited due to movement restrictions. In response, GoB made Shastho Batayon toll free, publicized the number through media, increased the number of call center doctors, introduced automated messages on COVID-19 preventive measures, and developed a scoring system to classify risk groups for COVID-19. Objectives and Methods: In this case report, we describe how an existing national teleconsultation service can be utilized in a low- and middle-income country to address primary health care needs during a public health emergency. We conducted secondary analysis of Shastho Batayon service data from January to April 2020. Results: The total calls for doctor's consultation increased during the pandemic. Prepandemic, Shastho Batayon received less than 20,000 calls per month. In March 2020, when the first cases of COVID-19 were confirmed, Shastho Batayon services received 60,811 calls for doctor's consultation, which increased to 125,660 calls in April, 2020. The doctor's consultation for primary care has increased for all conditions. Shastho Batayon services screened 28,944 patients with the influenza-like illness or COVID-19-like symptoms in March and April, 2020, provided preventive measures, advice, and referral to designated hospitals based on a national guideline. Conclusions: In public health emergencies such as COVID-19 pandemic, teleconsultation services can help provide prevention guidelines, debunk misinformation, identify risk categories, and refer people to appropriate service and facilities in a timely manner.
ABSTRACT
The latest 5G technology is being introduced the Internet of Things (IoT) Era. The study aims to focus the 5G technology and the current healthcare challenges as well as to highlight 5G based solutions that can handle the COVID-19 issues in different arenas. This paper provides a comprehensive review of 5G technology with the integration of other digital technologies (like AI and machine learning, IoT objects, big data analytics, cloud computing, robotic technology, and other digital platforms) in emerging healthcare applications. From the literature, it is clear that the promising aspects of 5G (such as super-high speed, high throughput, low latency) have a prospect in healthcare advancement. Now healthcare is being adopted 5G-based technologies to aid improved health services, more effective medical research, enhanced quality of life, better experiences of medical professionals and patients in anywhere-anytime. This paper emphasizes the evolving roles of 5G technology for handling the epidemiological challenges. The study also discusses various technological challenges and prospective for developing 5G powered healthcare solutions. Further works will incorporate more studies on how to expand 5G-based digital society as well as to resolve the issues of safety-security-privacy and availability-accessibility-integrity in future health crises.
ABSTRACT
Background: Although mental health is an important part of health and wellbeing, very little is known about the impact of the COVID-19 pandemic on the mental health of marginalized communities like urban slum dwellers. Our study estimated the prevalence of generalized anxiety disorder and insomnia among the residents of the informal settlements of Dhaka, Bangladesh, during the COVID-19 pandemic. Methods: A cross-sectional phone-based survey was conducted from October to November 2020 among adult residents of five informal settlements of Dhaka city randomly chosen from an existing Urban Health and Demographic Surveillance Systems (UHDSS) run by icddr,b. Data on Generalized Anxiety Disorder-7 (GAD-7) and Insomnia Severity Index (ISI) were collected. A multinomial logistic regression was performed to assess the associated factors of anxiety and insomnia. Results: Of the total 586 participants, the prevalence of mild to severe anxiety and insomnia were 53% and 43%, respectively. As per the multinomial regression analysis, participants with mild anxiety were significantly more likely to be older (>50 years) and afraid of COVID-19 infection. Likewise, participants with moderate/severe anxiety were significantly more likely to share less household facilities (e.g., toilet, kitchen, water) (OR: 2.23; 95% CI: 1.31-3.79), to have difficulties in food availability (OR: 2.76; 95% CI: 1.10-6.93), to be afraid of self (OR: 5.27; 95% CI: 2.82-9.88), and to worry about the family members (OR: 2.26; 95% CI: 1.23-4.17) getting infected. Participants with mild insomnia were significantly more likely to share fewer household facilities and be afraid of being infected with COVID-19 infection. Moreover, participants with moderate/severe insomnia were significantly more likely to be female (OR: 1.90; 95% CI: 1.02-3.56), to receive food aid (OR: 0.50; 95% CI: 0.29-0.88), to be afraid of self (OR: 3.85; 95% CI: 1.81-8.19), and to worry about someone like friends or neighbors (OR: 2.45; 95% CI: 1.07-5.58) getting infected with COVID-19. Conclusions: We found elevated prevalence of both anxiety and insomnia among the urban poor of Bangladesh in the context of COVID-19. This indicates the importance of integrating mental health in the mitigation and recovery efforts related to similar crises for the urban poor in the future.
ABSTRACT
The novel coronavirus disease (COVID-19) has spread over 219 countries of the globe as a pandemic, creating alarming impacts on health care, socioeconomic environments, and international relationships. The principal objective of the study is to provide the current technological aspects of artificial intelligence (AI) and other relevant technologies and their implications for confronting COVID-19 and preventing the pandemic's dreadful effects. This article presents AI approaches that have significant contributions in the fields of health care, then highlights and categorizes their applications in confronting COVID-19, such as detection and diagnosis, data analysis and treatment procedures, research and drug development, social control and services, and the prediction of outbreaks. The study addresses the link between the technologies and the epidemics as well as the potential impacts of technology in health care with the introduction of machine learning and natural language processing tools. It is expected that this comprehensive study will support researchers in modeling health care systems and drive further studies in advanced technologies. Finally, we propose future directions in research and conclude that persuasive AI strategies, probabilistic models, and supervised learning are required to tackle future pandemic challenges.