COVID-19 SIR model: Bifurcation analysis and optimal control

This paper proposes a SIR epidemic model with vital dynamics to control or eliminate the spread of the COVID-19 epidemic considering the constant population, saturated treatment, and direct-indirect transmission rate of the model. We demonstrate positivity, boundness and calculate the disease-free equilibrium point and basic reproduction number from the model. We use the Jacobian matrix and the Lyapunov function to analyze the local and global stability, respectively. It is observed that indirect infection increases the basic reproduction number and gives rise to multiple endemic diseases. We perform transcritical, forward, backward, and Hopf bifurcation analyses. We propose two control parameters (Use of face mask, hand sanitizer, social distancing, and vaccination) to minimize the spread of the coronavirus. We use Pontryagin's maximum principle to solve the optimal control problem and demonstrate the results numerically.

Examining channel choice preferences for grocery shopping during the Covid-19 pandemic

Research on grocery shopping channel preferences has been growing in the wake of the Covid-19 pandemic. However, few studies have utilized the discrete choice experiment (DCE) to elicit choices in hypothetical scenarios. Moreover, attitudinal factors, which may better explain preference heterogeneity, are rarely considered. Given that the evolution of shopping behavior in the context of the Covid-19 pandemic has huge implications for transportation planning and modeling, this study aims to examine consumers' grocery shopping channel preferences through a DCE that was constructed with three grocery shopping channels (home delivery, curbside pickup, and in-store) and five time–cost attributes (product price, shopping time, delivery time, delivery cost, and travel time). 8,603 responses were elicited from 1,229 Florida residents between February and April 2021. Information on various aspects of respondents' shopping attitudes as well as their socio-demographic and household attributes, grocery shopping activities, and distance to the grocery store were also collected. Using mixed logit modeling for analyses, results indicate that individuals with low education, in low- to middle-income earning households, with three or more household vehicles, and having full access to a vehicle tended to prefer in-store shopping. Also, perceived security risk, pro-alternative mobility options, pro-local store shopping, and shorter distances to grocery stores predisposed individuals toward in-store shopping. Alternatively, females, young and middle-aged individuals, workers, and individuals in large households tended to prefer home delivery and curbside pickup. Technology savviness, pro-environment, pro-online shopping, and shopping enjoyment were also drivers of home delivery and curbside pickup purchases, while cost and time consciousness did not show significant effects. Overall, the findings in this study have implications for retailers, transportation planners, and policymakers. © 2023 Tongji University and Tongji University Press

Impact of COVID-19 on Smallholder Aquaculture Farmers and Their Response Strategies: Empirical Evidence from Bangladesh

Bangladesh's aquaculture sector has contributed progressively to the nation's economy over the years, but the COVID-19 pandemic has impeded fish farmers' access to markets, reduced their production and sales capacity, resulted in lower income, and increased food security vulnerability. This study assesses how COVID-19 affects smallholder fish farmers and their response strategies by employing data collected from 250 fish farmers and traders from intensive fish-growing areas of Bangladesh. The results reveal that most farmers experienced difficulty obtaining inputs, and the price of those inputs skyrocketed during the COVID-19 period, resulting in several months of decreased production and operations. As a result of COVID-19, farm gate prices for silver carp, ruhu, common carp, grass carp, and tilapia fish dropped by 25%, 23%, 23%, 22%, 23%, and 40%, respectively. On the other hand, fish feed prices were found to increase significantly. Reduced income from fish farming and other sources has triggered a significant drop in capital for farming operations and production capacity improvement, leading to food insecurity. The most common coping strategies include reduced buying from the market (vegetables, fruits, meat, milk, etc.), relying on less expensive or less preferred food, purchasing food on credit, and selling assets. Notably, due to COVID-19, a new mode of marketing has evolved as an adaptation strategy in the fish marketing system, such as the use of the mobile phone (18%) and Facebook/internet to sell fish directly to the customer (16%). The sector requires short-term financial assistance to assist fish actors with production and marketing challenges. © 2023 by the authors.

Promoting agri-food systems resilience through ICT in developing countries amid COVID-19

An increasing body of literature has demonstrated COVID-19's harmful impact on agri-food systems, which are a major source of livelihood for millions of people worldwide. Information and communication technology (ICT) has been playing an increasing role in enhancing agri-food systems' resilience amid COVID-19. In this study, the PRISMA approach was employed to perform a systematic review of the literature from January 2020 to December 2021 on the overall impact of COVID-19 on agri-food system networks and ICT's role in enhancing agri-food system resilience in developing countries. This study reveals that COVID-19 has posed abundant obstacles to agri-food systems actors, including a lack of inputs, technical support, challenges to selling the product, transportation barriers, and low pricing. These impediments result in insufficient output, unforeseen stock, and revenue loss. COVID-19's restrictions have caused a significant food deficit by disrupting the demand and supply sides of the agri-food system networks. A high number of small-scale farmers have had to deal with food insecurity. As a result of the cumulative effects, actors in the agri-food system are getting less motivated to continue producing. This study also argues that many challenges in the agri-food systems can be overcome using ICTs, including maintaining precise farm management, product marketing, and access to production inputs. To assist stakeholders in coping with, adapting to, and building resilience in the agri-food system networks, this article emphasizes the critical need to turn to and expand the application of advanced agricultural ICTs to meet the world's growing needs for food production and to ensure the resilience and sustainability of farming systems, particularly in the face of a pandemic like COVID-19. Copyright © 2023 Alam, Khatun, Sarker, Joshi and Bhandari.

Implementing and sustaining lean, buyer-supplier role, and COVID-19 pandemic: insights from the garment industry of Bangladesh

PurposeThis study aims to explore the challenges in implementing and sustaining lean in garment supplier factories and the buyer-supplier role in mitigating lean barriers in a typical situation and pandemic. Design/methodology/approachFollowing a qualitative research approach and multiple embedded case study method, data were collected through in-depth interviews with senior managers of one lead buyer and their four key garment supplier factories in Bangladesh. Within and cross-case analysis, techniques were applied to understand the context-oriented lean challenges and buyer-supplier role in mitigating the challenges. FindingsThe study findings demonstrate that garment suppliers are less prepared and unsystematic in lean implementation having limited capabilities and less preparation. Moreover, they have limited support from buyers, less commitment from top management and employee resistance to implementing lean. Lean challenges become more intense because of the COVID-19 pandemic. However, buyer-supplier responsible, cooperative and collaborative behaviour can mitigate lean challenges. Research limitations/implicationsWhereas many stakeholders may be responsible for lean challenges, this study explores dyadic role between buyer and supplier only based on a single lead buyer and their four suppliers. Hence future studies could consider more buyers and suppliers for a holistic understanding. Practical implicationsThis study could help buyers and suppliers understand the underlying causes of lean implementation challenges in garment supplier factories and their role in sustaining lean reducing the challenges, particularly in a pandemic. Originality/valueTo the best of the authors' knowledge, for the first time, this study depicts how buyer and supplier can play their due roles to mitigate lean challenges in garment supplier factories in a pandemic situation.

Implementation of a community-based referral project to improve access to emergency obstetric and newborn care in Rohingya population during COVID-19 pandemic in Bangladesh

Introduction The delay in seeking emergency obstetric care leads to significant maternal morbidity and mortality and can worsen during pandemics, especially in humanitarian conflict settings with low uptake of obstetric services. To mitigate the challenges related to the second delay caused by lack of transport in the COVID-19 pandemic, the organisation United Nations Population Fund implements a community-based referral project called Referral Hub in the Rohingya refugee population in Bangladesh. The objective of the paper is to describe the implementation process of the Referral hub and present clients' utilisation and perception of the service. Methods Findings from part of a larger mixed-method study, the analysis of the standard operating protocol of the intervention, secondary data of routine utilisation of the 12 referral hubs between January and August 2020, 21 key informant interviews and a community survey among 100 pregnant women are presented in this paper. Results The findings show an increasing trend in the referral hub utilisation and a strong recommendation of the service. Conclusion Due to a robust referral mechanism by collaborating with the community and engaging accessible and free of cost transport service, the intervention has high potential to improve access to facility care in low-resource and humanitarian contexts, especially during pandemics. Copyright ©

Consumers' Online Buying Behaviour during COVID-19 Pandemic Using Structural Equation Modeling

Due to the pandemic, businesses turned to alternatives and took up online marketing. E-marketing is a versatile tool for streamlining business processes, reducing managerial costs, reducing turnaround time, maintaining social distance, staying at home, protecting against viruses, and illuminating relationships with customers and business partners. Therefore, this research examined the factors affecting consumers' online purchase behaviour during the COVID-19 pandemic using partial least square structural equation modeling (PLS-SEM). Both quantitative and descriptive analysis methods were used. A standardized questionnaire was used to collect data from a sample of 200 local consumers in Bangladesh. A partial least square structural equation modeling (PLS-SEM) approach was used to evaluate the data and test the hypotheses. PLS-SEM showed that web design, price, administrative and product had a positive and significant relationship with consumers' online buying behaviour during the pandemic. This research adds theoretical contributions by evaluating the changes of consumers’ online buying behaviour during the COVID-19 pandemic. © All rights reserved 2022 Transnational Press London

Acceptance of E-Learning Among University Students During Covid-19 Crisis: Bangladesh Perspective

COVID-19 pandemic has dramatically transformed the global education system to a great extent. In a short period, e-learning has been adopted globally as an alternative teaching-learning medium. However, this sudden transition raises many concerns about e-learning acceptability. To make a clear inference, this study investigated the acceptance of e-learning (perceived usefulness, and perceived ease of use) among university-level students using the Technology Acceptance Model (TAM). The empirical analysis was performed on a sample of 694 university students in Bangladesh during the COVID-19 crisis. Findings revealed that students' overall e-learning acceptability was not adequate (32.8%), a significant number of students (46.8%) were not satisfied with e-learning experience and that majority (70.2%) of students preferred face-to-face education systems for their future study. The study also highlighted the underlying factors that negatively affect students' e-learning acceptance such as lack of technological skills, less familiarity with e-learning, lack of simplicity, low productivity, inefficiency, and so on. The overall findings of this study are intended to assist stakeholders to understand the gaps that need to be addressed immediately to increase students 'e-learning acceptability in the future.

Predicting Covid-19 Test Report Using Data Mining Techniques Based on The Second Wave in Bangladesh

Coronavirus (Covid-19) is a disease that spreads from one person to another very quickly. The whole world is facing this Covid-19 pandemic now and Bangladesh is also not out of it. After the first wave, now the second wave is going on in Bangladesh. As the second wave is spreading faster than the first wave and the test process of Covid-19 is very time-consuming. As a result, before getting the test report, a person infected with Covid-19 and spreads this virus to other people as he doesn't know whether he is infected with Coronavirus or not. To create a dataset, we have asked some patients from our nearby people who live in Faridpur, Joypurhat, and Cumilla district and collected their data who have tested for Covid-19 during the second wave. We have collected some of their symptoms that appeared before their Covid-19 test. With this dataset, we have used some data mining approach to predict whether a patient is tested positive or negative. We have applied two algorithms here. Among them, Naive Bayes gives the highest accuracy which is 80%. © 2021 IEEE.

Development of a Low-Cost, Compact, and Portable Experimental Kit for Online Engineering Statics Course

Online education is expanding rapidly. The ongoing COVID-19 pandemic has forced many universities to move from conventional, face-to-face instruction to hybrid or entirely online instruction. To overcome this unprecedented situation, instructors have modified course content and laboratories to be available virtually while trying to make them as interactive as possible. Virtual laboratories are either mostly pre-recorded experiments or involve controlling physical/virtual equipment through an online interface. None of these methods provide an adequate hands-on learning experience, which is essential for understanding fundamental engineering concepts. For online and distance learning programs, hands-on activities in a laboratory classroom setting are not always feasible, generating a strong push to develop low-cost, compact, and portable experimental toolboxes and kits that individual students can obtain. A group of faculty, students, and staff at the University of Indianapolis has developed an experimental toolbox that allows students to visualize engineering statics fundamentals. The experimental kit and a list of experiments complete with instructions will be made available to the students at the beginning of the course to perform the laboratory-style experiments at home. Students will be able to collect an experimental kit from campus with an appropriate deposit (each kit costs approximately $180 to $200 US). The university can also ship kits to students' addresses upon request with an additional delivery cost. Students can return the experimental kit at the end of the course and have their deposits returned. Performing laboratory style experiments at home using these kits will provide a valuable hands-on learning experience. © American Society for Engineering Education, 2021

Design and Implementation of Automatic Line Follower Robot for Assistance of COVID-19 Patients

Coronavirus disease (COVID-19) has caused unprecedented global health problems, and the disease’s spread rate is extremely high. It spreads from infected people (COVID-19 positive) to others via droplets from the mouth or nose when they cough, sneeze, speak, sing, or take deep breaths. Frontline fighters of healthcare organizations such as doctors, nurses, and other medical staff cannot have direct contact with COVID-19 patients in isolation room without personal protective equipment (PPE). Hence, hospital workers have to face different types of problems in distributing foods, medicines, and disposal of waste. An Automatic Line Follower Robot (ALFR) is designed and implemented for COVID-19 patients which is capable of serving infected patients in an isolation room. The main contribution of this paper is to serve essential medicines and foods from the hospital staff and serve it to the patients following the black line. The ALFR also proposes a system which maintains an emergency wireless communication protocol between doctors and patients. It also collects waste from a specified basket and damps it to a proper place. Finally, it can sanitize the isolated room with the help of a disinfectant machine which is assembled in ALFR. ALFR’s performance has significantly improved, and it can successfully complete all tasks. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Social Sustainability Challenges Towards Flexible Supply Chain Management: Post-COVID-19 Perspective

The COVID-19 pandemic has severely impacted the global social sustainability of the supply chains, pushing them towards a more flexible management approach. However, there is a paucity of literature that focuses on social sustainability issues for emerging economies. In the post-COVID-19 period, firms around the world will face several critical challenges to social sustainability, which will hinder achieving sustainable development goals (SDGs). Against this backdrop, this study identifies the pressing challenges to social sustainability in the post-COVID-19 context by a literature review and opinions from an expert panel, focusing on the footwear supply chain. In this paper, the best–worst method is applied to compute the criticality of social sustainability challenges towards the flexibility of the supply chains. The study findings reveal that among the nine identified critical challenges, “high level of lay off”, “health protocol development”, “complexity in ensuring workplace safety”, “facing trouble in mental health”, and “lack of government enforcement and regulations for social issues” are reported as the top five challenges, respectively. Furthermore, this study suggests several flexible managerial guidelines, which will help practitioners and policymakers to achieve SDGs considering the COVID-19 pandemic. © 2021, Global Institute of Flexible Systems Management.

Leveraging Technology for Virtual Class and Learning during COVID-19 Pandemic

Online or virtual learning is a prominent educational method that takes place over the Internet as a form of distance education. Distance education has become substantially popular as a result of the COVID-19 pandemic in 2020. Virtual learning can play a key role in an emergency period like the COVID-19 pandemic because most of the learners have access to information and communication technologies (ICT). So, leveraging technology in education can be a potential solution in learning. This study intends to examine how digital technology can be integrated effectively for better learning and education during the COVID-19 pandemic. A systematic literature review was performed using the Scopus database from 2001 to 2020. According to inclusion criteria, 26 studies were selected for qualitative analysis. In particular, four forms of technology-oriented learning systems have been revealed: electronic (e-learning), mobile (m-learning), interactive (i-learning), and ubiquitous learning (u-learning). The introduction of technology into the teaching-learning process can be an important way of developing improved learning and educational outcomes for learners and educators. In this paper, the learning models provided have the ability to exploit the associated technologies to ensure the feedback and delivery of the learning approach. The research will provide educators, teachers, policymakers, and curriculum creators with a new lens to design a better learning strategy for the learner. © 2021 IEEE.

Mobile banking during COVID-19 pandemic in Bangladesh: A novel mechanism to change and accelerate people's financial access

Limited access to financial services is considered as a vital bottleneck for curbing poverty in Bangladesh. Digital technology such as mobile banking can contribute to accelerate people's access to finance but did not receive proper attention before COVID-19. This study intends to explore the use of mobile banking services to accelerate people's financial access in Bangladesh due to the emergence of the COVID-19 pandemic by using secondary data. Mainly documentation techniques and descriptive statistical methods are used to collect and analyze the data. The study reveals that the number of registered mobile banking customers has escalated during the COVID-19 era. Mainly government policies regarding different mobile banking transactions such as cash in, cash out, person to person (P2P) transaction, salary and utility bill payments etc., have significantly contributed to rise the people's digital financial access during this pandemic. People's changing habit towards digital transactions has also contributed to increasing their financial access. The government should provide a convenient financial access platform to create a cashless society in the country.

State of the art of urban smart vertical farming automation system: Advanced topologies, issues and recommendations

The global economy is now under threat due to the ongoing domestic and international lockdown for COVID-19. Many have already lost their jobs, and businesses have been unstable in the Corona era. Apart from educational institutions, banks, privately owned institutions, and agriculture, there are signs of economic recession in almost all sectors. The roles of modern technology, the Internet of things, and artificial intelligence are undeniable in helping the world achieve economic prosperity in the post-COVID-19 economic downturn. Food production must increase by 60% by 2050 to meet global food security demands in the face of uncertainty such as the COVID-19 pandemic and a growing population. Given COVID 19’s intensity and isolation, improving food production and distribution systems is critical to combating hunger and addressing the double burden of malnutrition. As the world’s population is growing day by day, according to an estimation world’s population reaches 9.6 billion by 2050, so there is a growing need to modify the agriculture methods, technologies so that maximum crops can be attained and human effort can be reduced. The urban smart vertical farming (USVF) is a solution to secure food production, which can be introduced at any adaptive reuse, retrofit, or new buildings in vertical manners. This paper aims to provide a comprehensive review of the concept of USVF using various techniques to enhance productivity as well as its types, topologies, technologies, control systems, social acceptance, and benefits. This review has focused on numerous issues, challenges, and recommendations in the development of the system, vertical farming management, and modern technologies approach. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

IoT Based Low-Cost Robotic Agent Design for Disabled and Covid-19 Virus Affected People

Disabled people and Virus affected patients can be helped through Internet of Things and Robotic systems in this modern era. Recently the whole world is suffering from the Covid-19 pandemic. The virus affected and disabled people are helpless because caregivers, doctors and other people are afraid of the contagious virus. This work will result in an MT based Robotic agent which will be able to help disabled and virus affected people with low cost systems. The robotic agent will he able to recognize the patient's Gesture and follow instructions through it with 360-degree movement. Without image processing the system is made with MPU 6050 Accelerometer Gyroscope sensor for Gesture Recognition. Radio Frequency communication was used to make the system wireless.

Healthcare worker attendance during the early stages of the COVID-19 pandemic: A longitudinal analysis of fingerprint-verified data from all public-sector secondary and tertiary care facilities in Bangladesh

Background The COVID-19 pandemic has overwhelmed hospitals in several areas in high-income countries. An effective response to this pandemic requires health care workers (HCWs) to be present at work, particularly in low- and middle-income countries (LMICs) where they are already in critically low supply. To inform whether and to what degree policymakers in Bangladesh, and LMICs more broadly, should expect a drop in HCW attendance as COVID-19 continues to spread, this study aims to determine how HCW attendance has changed during the early stages of the COVID-19 pandemic in Bangladesh. Methods This study analyzed daily fingerprint-verified attendance data from all 527 public-sector secondary and tertiary care facilities in Bangladesh to describe HCW attendance from January 26, 2019 to March 22, 2020, by cadre, hospital type, and geographic division. We then regressed HCW attendance onto fixed effects for day-of-week, month, and hospital, as well as indicators for each of three pandemic periods: a China-focused period (January 11, 2020 (first confirmed COVID-19 death in China) until January 29, 2020), international-spread period (January 30, 2020 (World Health Organization's declaration of a global emergency) until March 6, 2020), and local-spread period (March 7, 2020 (first confirmed COVID-19 case in Bangladesh) until the end of the study period). Findings On average between January 26, 2019 and March 22, 2020, 34.1% of doctors, 64.6% of nurses, and 70.6% of other health care staff were present for their scheduled shift. HCWs' attendance rate increased with time in 2019 among all cadres. Nurses' attendance level dropped by 2.5% points (95% confidence interval (CI) =-3.2% to -1.8%) and 3.5% points (95% CI = -4.5% to -2.5%) during the international-spread and the local-spread periods of the COVID-19 pandemic, relative to the China-focused period. Similarly, the attendance level of other health care staff declined by 0.3% points (95% CI=-0.8% to 0.2%) and 2.3% points (95% CI = -3.0% to -1.6%) during the international-spread and local-spread periods, respectively. Among doctors, however, the international-spread and local-spread periods were associated with a statistically significant increase in attendance by 3.7% points (95% CI =2.5% to 4.8%) and 4.9% points (95% CI=3.5% to 6.4%), respectively. The reduction in attendance levels across all HCWs during the local-spread period was much greater at large hospitals, where the majority of COVID-19 testing and treatment took place, than that at small hospitals. Conclusions After a year of significant improvements, HCWs' attendance levels among nurses and other health care staff (who form the majority of Bangladesh's health care workforce) have declined during the early stages of the COVID-19 pandemic. This finding may portend an even greater decrease in attendance if COVID-19 continues to spread in Bangladesh. Policymakers in Bangladesh and similar LMICs should undertake major efforts to achieve high attendance levels among HCWs, particularly nurses, such as by providing sufficient personal protective equipment as well as monetary and non-monetary incentives.

Coding-Complete Genome Sequences of Three SARS-CoV-2 Strains from Bangladesh.

We report the sequencing of three severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from Bangladesh. We have identified a unique mutation (NSP2_V480I) in one of the sequenced genomes (isolate hCoV-19/Bangladesh/BCSIR-NILMRC-006/2020) compared to the sequences available in the Global Initiative on Sharing All Influenza Data (GISAID) database. The data from this analysis will contribute to advancing our understanding of the epidemiology of SARS-CoV-2 in Bangladesh as well as worldwide at the molecular level and will identify potential new targets for interventions.