Challenges in the construction of a tunnel under crossing a channel in Singapore

To increase the conveyance capacity to Western Singapore and to meet long-term water needs in a more cost-effective manner, four new transmission pipelines consisting of 2 numbers of 2200 mm diameter and 2 numbers of 1200mm diameter water pipes will be needed by 2024 to convey water from a Water Reclamation Plant to existing networks in the western region of Singapore. Out of the several possible routes studied, the most cost-effective and technically feasible route was selected by laying the proposed 1.6km-long pipelines that under crosses a channel via a 6m diameter subsea tunnel. This paper outlines the challenges the team faced throughout the project thus far. It also examines the difficulties such as the construction of a 56m-deep launching shaft near a highly sensitive 700mm diameter Gas Transmission Pipeline (GTP) and at a location with high groundwater;and manpower and supply disruptions caused by the COVID-19 pandemic situation. © 2023 The Author(s).

The Drug Repurposing Strategy in the Exscalate4CoV Project: Raloxifene Clinical Trials

Drug repurposing is a cost-effective process to identify therapeutic candidates during a medical crisis or pandemic. The supercomputing platform, EXaSCale smArt pLatform Against paThogEns for CoronaVirus (EXSCALATE4CoV;E4C), was used to identify drug candidates for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. E4C identified raloxifene as having great therapeutic potential, confirmed by in vitro data, which led to the progression of clinical trials to assess its efficacy. Raloxifene met the primary virologic endpoint in the treatment of early mild coronavirus disease 2019 (COVID-19), and although additional clinical trials are needed to confirm these results, there is evidence in support of in silico drug repurposing to provide cost-effective and rapid drug screening to identify treatment options for the pandemic and future pandemics. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Safety and efficacy of video DLT (VDLT) for lung isolation during the COVID-19 pandemic.

One lung ventilation (OLV) with collapse of the ipsilateral lung is a prerequisite for most thoracic surgical procedures. Double-lumen tube (DLT) is still the preferred method to isolate the lungs and fiberoptic bronchoscopy (FOB) is the gold standard for the confirmation of correct placement of the DLT. However, both these procedures are considered as a high-aerosol-generating procedures and are hazardous to the health workers, particularly at this time of the COVID-19 pandemic. We did nine thoracic surgery cases categorized as essential, requiring OLV during the ongoing period of the COVID-19 between April 2020 and May 2020 where we used Full view DLT for lung isolation. We present our case series which shows that the Full view VDLT can minimize or circumvent the use of FOB during OLV, and reduce the time taken to isolate the lungs thus reducing aerosol in the theater. None of the nine patients required FOB for confirmation of initial positioning nor for diagnosis of intraoperative malposition. The time taken to isolate the lungs was significantly less and the surgical positioning was done under real-time monitoring by visualizing the blue cuff distal to carina at all times. The real-time monitoring by the Full view VDLT offers the additional advantage of detecting any malposition even before it results in loss of isolation or desaturation. We conclude that the Full view VDLT is an efficient and safe alternative for lung isolation at this time of the COVID-19 pandemic.

Eco-Environment friendly cost-effective synthesis for sustainable human development in context of globalization

Nanotechnology is nowadays very much successful in producing specifically functionalized nano-sized particles. In this work, copper nanoparticles were prepared by reduction method which is greener and environmentally suitable, cheap and best as compared to other conventional methods, particularly in the context of COVID in globalized world. The formation and size of copper nanoparticles was evidenced by the X-ray diffraction and transmission electron microscopy. The very high surface area of 35-50 m2/gm and very small crystallite sizes of 5-15 nm of these metal nanoparticles is mainly responsible for their effective involvement in removal of carbon dioxide gas as one of major hazardous pollutants from the environment. This chapter, as its main objective, mainly focuses on utility of nano technology and its beneficiary in creating a sustainable environment in economic world. Apart from laboratory experimental procedure and characterizations for preparation of copper nanoparticles, appropriate research methods such as simple statistical, econometric tools and mathematical tools have been used for economic analysis. However, as major findings of the results, developed countries have been successful in maintaining a sustainable human development, in spite of having higher per capita income (PCI) growth as compared to the role of developing countries with lower PCI in this global world. © 2022 by Emerald Publishing Limited.

How to Achieve an Easier, Cost-Effective Hybrid Event Environment: Actual Equipment Cases and its Way to the Future

With the outbreak of COVID-19, the lecture environment at universities has increasingly turned into online environments. In addition to those delivered entirely by online tools, there are hybrid, online and in-person, lecture environments. Hybrid casting environments are growing not only in the classroom, but also in various conferences. In an online-only meeting environment, web conferencing tools such as Zoom and Webex can be used to approximately achieve the objective. In a hybrid environment, however, a face-to-face environment is also necessary, and it is essential to build an environment that is aware of both online and face-to-face interaction. It would be fine if the venue already has the equipment to serve the purpose, but in some cases, there are no facilities and the equipment must be carried in and arranged. At this point, the most difficult point is in the audio system configuration. This requires a certain level of technical knowledge and monetary costs. For a reasonable price, it is possible to outsource to a specialized service provider to create a perfect casting environment. However, in many situations, it is difficult to take significant costs and many people are trying to manage the situations by trial and error. We have experienced various hybrid casting situations. Recently, we try to consider how to reduce costs from various aspects, such as "avoiding high costs in terms of manpower, equipment, and expenses,""not requiring operators to have lots of knowledge,"and "minimizing the amount of equipment to be carried in, as it is integrated with the existing equipment at the venue. In this presentation, we provide actual examples of hybrid casting environments in which the author experienced, mainly by bringing in, setting up, and operating equipment by one person, and outlines the key points of these operations, as well as considering what kind of casting environment can reduce various costs and achieve hybrid casting more easily. We would like to share with the SIGUCCS community what kind of total peripheral environment is needed to make hybrid delivery more familiar, not just the delivery technology itself, such as Zoom or Webex, and to think together about how it should be. © 2023 Owner/Author.

mRNA-based COVID-19 booster vaccination is highly effective and cost-effective in Australia.

BACKGROUND: Australia implemented an mRNA-based booster vaccination strategy against the COVID-19 Omicron variant in November 2021. We aimed to evaluate the effectiveness and cost-effectiveness of the booster strategy over 180 days. METHODS: We developed a decision-analytic Markov model of COVID-19 to evaluate the cost-effectiveness of a booster strategy (administered 3 months after 2nd dose) in those aged ≥ 16 years, from a healthcare system perspective. The willingness-to-pay threshold was chosen as A$ 50,000. RESULTS: Compared with 2-doses of COVID-19 vaccines without a booster, Australia's booster strategy would incur an additional cost of A$0.88 billion but save A$1.28 billion in direct medical cost and gain 670 quality-adjusted life years (QALYs) in 180 days of its implementation. This suggested the booster strategy is cost-saving, corresponding to a benefit-cost ratio of 1.45 and a net monetary benefit of A$0.43 billion. The strategy would prevent 1.32 million new infections, 65,170 hospitalisations, 6,927 ICU admissions and 1,348 deaths from COVID-19 in 180 days. Further, a universal booster strategy of having all individuals vaccinated with the booster shot immediately once their eligibility is met would have resulted in a gain of 1,599 QALYs, a net monetary benefit of A$1.46 billion and a benefit-cost ratio of 1.95 in 180 days. CONCLUSION: The COVID-19 booster strategy implemented in Australia is likely to be effective and cost-effective for the Omicron epidemic. Universal booster vaccination would have further improved its effectiveness and cost-effectiveness.

Automation of COVID-19 Disease Diagnosis from Radiograph

The coronavirus disease (COVID-19) makes humans suffer from mild to moderate respiratory problems, with severe cases requiring special treatment. In many severe cases, elderly individuals and people with pre-existing medical issues like lung-related disease, insulin-dependent disease, and carcinoma, are more prone to difficulty breathing and developing a severe illness. To detect the coronavirus here, X-ray radiograph images are considered. The main motive for using X-ray radiograph images is their being cost-effective and being able to give considerable accuracy compared to its counterpart, computed tomography (CT) scans. In this study, the deep learning model Visual Geometry Group (VGG)16 using the transfer learning method and image augmentation techniques was employed for automatic COVID-19 diagnosis. These two techniques will assist the deep learning model to learn the target task by improving the baseline performance by using fewer X-ray radiograph images in the training phase and showing improvements in the model development time by utilising knowledge gained from a source model. Many deep learning methods have been published in the literature to solve the same cases, but the proposed method uses a simple VGG16 model with transfer learning, which takes less processing time and gives satisfactory results even by using fewer training samples. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

Various Tracking and Health Monitoring System in COVID-19 Based on IoT

The IoT (Internet of Things), a network of interconnected systems and data analytics, which can provides information about the spread of diseases/Virus globally. Typically, IoT is a bridge between machine learning philosophy, real time application such as security system, smart lights, smart speakers and many more. [1.2]. In current situation (pandemic), all over the world, is facing the problem where all are sucked down and looking for solution which can resolve the problem with cost -effective solution that has risen. Researchers are looking forward for the challenges and describing the studies which can overcome with the by IoT. The brief review aimed to significant applications over the COVID-19. © 2022 IEEE.

Simulating Counterfeit Personal Protective Equipment (PPE) Supply Chains During Covid-19

Increased demand for medical supplies, and specifically respirators and face masks, during the Covid-19 pandemic along with the inability of legitimate suppliers to meet these needs created a window of opportunity for counterfeiters to capitalize on the supply chain disruptions caused by a global health crisis. Both legitimate and illicit businesses began shifting their scope from sectors such as textiles to producing and distributing personal protective equipment (PPE), many of which were counterfeit or unauthentic products and thus unable to properly protect users. To study cost-effective disruption strategies, this study proposes a simulation-optimization framework. The framework is used to model counterfeiters' behavior and analyze the effectiveness of different disruption strategies for counterfeit PPE supply chains during the Covid-19 pandemic. © 2022 IEEE.

Lightweight Cost Effective Deep Learning Model for COVID-19 Detection using CXR Images

In the field of medical imaging, deep learning techniques have already proven to be quite a success.The global population's health and well being continue to be severely impacted by the Coronavirus Disease 2019 (COVID-19) pandemic, healthcare systems are unable to examine and diagnose patients as soon as they ought to. The various post COVID complications which may have been dealt in a better way if the virus was detected at an earlier stage and given appropriate clinical support. Chest radiography imaging is essential for detecting and tracking COVID-19 because of its effects on pulmonary tissues. Chest X-Ray(CXR) imaging is even more readily available than chest computed tomography(CT) imaging, especially in developing countries where CT scanners are too costly due to high equipment and maintenance costs. In this work we propose a very lightweight convolutional neural network (CNN), in which the chest X-Ray samples comprising of COVID-19, Non-COVID and Normal cases are analyzed without any human intervention. Our model gives comparable accuracy to other COVID-19 detection models proposed earlier while having significantly fewer parameters than them, which makes our model optimal for deployment on machines with low computing power. © 2022 IEEE.

Evaluating the Covid-19 Screening Regime for Cross-Border Workers

Global travel and trade have been hit hard by the COVID-19 pandemic. Border closures have impacted both leisure and business travel. The socioeconomic costs of border closure are particularly severe for individuals living and working across state lines, for which previously unhindered passage has been curtailed, and daily commute across borders is now virtually impossible. Here, we examine how the periodic screening of daily cross-border commuters across territories with relatively low COVID-19 incidence will impact the transmission of SARS-CoV-2 across borders using agent-based simulation. We find that periodic testing at practical frequencies of once every 7, 14 or 21 days would reduce the number of infected individuals crossing the border. The unique transmission characteristics of SARS-CoV-2 suggest that periodic testing of populations with low incidence is of limited use in reducing cross-border transmission and is not as cost-effective as other mitigation measures for preventing transmission. © 2022 IEEE.

Hospital at home: emergence of a high-value model of care delivery.

Background: With increasing healthcare demands for acute illness in patients especially in the times of pandemic, healthcare organizations require modern solutions. Hospital at home (HaH) is one such tool that has the potential to solve these problems without compromising the care of the patients. Main body: Hospitals have been the conventional setting for managing acute sickness patients; however, it could be a very challenging environment for a few patients, especially for the older population who are highly susceptible to hospital-acquired infections. Health care in a hospital setting can also be very expensive, as it often involves a lot of healthcare professionals providing care. HaH service can provide the same quality of care expected in traditional settings. Conclusions: The median length of stay and the rate of readmissions were lower in people under HaH care. Compared with patients in a hospital setting, patients in HaH had better clinical outcomes. HaH unit provides an integrated, flexible, easy-to-scale platform that can be cost-effectively adapted to high-demand situations.

Nickel-Ion Activating Discarded COVID-19 Medical Surgical Masks for Forming Carbon-Nickel Composite Nanowires and Using as a High-Performance Lithium Battery Anode

With the prevalence of COVID-19, wearing medical surgical masks has become a requisite measure to protect against the invasion of the virus. Therefore, a huge amount of discarded medical surgical masks will be produced, which will become a potential hazard to pollute the environment and endanger the health of organisms without our awareness. Herein, a green and cost-effective way for the reasonable disposal of waste masks becomes necessary. In this work, we realized the transformation from waste medical surgical masks into high-quality carbon-nickel composite nanowires, which not only benefit the protection of the environment and ecosystem but also contribute to the realization of economic value. The obtained composite carbon-based materials demonstrate 70 S m-1conductivity, 5.2 nm average pore diameters, 234 m2g-1surface areas, and proper graphitization degree. As an anode material for lithium-ion batteries, the prepared carbon composite materials demonstrate a specific capacity of 420 mA h g-1after 800 cycles at a current density of 0.2 A g-1. It also displays good rate performance and decent cycling stability. Therefore, this study provides an approach to converting the discarded medical surgical masks into high-quality carbon nanowire anode materials to turn waste into treasure. © 2023 American Chemical Society. All rights reserved.

Cost-effective Vaccine Provisioning using Coalitional Game Theory

Rapid development and distribution of vaccines have been a hallmark of the battle against COVID-19. While the efficacy, clinical trials, adverse health effects, and sociodemographic and clinical factors determining the distribution of vaccines have been studied extensively, there has been little effort to design cost-effective vaccine provisioning schemes. We introduce a vaccine provisioning scheme that leverages coalitional game theory to improve the cost of vaccines while meeting the epidemiological demand of neighboring zones. The proposed approach incentivizes bulk purchases by groups (or coalitions) of zones at lower prices while penalizing large coalitions to avoid logistical challenges. Moreover, it enables the policymaker to model the vaccine demand of zones based on their epidemiological profiles, such as susceptible, infected numbers or population density, or a combination thereof. We carry out experiments using the SEIRD (susceptible, exposed, infected, recovered, death) epidemic model as well as the daily confirmed cases in the five boroughs of New York City to show the efficacy of the approach. © 2022 IEEE.

Cost-effective automated multipurpose delivery system software for hospitals

Covid-19 pandemic has impacted every aspect of our society. One of the worst affected parts is the countries' health systems. Our goal is to provide a proof of concept for cost effective automated delivery system which can be used by hospitals for distributing medicine and food to patients in non-intensive wards, so medical personnel exposure to the virus can be minimized. Only free and open source software tools are used. Working proof of concept of the system is created consisted of: robot platform running ROS, SQL Server relational database, Web App. Limitations are identified. Testing is successful. We have showed that using free and open-source software and tools, it is possible to achieve the goal of creating the system. Copyright © 2022 The Authors.

Cost-Effectiveness Analysis of COVID-19 Vaccination in Low- and Middle-Income Countries.

Background: WHO reported that 5.5 million people died in the world because of COVID-19. One of the efforts to mitigate the pandemic is administrating the vaccines globally. Objective: The objective of this study was to review cost-effectiveness analysis of COVID-19 vaccination in low- and middle-income countries (LMICs). Methods: We searched PubMed and EBSCO for the eligible studies with inclusion criteria using cost-effectiveness analysis, free full text, low-middle-income countries, and the publication date since the last year. Four reviewers conducted the review independently. Results: The review identified four articles meeting the eligibility criteria. The settings were LMICs. Different perspectives and economic modelling used by the countries confirmed a similar result. They all explained that vaccination could prevent the infection spread and mortality caused by COVID-19 and showed high cost-effectiveness values. Conclusion: Administering COVID-19 vaccines was cost-effective and even cost-saving. The studies found that vaccination was more cost-effective in reducing the spread of the COVID-19 virus and the mortality it caused than no vaccination.

Cost-effective Vaccine Provisioning using Coalitional Game Theory

Rapid development and distribution of vaccines have been a hallmark of the battle against COVID-19. While the efficacy, clinical trials, adverse health effects, and sociodemographic and clinical factors determining the distribution of vaccines have been studied extensively, there has been little effort to design cost-effective vaccine provisioning schemes. We introduce a vaccine provisioning scheme that leverages coalitional game theory to improve the cost of vaccines while meeting the epidemiological demand of neighboring zones. The proposed approach incentivizes bulk purchases by groups (or coalitions) of zones at lower prices while penalizing large coalitions to avoid logistical challenges. Moreover, it enables the policymaker to model the vaccine demand of zones based on their epidemiological profiles, such as susceptible, infected numbers or population density, or a combination thereof. We carry out experiments using the SEIRD (susceptible, exposed, infected, recovered, death) epidemic model as well as the daily confirmed cases in the five boroughs of New York City to show the efficacy of the approach. © 2022 IEEE.

Optimization of the Illumina COVIDSeq™ protocol for decentralized, cost-effective genomic surveillance.

A decentralized surveillance system to identify local outbreaks and monitor SARS-CoV-2 Variants of Concern is one of the primary strategies for the pandemic's containment. Although next-generation sequencing (NGS) is a gold standard for genomic surveillance and variant discovery, the technology is still cost-prohibitive for decentralized sequencing, particularly in small independent labs with limited resources. We have optimized the Illumina COVIDSeq™ protocol for the Illumina MiniSeq instrument to reduce cost without compromising accuracy. We slashed the library preparation cost by half by using 50% of recommended reagents at each step and normalizing the libraries before pooling to achieve uniform coverage. Reagent-only cost (∼$43.27/sample) for SARS-CoV-2 variant analysis with this normalized input protocol on MiniSeq instruments is comparable to what is achieved on high throughput instruments such as NextSeq and NovaSeq. Using this modified protocol, we tested 153 clinical samples, and 90% of genomic coverage was achieved for 142/153 samples analyzed in this study. The lineage was correctly assigned to all samples (152/153) except for one. This modified protocol can help laboratories with constrained resources to contribute in decentralized COVID-19 surveillance in the post-vaccination era.

Let Every Voice Be Heard: Developing a Cost-Effective Community Sampling Frame in Rural Alabama to Combat COVID-19 (poster)

The lack of accurate data on the rural communities' perspectives of the COVID-19 vaccine impairs the planning, monitoring, and evaluation of vaccine programs. Notably, we do not have adequate data to understand why, although COVID-19 has disproportionately impacted minority populations in these communities, they are reported to be the least likely to be vaccinated. This paper develops a cost-effective community sampling frame based on satellite imagery and machine learning to improve the diversity of data and study the association between household-level visual information and COVID-19 vaccination rates in the Alabama Black Belt. The results provided solid evidence for the hypothesis that high-resolution satellite imagery contains valuable information to understand communities' perspectives on the COVID-19 vaccine. It also generated extra knowledge and implications for community health to help social workers to develop future vaccine promotion strategies in rural America. © 2022 ACM.

An efficient and cost-effective method for directed mutagenesis at multiple dispersed sites-a case study with Omicron Spike DNA.

Site-directed mutagenesis is an invaluable technique that enables the elucidation of the contribution of specific residues to protein structure and function. The simultaneous introduction of mutations at a large number of sites (>10), singly and in multiple combinations, is often necessary to fully understand the functional contributions. We report a simple, efficient, time and cost-effective method to achieve this using commonly available molecular biology reagents and protocols, as an alternative to gene synthesis. We demonstrate this method using the Omicron Spike DNA construct as an example, and create a construct bearing 37 mutations (as compared to wild-type Spike DNA), as well as 4 other constructs bearing subsets of the full spectrum of mutations. We believe that this method can be an excellent alternative to gene synthesis, especially when three or more variants are required.