Intelligent Telework Internet Cost Requirement Modeling Using Optimizable Machine Learning Algorithms

The COVID-19 pandemic has caused disruption to the economy due to the increasing infection that affects the workforce in different sectors. The Philippine government has imposed lockdowns to control the spread of infection. This urged the different sectors to implement flexible work schedules or work from home setup. A work-from-home (WFH) setup burdens both the employee and employer by installing different equipment set-ups such as WiFi-equipped laptops, computers, tablets, or smartphones. However, the internet stability in some of the areas in the Philippines is not yet reliable. In this study, an application is used collect survey information and provide an estimate of the telework internet cost requirement of a given government employee or a given government employee implementing a work-from-home set up in their respective household. This involves survey results from different respondents who are currently on a work-from-home setup and significant factors from the survey have been analyzed using machine learning (ML) algorithms. Among the machine learning algorithms used, the ensemble bagged trees model outperformed the other ML models. This work can be extended by incorporating a wider scope of datasets from different industry doing work from home set-up. In addition, in terms of education, it is also recommended to determine the WFH set up not just with the government employee and employer but to also extend this into the education side. © 2022 IEEE.

Rapid and Low-Cost Detection of Human Corona Virus Using MEMS ATR-FTIR Spectroscopy

The conventional methods used for the diagnostics of viral infection are either expensive and time-consuming or not accurate enough and dependent on consumable reagents. In the presence of pandemics, a fast and reagent-free solution is needed for mass screening. Recently, the diagnosis of viral infections using infrared spectroscopy has been reported as a fast and low-cost method. In this work a fast and low-cost solution for corona viral detection using infrared spectroscopy based on a compact micro-electro-mechanical systems (MEMS) device and artificial intelligence (AI) suitable for mass deployment is presented. Among the different variants of the corona virus that can infect people, 229E is used in this study due to its low pathogeny. The MEMS ATR-FTIR device employs a 6 reflections ZnSe crystal interface working in the spectral range of 2200-7000 cm-1. The virus was propagated and maintained in a medium for long enough time then cell supernatant was collected and centrifuged. The supernatant was then transferred and titrated using plaque titration assay. Positive virus samples were prepared with a concentration of 105 PFU/mL. Positive and negative control samples were applied on the crystal surface, dried using a heating lamp and the spectrum was captured. Principal component analysis and logistic regression were used as simple AI techniques. A sensitivity of about 90 % and a specificity of about 80 % were obtained demonstrating the potential detection of the virus based on the MEMS FTIR device. © 2023 SPIE.

Health Economic Evaluation of COVID-19 Vaccines: A Systematic Literature Review

Objectives: The COVID19 pandemic caused over six million deaths worldwide as of 2022 and made necessary the rapid development of vaccines. The objective of this Systematic Literature Review is to summarise the main evidence from economic evaluations of vaccines against COVID19. Method(s): Searches were conducted on PubMed on July 13th 2022. The selected papers considered COVID19 vaccination scenarios without population limits. The types of study design examined were cost-benefit and cost-effectiveness analyses. Result(s): Overall, 16 articles from an initial list of 1842 were included in this review. Out of the 16 models, there were five Markov cohort models (three of them were combined with a decision tree model), four dynamic transmission models, three microsimulation models, three epidemiological models (without further information on the model structure) and one decision tree model. Model characteristics were considerably consistent between high-, middle- or low-income countries. Five studies considered both the healthcare and societal perspective, while seven studies reported only the former, and one only the latter. Two studied did not specify the study perspective. Ten of the studies did not consider any level of herd immunity, and no study considered cross-protection. Although eight studies used "naive" comparisons between vaccines, none of the studies conducted thorough indirect treatment comparison. All the models suggest that vaccines are cost-effective as they prevent death and transmission, and reduce the severity of cases. Although the sources of effectiveness estimates were always stated, the details of those studies were rarely reported. Nevertheless, the outcome measures and the key parameters used in the models were generally clearly stated and justified. Conclusion(s): This SLR highlights several challenges for conducting Health Economic evaluations of COVID19 vaccines. The quality of the models and their estimates suffered from the very fast pace of COVID19 research. Therefore, economic evidence on vaccination programs requires additional rigorous research.Copyright © 2023

Consortium biofertilizers to economise nutrient use and sustain productivity in cassava (Manihot esculenta Crantz)

Climate change events and the COVID-19 pandemic have brought to focus the significance of cassava as a supplementary food crop worldwide. However, the high yield potential of the crop necessitates timely and adequate enrichment of the soil with nutrient inputs. Consortium biofertilizers offer a viable option for reducing intensive fertilizer use to sustain soil health and productivity in cassava. The efficacy of a liquid consortium biofertilizer, specifically a plant growth-promoting rhizobacteria (PGPR) Mix - I, in economizing nutrient use in cassava was evaluated in a 4 x 3 factorial randomized block design, replicated thrice. The treatments consisted of combinations of four levels of biofertilizers and three levels of nutrients. Biometric and yield observations were recorded, and soil properties were analyzed before and after the harvest of the crop. The results showed that the liquid biofertilizer consortium at a concentration of 5% + 75% of the recommended dose, with 37.5:37.5:75 kg NPK/ha as chemical fertilizers, recorded significantly superior tuber yield in cassava. Considering the economics, the application of the PGPR liquid formulation (5%) thrice (basal, 2 and 4 MAP) along with 37.5:37.5:75 kg NPK/ha, or at a concentration of 2% with 50:50:100 kg NPK/ha, realized higher benefit-cost ratios and can be recommended for use in cassava.

The economics of the COVID-19 pandemic: economic evaluation of government mitigation and suppression policies, health system innovations, and models of care.

Background: The COVID-19 pandemic has impacted the scope of health economics literature, which will increasingly examine value beyond health care interventions such as government policy and broad health system innovations. Aim: The study analyzes economic evaluations and methodologies evaluating government policies suppressing or mitigating transmission and reducing COVID-19, broad health system innovations, and models of care. This can facilitate future economic evaluations and assist government and public health policy decisions during pandemics. Methods: The Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) was used. Methodological quality was quantified using the scoring criteria in European Journal of Health Economics, Consolidated Health Economic Evaluation Reporting Standards (CHEERS) 2022 Checklist and the National Institute for Health and Care Excellence's (NICE) Cost Benefit Analysis Checklist. PUBMED, Medline, and Google Scholar were searched from 2020-2021. Results: Cost utility analysis (CUA) and cost benefit analysis (CBA) analyzing mortality, morbidity, quality adjusted life year (QALY) gained, national income loss, and value of production effectively evaluate government policies suppressing or mitigating COVID-19 transmission, disease, and impacting national income loss. The WHO's pandemic economic framework facilitates economic evaluations of social and movement restrictions. Social return on investment (SROI) links benefits to health and broader social improvements. Multi-criteria decision analysis (MCDA) can facilitate vaccine prioritization, equitable health access, and technology evaluation. Social welfare function (SWF) can account for social inequalities and population-wide policy impact. It is a generalization of CBA, and operationally, it is equal to an equity-weighted CBA. It can provide governments with a guideline for achieving the optimal distribution of income, which is vital during pandemics. Economic evaluations of broad health system innovations and care models addressing COVID-19 effectively use cost effectiveness analysis (CEA) that utilize decision trees and Monte Carlo models, and CUAs that effectively utilize decision trees and Markov models, respectively. Conclusion: These methodologies are very instructive for governments, in addition to their current use of CBA and the value of a statistical life analytical tool. CUA and CBA effectively evaluate government policies suppressing or mitigating COVID-19 transmission, disease, and impacts on national income loss. CEA and CUA effectively evaluate broad health system innovations and care models addressing COVID-19. The WHO's framework, SROI, MCDA, and SWF can also facilitate government decision-making during pandemics. Supplementary Information: The online version contains supplementary material available at 10.1007/s10389-023-01919-z.

American College of Nuclear Medicine (ACNM) 2022 ACNM Annual Meeting Abstracts

The proceedings contain 91 papers. The topics discussed include: the new approach of COVID-19 patients with deteriorating respiratory functions using perfusion SPECT/CT imaging;increasing interest in nuclear medicine: evaluation of an educational workshop;cost-benefit analysis recommends further utilization of cardiac PET/MR for sarcoidosis evaluation;development of a nomogram model for predicting the recurrence of differentiated thyroid carcinoma patients based on a thyroid cancer database from a tertiary hospital in China;multi-center validation of radiomic models in new data using ComBat-based harmonization of features;bone scan with Tc99m-MDP, the missing link in the initial staging of muscle-invasive bladder carcinoma;and comparison of absorbed doses to kidneys calculated employing three time points and employing two time points in neuroendocrine patients undergoing Lu-177 DOTATATE therapy using planar images.

Application of Cloud Computing in an Education Sector through Education and Learning as a Service and its Cost Benefit Analysis

An education sector across the globe is facing numerous challenges. It is being one of the most badly affected sectors due to Covid-19. This paper presents a perspective on applying Cloud Computing technologies in the field of education at several ion levels. In addition, it proposes Education and Learning as a Service model and Decision-Making Matrix for an Organization. © 2023 IEEE.

The Benefits and Costs of Using Social Distancing to Flatten the Curve for COVID-19

We examine the net benefits of social distancing to slow the spread of COVID-19 in USA. Social distancing saves lives but imposes large costs on society due to reduced economic activity. We use epidemiological and economic forecasting to perform a rapid benefit–cost analysis of controlling the COVID-19 outbreak. Assuming that social distancing measures can substantially reduce contacts among individuals, we find net benefits of about $5.2 trillion in our benchmark case. We examine the magnitude of the critical parameters that might imply negative net benefits, including the value of statistical life and the discount rate. A key unknown factor is the speed of economic recovery with and without social distancing measures in place. A series of robustness checks also highlight the key role of the value of mortality risk reductions and discounting in the analysis and point to a need for effective economic stimulus when the outbreak has passed.

A COST ANALYSIS of TELEHEALTH-INTEGRATED ANTENATAL CARE

Background: Monash Health implemented a new telehealth-integrated antenatal care schedule in March 2020, in response to the COVID-19 pandemic. Given ever-increasing healthcare costs, new interventions must be evaluated to ensure value for money. Method(s): We conducted a retrospective comparative cost analysis from the health service and patient perspective. Women with a singleton pregnancy who received antenatal care and gave birth at Monash Health from 1 January 2018 to 22 March 2020 (pre-telehealth) and 20 April 2020 to 31 December 2021 (post-telehealth) were included. We generated propensity score matched pre- and post-telehealth cohorts, balancing baseline characteristics and comorbidities. We assigned costs for all episodes of care at Monash Health and calculated the average cost per birth in each cohort. Travel costs were estimated using the average travel distance and time. Result(s): Matched pre- and post-telehealth cohorts (both n = 13 534) were generated from the pre-telehealth ( n = 18 628) and post-telehealth ( n = 14 137) populations. We found an AU$122 increase per birth, for a total cost of AU$12 069 per birth post-telehealth. This was mainly driven by an AU$188 per birth increase in outpatient costs, associated with an extra half an appointment per birth, but offset by an AU$99 per birth decrease in patient travel costs. Differences in clinical outcomes are described in Table 1. Conclusion(s): Telehealth-integrated antenatal care enabled the health service to provide safe, ongoing care for more complex pregnancies during the pandemic for only a minimal cost increase. The results highlight the need for more research into obstetric telehealth, including more comprehensive valuations of benefits and costs to all stakeholders.

Cost analysis of launching telemedicine services by Peking union Medicalcollege hospital during the pandemic of Coronavirus disease 2019.

Objective To assess the cost of launching telemedicine services by Peking Union Medical College Hospital (PUMCH) during coronavirus disease 2019 pandemic. Methods The patients using telemedicine services were enrolled during the period of pilot run from February 10th to April 15th, 2020. The study was done from the social perspective. A decision-tree model was constructed to compare the costs between telemedicine services and conventional clinical services for outpatients. The main outcome was measured as incre- mental cost-effective ness ratios (ICER). Sensitivity analysis was conducted by using one-way sensitivity analysis. Results During a period of forty-seven days, the online fever clinic was applied 3055 person-times(2070 patients) and the online outpatient clinic were applied 36 549 person-times(20 467 patients). On average, 44 febrile cases/d and 435 nonfebrile cases/d were reduced in the outpatient clinic. It helped to reduce roughly 1/4 (febrile) and 1/5(nonfebrile) of total numbers of the patients in the outpatient clinic during the peak period of the epidemic. If calculated according to the actual free-of-charge condition, the ICER was -64.7 yuans/person-time. If the actual cost of each consultant of telemedicine service was estimated according to the level of outpatient-service fee, the ICER was -5.5 yuans/person-time. The results of sensitivity analysis showed that the main factors affecting the ICERs were transportation cost, lost wages, and the efficiency of telemedicine services. Conclusions Launching telemedicine services helped to relieve the pressure at the outpatient clinics, and has the potential to provide significant cost saving compared to conventional clinic services for outpatients. It is worth considering applying this practice widely in the medical and health services.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Execution of Market Basket Analysis and Recommendation Systems in Physical Retail Stores to Advance Sales Revenues

In the early months of 2020, pandemic covid-19 hit many parts of the world. Especially developing countries like India observed a negative growth rate in few quarters of last financial year. Retailing is one of the key sectors that contribute to Indian GDP with a share of nearly 10 percent. Hence there is a need for the retail sector to bounce back which is possible with the efficient use of new digital technologies. Market basket analysis is used here to extract the association rules which can be directly used for formulating discount and combo offers. Along with that, these rules can be used to decide the product positioning in the retail store. Items which are bought together can be placed next to each other to increase sales. Recommendation systems are most commonly used in ecommerce websites like Amazon, Flipkart, etc, and streaming platforms like Netflix to recommend the items that are to be purchased by users. Although recommendation engines are implemented in multiple web and mobile applications, these are not in the implementation stage in offline retail stores due to many implications associated with them like infrastructure, cost, etc. In this project, we have used market basket analysis and recommendation systems to propose a model to implement in retail stores to increase sales revenues and enhance customer experience. © 2022 IEEE.

Optimal interventions of infectious disease

The recent outbreak of novel coronavirus has highlighted the need for a benefit-cost framework to guide unconventional public health interventions aimed at reducing close contact between infected and susceptible individuals. In this paper, we propose an optimal control problem for an infectious disease model, wherein the social planner can control the transmission rate by implementing or lifting lockdown measures. The objective is to minimize total costs, which comprise infection costs, as well as fixed and variable costs associated with lockdown measures. We establish conditions concerning model primitives that guarantee the existence of a straightforward optimal policy. The policy specifies two switching points (Formula presented.), whereby the social planner institutes a lockdown when the percentage of infected individuals exceeds (Formula presented.), and reopens the economy when the percentage of infected individuals drops below (Formula presented.). We subsequently extend the model to cases where the social planner may implement multiple lockdown levels. Finally, numerical studies are conducted to gain additional insights into the value of these controls. © 2023 Wiley Periodicals LLC.

Perceptions of the Vaccinated and Unvaccinated to Inform Translation to Health and Public Health Practice

OBJECTIVES/GOALS: Translating the science of vaccines to health and public health practice requires understanding how vaccine risks and benefits are understood and applying that knowledge to community translation. During the pandemic the lack of this knowledge became apparent. METHODS/STUDY POPULATION: Through the PACER community engagement special interest group of the ACTS, the University of Florida(UF)/Florida State University and 5 other CTSIs community engagement programs received Center for Disease Control and Prevention funding for the Program to Alleviate National Disparities in Ethnic and Minority Immunizations in the Community (PANDEMIC) to translate vaccinations into the community. At UF, HealthStreet's Community Health Workers, CTSI Mobile Health Vehicle nurses, and Institute of Food and Agricultural Sciences extension agents collaborated to engage adults throughout the North and Central part of the state on their vaccine status and perceptions and to offer them vaccines. RESULTS/ANTICIPATED RESULTS: Through UF, 4,587 people have been interviewed in community settings using the Survey of Perceptions;25% (1,125) had not received any COVID-19 vaccine. Among differences in perceptions, those vaccinated versus unvaccinated perceived people to be getting vaccines because they cut down on disease spread (28.9% vs. 15.2%), and perceived people NOT to be getting vaccinated because of misinformation/ignorance (27.1% vs. 11.0%) and political beliefs (16.3% vs. 6.7%). Both vaccinated and not perceived lack of trust as a reason to not get vaccinated (41.3% vs 46.4%). When asked what people were doing instead of vaccination, those vaccinated versus unvaccinated responded that people were doing nothing/very little much more often (40.6% vs. 21.8%) but were less likely to say 'trying to stay healthy' (9.1% vs. 18.9%). DISCUSSION/SIGNIFICANCE: The science of translating from bench through clinical trials and to common health and public health practice requires knowledge of reasons for successful adoption. This survey adds to knowledge of perceptions towards vaccines that inhibit translation and biases toward the vaccine-hesitant.

Gastronomic tourism in India-a transaction cost perspective

The purpose of this chapter is to present an economic perspective of how understanding individual decision-making can be impacted by transactional costs, and benefits in the context of gastronomic tourism. This chapter broadly discusses observable and perceived information search, bargaining and decision, policing and enforcement costs, and benefits in the context of gastronomic tourism in India. The proposed framework incorporates elements of Indian gastronomic offerings for tourists. Implications are discussed for future research and in the backdrop of the post-COVID-19 crisis. © 2022 Amit Sharma.

[Life and Money? Life or Money? -Health Economic Assessment and Value Assessment for Oncology Medications]

Health economics seek to provide the information which can contribute to the rational decision making, towards the appropriate allocation of scarce healthcare resources. Through the COVID-19 pandemic, everyone has recognized that healthcare resource would not be infinite and general public would no longer permit too excessive resource allocation for healthcare area, which might cause the conflict against other social activities. Even under the Universal Health Coverage, some restriction for coverage should be implemented, to maintain the public health care system. The health economic evaluation, or cost-effectiveness evaluation could be used for coverage decision of healthcare intervention for public health system, as it aimed to assess both costs and health outcome of candidate intervention against the conventional ones. The ICER, additional costs divided by additional outcomes could be used as"benchmark"of cost-effectiveness. The QALYs, quality-adjusted life years, was widely used as a"common"outcome measure, which enables us to evaluate interventions regardless of type of the diseases. However, cost-effectiveness data, or cost data with QALY data should not be the"only"benchmark value for decision making. Various aspects, outside of costs and QALYs, such as productivity losses and family spillovers, would constitute the"value"of interventions. How to evaluate the value of healthcare interventions must be differed from how to evaluate the cost-effectiveness of them.

Risk assessment using information entropy

Risk assessment, particularly when using simulations, requires that the analyst develops estimates of expected, low, and high values for inputs. Mean and standard deviation are often used to assess the variability of metrics, assuming that the underlying distribution is normal. However, it is increasingly realized that non-normal distributions are common and important. If data are available, it is simple and straightforward to check this assumption by computing higher order moments.Claude Shannon [1], [2] proposed that the information entropy for a set of N discrete events can be measured by (Formula Presented) E. T. Jaynes [3] proposed that, if data is available, information entropy can be maximized using Lagrangian multipliers and that the resulting probability distribution maximizes the uncertainty of that distribution given the data.In order to use entropy maximization, it is required to define constraints such that Σpi = 1, plus constraints on the mean, variance, skew, kurtosis, and other moments. This problem does not have a closed form solution but can be solved iteratively in a spreadsheet.The problem can be set up as follows for mean bar x and variance s2: (Formula Presented) This basic formulation models the normal distribution. The importance of non-normality can be estimated by adding higher order moments as desired. For n ≥ 3, constraints can be added using: (Formula Presented) where Mn is the computed nth moment of the data set.Differentiating ∂H/∂pi = 0 maximizes information entropy, and the resulting probability distribution has the most uncertainty given the observed data.This suggests that it is possible to develop an estimate of the distribution where some values are underrepresented in the sample. It further suggests that unusual or atypical results can be better estimated.This paper uses the method of maximizing entropy to model observed data and will study two time series applications. One problem of interest is sequential acquisition of data. For example, time to failure for a device may be a metric of concern. A maximum entropy model provides an empirical estimate of the distribution of this metric. A second problem of interest is forecasting the distribution of a metric at some point in the future. This applies to supply chain management. Project sponsors prepare cost and schedule estimates well in advance of placing the orders for the materials used in those projects. Management reserves for cost and schedule are typically set by subject matter experts, and recent experience (e.g., supply chain disruptions due to the COVID19 pandemic) may overemphasize current data when developing risk assessments. This approach offers a datadriven way to empirically develop risk assessments. © 2023 IEEE.

Intermediate Respiratory Care Units: Questions and Answers

The intermediate respiratory care units (UCRI) are areas of monitoring and specialized care of patients with acute or chronic-exacerbated respiratory failure, whose severity does not require admission to an intensive care unit, but which due to their complexity cannot be treated in conventional hospitalization. Although the COVID-19 pandemic has proven its usefulness in the management of critical respiratory patients, the historical trajectory of the UCRI comes from many years ago, in which its cost-effectiveness has been demonstrated by far. This document presents a series of questions and answers on the history of the UCRI, in addition to the criteria for admission, infrastructure, human and technical resources, and the types of existing Units. Within the UCRI year 2021-2022 designated by the Spanish Society of Pneumology and Thoracic Surgery, any scientific dissemination linked to the in-depth knowledge of these units is timely, where multidisciplinarity and the work of professionals related to the care of critical respiratory patients converge.Copyright © 2022

Designing IAQ-Resilient Post-Pandemic Buildings

The COVID-19 pandemic has led to significant changes to human life and habits. There is an increasing urgency to promote occupants' health and well-being in the built environment where they spend most of their lives, putting indoor air quality (IAQ) in the spotlight. This study fits into this context, aiming to provide useful information about the design, construction, and operation of an IAQ-resilient building in the post-pandemic era for it to ensure a good trade-off between energy- and health-related objectives. The PRISMA guidelines were adopted to conducting a systematic review obtaining 58 studies that offered relevant results on two main research areas: (i) the concept of resilience, focusing on its definition in relation to the built environment and to pandemic-related disruptions;and (ii) the building design strategies that are able to increase buildings' resilience, focusing on the preventive measures involving engineering control. In addition, the metrics and the decision-making tools able to make IAQ-resilient buildings attractive to the investors, focusing on the cost-benefit analysis (CBA) technique, were discussed. The research supported the transition of the building sector to a human-centered approach that is able to include IAQ resilience among the main priorities of future buildings to guarantee the occupants' health and well-being. © 2023 by the authors.

this Research has Important Policy Implications...

The COVID 19 pandemic has generated much interest in the relationship between research and policy. It has drawn new attention to the limitations of a linear model, where policy is based on first observing prior scientific research and then designed in response to this. Conflict researchers often motivate the importance of their work by claiming that their "research has important policy implications", but the proposals offered are often at best incomplete. I identify a number of common limitations in claims about policy implications, including a lack of discussion of objectives and priorities, stating objectives themselves as if they were policies, claims about targeting factors without discussing the effectiveness of possible interventions, and a failure to consider uncertainty and potential tensions with other objectives or unintended effects. Research can potentially inform policy discussions and improve decisions, but the incentives in academic research are very different from policy decisions, and the latter often calls for very different evidence than what is offered by the former. Rather than attempting to offer policy prescriptions as an afterthought to academic articles, research can be more helpful to policy by trying to inform debates, focusing on what we know from the cumulative body of research than individual manuscripts, and providing new data and empirical material that allow for better problem description and analysis. © 2023 the author(s), published by De Gruyter, Berlin/Boston 2023.