Vaccine ethics: An ethical framework for global distribution of COVID-19 vaccines

This paper addresses the just distribution of vaccines against the SARS-CoV- 2 virus and sets forth an ethical framework that prioritises frontline and essential workers, people at high risk of severe disease or death, and people at high risk of infection. Section I makes the case that vaccine distribution should occur at a global level in order to accelerate development and fair, efficient vaccine allocation. Section II puts forth ethical values to guide vaccine distribution including helping people with the greatest need, reducing health disparity, saving the most lives and promoting narrow social utility. It also responds to objections which claim that earlier years have more value than later years. Section III puts forth a practical ethical framework to aid decision-makers and compares it with alternatives. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Economic Evaluation of Decennial Pertussis Vaccination with Tetanus, Diphtheria and Acellular Pertussis (TDAP) Vaccine in Adult Populations with Asthma or Chronic Obstructive Pulmonary Disease (COPD) in Brazil

Objectives: Pertussis, a highly contagious respiratory disease caused by Bordetella pertussis, is endemic in Brazil, but is underdiagnosed in adults due to atypical symptomatology and limited diagnosis time window. Brazil's Ministry of Health recommends decennial boosters in adults against diphtheria and tetanus, but not pertussis. After the COVID-19 pandemic, infectious diseases surged worldwide due to lack of natural exposure and reduced immunization coverage. Asthma and COPD populations are at increased risk of pertussis infection. This study assessed the cost-utility of decennial pertussis vaccination with Tdap vaccine versus no pertussis vaccination in Brazil's adult asthma and COPD populations in a high-incidence context. Method(s): A static cross-sectional population-based cost-utility model of decennial Tdap boosters in asthma patients >=50 years and COPD patients >=40 years was developed from the payer's perspective. Pertussis incidence from Sao Paulo's state surveillance system in the peak year 2014 was adjusted for underdiagnosis and relative risk of pertussis in asthma and COPD populations. Vaccine efficacy and coverage, and costs and outcomes discounted at 5%, were obtained from the literature and public databases. Deterministic and probabilistic sensitivity analyses, and scenario analyses were run, including alternative annual incidence. Result(s): In the asthma population, Tdap boosters would incur 7,065,788 Brazilian reais (BRL) direct costs and save 32.85 Life Years (LYs) and 262.13 Quality-Adjusted LYs (QALYs). In the COPD population, Tdap boosters would incur 41,102,844 BRL direct costs and save 157.47 LYs and 1,078.26 QALYs. Discounted incremental cost-utility ratios were 26,956 and 38,120 BRL/QALY in asthma and COPD populations, respectively. At a cost-effectiveness threshold of 1 Gross Domestic Product (GDP)/capita, 85.8% and 49.7% of simulations were cost-effective in asthma and COPD populations, respectively, while all simulations were cost-effective at a threshold of 3 GDP/capita. Conclusion(s): Implementing decennial Tdap boosters for adult asthma and COPD patients should be considered, given the favorable cost-utility profile in peak-incidence years.Copyright © 2023

Future directions for health information exchange

Health information exchange (HIE) now exists in diverse forms within and across countries. However, our HIE infrastructure is fragmented, which impedes the ability to meet the needs of varied data sharing use cases—particularly public health data needs that became evident during the COVID-19 pandemic. In response, several efforts—some within the United States and some outside the United States—have started to undertake work to help tie existing HIE approaches together into a more seamless whole. While the societal benefits of doing so are clear, there are substantial cost and complexity involved, leaving it an open question as to how successful they will be. This chapter describes three major efforts underway to advance HIE infrastructure at scale—the Trusted Exchange Framework and Common Agreement (a US policy strategy), the Joint Action Towards the European Health Data Space (an EU initiative), and the emerging concept of health data utility models as more comprehensive repositories of health data with strong government requirements for participation. For each, we describe the effort as well as discuss potential challenges to implementation and success in achieving the intended outcomes. We also discuss a complementary issue related to health data integration and usability of exchanged health information that will become more acute as efforts to advance data sharing at scale are pursued. © 2023 Elsevier Inc. All rights reserved.

Clinical utility of SARS-CoV-2 subgenomic RT-PCR in a pediatric quaternary care setting.

BACKGROUND: During active transcription, SARS-CoV-2 generates subgenomic regions of viral RNA. While standard SARS-CoV-2 RT-PCR amplifies region(s) of genomic RNA, it cannot distinguish active infection from remnant viral genomic material. However, screening for subgenomic RNA (sgRNA) by RT-PCR may aid in the determination of actively transcribing virus. OBJECTIVES: To evaluate the clinical utility of SARS-CoV-2 sgRNA RT-PCR testing in a pediatric population. STUDY DESIGN: Retrospective analysis was performed on inpatients from February-September 2022 positive for SARS-CoV-2 by RT-PCR with a concomitant order for sgRNA RT-PCR. Chart abstractions were conducted to determine clinical outcomes, management, and infection prevention and control (IPC) practices. RESULTS: Of 95 SARS-CoV-2 positive samples from 75 unique patients, 27 (28.4%) were positive by sgRNA RT-PCR. A negative sgRNA RT-PCR test allowed for de-isolation in 68 (71.6%) patient episodes. Regardless of age or sex, a positive sgRNA RT-PCR result significantly correlated with disease severity (P = 0.007), generalized COVID-19 symptoms (P = 0.012), hospitalization for COVID-19 (P = 0.019), and immune status (P = 0.024). Moreover, sgRNA RT-PCR results prompted changes in management in 28 patients (37.3%); specifically, therapeutic escalation in 13/27 (48.1%) positives and de-escalation in 15/68 (22.1%) negatives. CONCLUSIONS: Taken together, these findings underscore the clinical utility of sgRNA RT-PCR testing in a pediatric population as we report significant associations between sgRNA RT-PCR results and clinical parameters related to COVID-19. These findings align with the proposed use of sgRNA RT-PCR testing to guide patient management and IPC practices in the hospital setting.

Why do people shop? Understanding consumer e-commerce shopping intention in Indonesia: Mediating effect of shopping orientation

Purpose: The COVID-19 pandemic has led to an increase in the use of e-commerce as a shopping platform in Indonesia. This study aims to identify the factors that influences consumers' intention to shop through e-commerce platforms. Design/Methodology/Approach: The study uses a survey method to collect data from online shoppers in the 11-24 age range. The research model includes shopping orientation as a mediating variable. The data analysis reveals that perceived enjoyment, social norms, social presence, and perceiver utility positively and significantly affect e-commerce shopping intention. The study also identifies the mediating role of shopping orientation. Finding: The results shows that shopping orientation fully mediates the relationship between perceived utility and e-commerce shopping intention. Conclusion: The study highlights the importance of perceived enjoyment, social norms, social presence, perceived utility, and shopping orientation in driving e-commerce shopping intention. To increase perceived utility, e-commerce managers should provide information that emphasizes the convenience of shopping through their platforms. Finally, what can be implied from this study's results is how managers can increase the shopping orientation of potential consumers. Research Limitation: The study's sample is limited to consumers aged 11 to 24 years, where at that age, many people in Indonesia do not have good purchasing power. Future research should consider a more diverse sample. Additionally, the study only examines the full mediation of shopping orientation on the relationship between perceived utility and e-commerce shopping intention. Therefore, further research is recommended to examine whether shopping orientation is fully mediated in the relationship between perceived utility and e-commerce shopping intention. © 2023 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Emergency plan selection for epidemic prevention and control based on cumulative prospect theory and hybrid-information MADM

PurposeDecision-making problems in emergency plan selection for epidemic prevention and control (EPAC) are generally characterized by risky and uncertainty due to multiple possible emergency states and vagueness of decision information. In the process of emergency plan selection for EPAC, it is necessary to consider several obvious features, i.e. different states of epidemics, dynamic evolvement process of epidemics and decision-makers' (DMs') psychological factors such as risk preference and loss aversion.Design/methodology/approachIn this paper, a novel decision-making method based on cumulative prospect theory (CPT) is proposed to solve emergency plan selection of an epidemic problem, which is generally regarded as hybrid-information multi-attribute decision-making (HI-MADM) problems in major epidemics. Initially, considering the psychological factors of DMs, the expectations of DMs are chosen as reference points to normalize the expectation vectors and decision information with three different formats. Subsequently, the matrix of gains and losses is established according to the reference points. Furthermore, the prospect value of each alternative is obtained and the comprehensive prospect values of alternatives under different states are calculated. Accordingly, the ranking of alternatives can be obtained.FindingsThe validity and robustness of the proposed method are demonstrated by a case calculation of emergency plan selection. Meanwhile, sensitivity analysis and comparison analysis with fuzzy similarity to ideal solution (FTOPSIS) method and TODIM (an acronym in Portuguese for interactive and MADM) method illustrate the effectiveness and superiority of the proposed method.Originality/valueAn emergency plan selection method is proposed for EPAC based on CPT, taking into account the psychological factors of DMs.HighlightsThis paper proposes a new CPT-based EDM method for EPAC under a major epidemic considering the psychological factorsof DMs, such as risk preference, loss aversion and so on.The authors' work gives approaches of normalization, comparison and distance measurement for dealing with the integration of three hybrid formats of attributes.This article gives some guidance, which contributes to solve the problems of risk-based hybrid multi-attribute EDM.The authors illustrate the advantages of the proposed method by a sensitivity analysis and comparison analysis with existing FTOPSIS method and TODIM method.

A Comprehensive Analysis of Clustering Public Utility Bus Passenger's Behavior during the COVID-19 Pandemic: Utilization of Machine Learning with Metaheuristic Algorithm

Public utility bus (PUB) systems and passenger behaviors drastically changed during the COVID-19 pandemic. This study assessed the clustered behavior of 505 PUB passengers using feature selection, K-means clustering, and particle swarm optimization (PSO). The wrapper method was seen to be the best among the six feature selection techniques through recursive feature selection with a 90% training set and a 10% testing set. It was revealed that this technique produced 26 optimal feature subsets. These features were then fed into K-means clustering and PSO to find PUB passengers' clusters. The algorithm was tested using 12 different parameter settings to find the best outcome. As a result, the optimal parameter combination produced 23 clusters. Utilizing the Pareto analysis, the study only considered the vital clusters. Specifically, five vital clusters were found to have comprehensive similarities in demographics and feature responses. The PUB stakeholders could use the cluster findings as a benchmark to improve the current system.

Developing the Patient Falls Risk Report: A Mixed-Methods Study on Sharing Falls-Related Clinical Information from Home Care with Primary Care Providers.

If interRAI home care information were shared with primary care providers, care provision and integration could be enhanced. The objective of this study was to co-develop an interRAI-based clinical information sharing tool (i.e., the Patient Falls Risk Report) with a sample of primary care providers. This mixed-methods study employed semi-structured interviews to inform the development of the Patient Falls Risk Report and online surveys based on the System Usability Scale instrument to test its usability. Most of the interview sample (n = 9) believed that the report could support patient care by sharing relevant and actionable falls-related information. However, criticisms were identified, including insufficient detail, clarity, and support for shared care planning. After incorporating suggestions for improvement, the survey sample (n = 27) determined that the report had excellent usability with an overall usability score of 83.4 (95% CI = 78.7-88.2). By prioritizing the needs of end-users, sustainable interRAI interventions can be developed to support primary care.

How goal framing and temporal distance influence the effectiveness of COVID- 19 vaccine persuasion

Vaccines are crucial for controlling deadly diseases, and how to persuade people to get vaccinated has become a hot topic in enhancing public health benefits. One way to increase the vaccination rate is to raise public awareness of the importance of vaccines through advertising. As an effective and cost-friendly approach, goal framing has been widely used in vaccine advertising. However, the literature has mixed findings about whether positive or negative goal framing is more effective in persuading people to get vaccinated. The present study aims to investigate how temporal distance (present vs. future) interacts with different types of goal framing (positive vs. negative) in persuading people to get the COVID-19 vaccine. We hypothesized that negative goal framing is more persuasive when the advertising focuses on present outcomes, while positive goal framing is more effective when combined with future- focused outcomes. We further hypothesized that the inner mechanism is the intertemporal asymmetry of approach and avoidance motivation. More specifically, the avoidance motivation induced by a negative frame is stronger in the present, while the approach motivation induced by a positive frame is stronger in the future. The perceived risk of COVID-19 moderated this effect. Four studies were conducted to examine our hypotheses. Study 1 was conducted to preliminarily investigate how goal framing and temporal distance jointly influence willingness to get the COVID-19 vaccine. The aim of Study 2 was to verify the mediating effect of approach and avoidance motivation in a different advertising setting, as well as to rule out the potential mediators of the construal level and positive/ negative emotions. In Study 3, we further tested the mediators by manipulating participants' approach and avoidance motivation. Study 4 was a quasi-experiment in which we recruited participants from areas with different levels of COVID-19 risk to test how perceived risk moderated the interaction effect of goal framing and temporal distance. The results showed that a negative goal frame was more persuasive when combined with present-focused advertising, while a positive goal frame was more effective when combined with future- focused advertising (Study 1, N = 363). Avoidance motivation mediated the relationship between the goal frame and vaccine uptake in the present context, while approach motivation mediated the relationship between the goal frame and vaccine uptake in the future context (Study 2, N = 292). The results in Study 3 ( N = 347) revealed that approach motivation priming increases the persuasiveness of the present-positive frame, while avoidance motivation priming increases the persuasiveness of the future- negative frame. COVID-19 risk also had an impact on the relationship between goal framing and temporal distance on vaccine uptake. When the COVID-19 risk was high, the difference in vaccine uptake between present-positive and present-negative conditions disappeared, while the future-positive frame was still more persuasive than the future- negative frame (Study 4, N = 423). In conclusion, the present study found an interactive effect of goal framing and temporal distance in persuading people to get the COVID-19 vaccine. Avoidance/approach motivation mediates the relationship between goal framing and vaccine uptake in the present/future temporal context. The perceived COVID risk further moderated the interaction effect. The present study contributes to both the framing and approachavoidance motivation literature and sheds light on future practices in persuading people to get the COVID vaccine and promoting the uptake of other vaccines.

Extended High-Utility Pattern Mining: An Answer Set Programming-Based Framework and Applications

Detecting sets of relevant patterns from a given dataset is an important challenge in data mining. The relevance of a pattern, also called utility in the literature, is a subjective measure and can be actually assessed from very different points of view. Rule-based languages like Answer Set Programming (ASP) seem well suited for specifying user-provided criteria to assess pattern utility in a form of constraints;moreover, declarativity of ASP allows for a very easy switch between several criteria in order to analyze the dataset from different points of view. In this paper, we make steps toward extending the notion of High-Utility Pattern Mining;in particular, we introduce a new framework that allows for new classes of utility criteria not considered in the previous literature. We also show how recent extensions of ASP with external functions can support a fast and effective encoding and testing of the new framework. To demonstrate the potential of the proposed framework, we exploit it as a building block for the definition of an innovative method for predicting ICU admission for COVID-19 patients. Finally, an extensive experimental activity demonstrates both from a quantitative and a qualitative point of view the effectiveness of the proposed approach.

Methodology to Support the Triage of Suspected COVID-19 Patients in Resource-Limited Circumstances

COVID-19 pandemic has put health systems worldwide under pressure. Thus, establish a triage protocol to support the allocation of resources is important to deal with this public health crisis. In this paper, a structured methodology to support the triage of suspected or confirmed COVID-19 patients has been proposed, based on the utilitarian principle. A decision model has been proposed for evaluating three treatment alternatives: intensive care, hospital stay and home isolation. The model is developed according to multi-attribute utility theory and considers two criteria: the life of the patient and the overall cost to the health system. A screening protocol is proposed to support the use of the decision model, and a method is presented for calculating the probability of which of three treatment is the best one. The proposed methodology was implemented in an information and decision system. The originality of this study is using of the multi-attribute utility theory to support the triage of suspected COVID-19 and implement the decision model in an information and decision system.

Investigation of the Prognostic Values of the Shock Index and Modified Shock Index in Predicting the Clinical Outcomes in Elderly Hospitalized Patients with Coronavirus Disease-2019

Introduction: Advanced age is an independent risk factor for increased mortality in coronavirus disease-2019 (COVID-19). However, the best method for estimating mortality in elderly patients with COVID-19 is still under debate. We performed this study to assess the shock index (SI) and the modified shock index (MSI) for the abovementioned problem. Methods: A retrospective study was conducted including elderly cases (>= 65 years) confirmed with COVID-19 who admitted to a tertiary university hospital between March-December 2020. The SI and MSI at the time of the emergency department visits were used to evaluate the intensive care unit admission, ventilator support, septic shock, and 30-day mortality in all patients. The receiver operating characteristic and area under the curve (AUC) were used to measure the overall ability of SI and MSI to predict clinical outcomes. Results: We recruited 334 consecutive COVID-19 patients with a mean age of 75.2 +/- 7.3 and an almost equal gender distribution [170 males (50.9%)]. In deceased and surviving patients, the SI was 0.66 +/- 0.16 and 0.6 +/- 0.1 (p=0.014), while the MSI was 0.95 +/- 0.22 and 1.09 +/- 0.34 (p=0.003), respectively. In predicting mortality, the AUC of the SI and MSI were 0.590 [95% confidence interval (CI): 0.535 to 0.643] and 0.608 (95% CI: 0.553 to 0.660), respectively. Conclusion: Increased SIs and MSIs are associated with 30-day mortality. SI and MSI can benefit the triage of elderly patients hospitalized for COVID-19. However, it was found that there is no single cut-off value of SI or MSI with optimum accuracy for predicting COVID-19-related clinical outcomes.

Small Drinking Water Utilities? Resilience: The Case of the COVID-19 Pandemic

Extreme events can significantly disrupt the operation and maintenance (O&M) of drinking water utilities (DWUs), compromising community access to water in critical times. However, we posit that utility size can influence DWUs' resilience, as large DWUs may have a greater capacity to handle extreme and sudden changes characteristic of emergencies. Here, we explore the resilience of small DWUs by understanding how a global crisis (i.e., the COVID-19 pandemic) affected small DWUs and how these impacts statistically differ from those of large DWUs using statistical inferencing. We used two data sets that reflect the perspectives of 28 large and 26 small DWUs from 14 states. We found that small DWUs experienced issues involving supply chain, finances, and personnel management that pre-existing issues may have magnified. Additionally, small and large DWUs experienced statistically significant differences in personnel management, revenue change, increase in delinquent accounts, and emergency response plan activation. For example, large DWUs experienced more revenue loss than small DWUs due to economies of scale and larger changes from status quo operations. This study reveals areas of concern (and opportunities) regarding the resiliency of small DWUs in the face of emergencies that can allow policymakers to assist small DWUs.

Cost-Utility analysis for rapid severe acute respiratory syndrome-coronavirus-2 antigen detection assay in comparison versus real-time reverse transcription-polymerase chain reaction assay for laboratory diagnosis of coronavirus disease -2019

Background: The global pandemic of coronavirus disease-2019 (COVID-19) is still spreading. As a result, rapid, simple, and accurate diagnostics to diagnose severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection are urgently needed. For the diagnosis of COVID-19 cases, the performance characteristics of the quick SARS-CoV-2 antigen detection test should be investigated and compared to the gold standard real-time reverse transcription-polymerase chain reaction (RT-PCR) test. The utility of the antigen detection test is reported from field evaluation. However, an interesting concern is on the utility of the test. Methods: Here, the authors perform a cost utility analysis to appraise rapid SARS-CoV-2 antigen detection assay in comparison versus real-time RT-PCR assay for laboratory diagnosis of COVID-19. Results: According to the analysis, the cost per utility of rapid SARS-CoV-2 antigen detection assay is 3.24 times less than that of comparison versus real-time RT-PCR assay. Conclusion: Hence, it can conclude that rapid SARS-CoV-2 antigen detection assay is appropriate for using for diagnosis of COVID-19 in term of cost-utility. © The Author(s) 2023.

Service center location problems with decision dependent utilities and a pandemic case study

We study a service center location problem with ambiguous utility gains upon receiving service. The model is motivated by the problem of deciding medical clinic/service centers, possibly in rural communities, where residents need to visit the clinics to receive health services. A resident gains his utility based on travel distance, waiting time, and service features of the facility that depend on the clinic location. The elicited location-dependent utilities are assumed to be ambiguously described by an expected value and variance constraint. We show that despite a non-convex nonlinearity, given by a constraint specified by a maximum of two second-order conic functions, the model admits a mixed 0-1 second-order cone (MISOCP) formulation. We study the non-convex substructure of the problem, and present methods for developing its strengthened formulations by using valid tangent inequalities. Computational study shows the effectiveness of solving the strengthened formulations. Examples are used to illustrate the importance of including decision dependent ambiguity. An illustrative example to identify locations for Covid-19 testing and vaccination is used to further illustrate the model and its properties. © 2023 The Authors. Naval Research Logistics published by Wiley Periodicals LLC.

Epilogue

The evidence is overwhelming in favor of the public choice explanation of the pandemic decision-making while simultaneously refuting all the public-interest claims thereof. The theoretical presuppositions upon which public choice theory relies are more robust than the ones of public-interest explanation, and this is vindicated once again when the two theories are applied to the Covid-19 pandemic. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Triaging and managing Covid-Inequities and ethical decision-making

Early identification and separation of suspected Covid-19 patients at triage is vital to prevent disease transmission in healthcare settings. Triaging is a complex and context-specific process to implement especially where resources are scarce and health systems are fragile. The need to allocate these resources in a consistent, transparent, and equitable manner during the covid-19 pandemic is underpinned by ethical principles among which are utilitarianism and egalitarianism. Considerations of social identities such as age, gender, social class, and medical criteria such as comorbidities and frailty may lead to explicit and implicit bias and attendant discrimination. Theoretical constructs such as narrow social utility and reciprocity may be invoked to justify the prioritisation of healthcare workers (HCWs) infected with Covid-19 despite the pitfalls in the underlying assumptions. As no single framework exists to comprehensively guide the Covid-19 triage process, the establishment of institutional recommendations and policies within which are embedded safety nets for managing the physical, mental, and emotional fallouts on HCWs is critical. © 2023 Kemi Ogunyemi and Adaora I. Onaga. All rights reserved.

Use of Rapid Antigen Tests to End Isolation in a University Setting: Observational Study.

BACKGROUND: COVID-19 isolation recommendations have evolved over the course of the pandemic. Initially, the US Centers for Disease Control and Prevention required 10 days of isolation after a positive test result. In December 2021, this was reduced to a minimum of 5 days with symptom improvement, followed by 5 days of mask wearing. As a result, several institutions of higher education, including the George Washington University, required persons testing positive for COVID-19 to either submit a negative rapid antigen test (RAT) with symptom resolution to leave isolation after 5 days or to maintain a 10-day isolation period in the absence of a negative RAT and the presence of continued symptoms. RATs are tools that can be used both to shorten isolation periods and to ensure that persons testing positive for COVID-19 remain in isolation if infectious. OBJECTIVE: The purpose of this analysis is to report on the experience of implementing RAT policies, examine the number of days that isolation was reduced via RAT testing, determine the factors that predicted uploading a RAT, and determine RAT positivity percentages to illustrate the utility of using RATs to end isolation. METHODS: In this study, 880 individuals in COVID-19 isolation at a university in Washington, DC, uploaded 887 RATs between February 21 and April 14, 2022. Daily positivity percentages were calculated, and multiple logistic regression analyses examined the odds of uploading a RAT by campus residential living status (ie, on or off campus), student or employee designation, age, and days in isolation. RESULTS: A total of 76% (669/880) of individuals in isolation uploaded a RAT during the study period. Overall, 38.6% (342/887) of uploaded RATs were positive. Uploaded RATs were positive 45.6% (118/259) of the time on day 5; 45.4% (55/121) on day 6; 47.1% (99/210) on day 7; and 11.1% (7/63) on day 10 or beyond. Adjusted logistic regression modeling indicated cases living on campus had increased odds of uploading a RAT (odds ratio [OR] 2.54, 95% CI 1.64-3.92), whereas primary student affiliation (OR 0.29, 95% CI 0.12-0.69) and days in isolation (OR 0.45, 95% CI 0.39-0.52) had decreased odds of uploading a RAT. Of the 545 cases with a negative RAT, 477 were cleared prior to day 10 of their isolation due to lack of symptoms and timely submission, resulting in a total of 1547 days of lost productivity saved compared to all being in isolation for 10 days. CONCLUSIONS: RATs are beneficial, as they can support a decision to release individuals from isolation when they have recovered and maintain isolation for people who may still be infectious. Future isolation policies should be guided by similar protocols and research to reduce the spread of COVID-19 and minimize lost productivity and disruption to individuals' lives.

A Novel Statistical and Neural Network Combined Approach for the Cloud Spot Market

The price of virtual machine instances in the Amazon EC2 spot model is often much lower than in the on-demand counterpart. However, this price reduction comes with a decrease in the availability guarantees. Several mechanisms have been proposed to analyze the spot model in the last years, employing different strategies. To our knowledge, there is no work that accurately captures the trade-off between spot price and availability, for short term analysis, and does long term analysis for spot price tendencies, in favor of user decision making. In this work, we propose (a) a utility-based strategy, that balances cost and availability of spot instances and is targeted to short-term analysis, and (b) a LSTM (Long Short Term Memory) neural network framework for long term spot price tendency analysis. Our experiments show that, for r4.2xlarge, 90 percent of spot bid suggestions ensured at least 5.73 hours of availability in the second quarter of 2020, with a bid price of approximately 38 percent of the on-demand price. The LSTM experiments were able to predict spot prices tendencies for several instance types with very low error. Our LSTM framework predicted an average value of 0.19 USD/hour for the r5.2xlarge instance type (Mean Squared Error [Formula Omitted]) for a 7-day period of time, which is about 37 percent of the on-demand price. Finally, we used our combined mechanism on an application that compares thousands of SARS-CoV-2 DNA sequences and show that our approach is able to provide good choices of instances, with low bids and very good availability.

Natural gas and the utility sector nexus in the U.S.: Quantile connectedness and portfolio implications

Given that natural gas is a vital input for the U.S. utility sector, this study empirically investigates the return connectedness between the natural gas and utility stocks in the U.S. market. Using the quantile connectedness approach, we show that the nexus between natural gas and utility stocks is more pronounced at the tails compared to the central of the conditional distribution. The return connectedness indices are time-varying with a net receiver role of natural gas and driven by various macro-variables. Finally, our portfolio implication analyses with alternative tail risk measures suggest that it can be more beneficial for risk-adverse investors to allocate substantial weights into the electricity utility stocks in normal market conditions. However, during the COVID-19- induced recession, it is critical to shift more fund to the natural gas futures to reduce tail risks. © 2023 Elsevier B.V.