Prioritization Scheme Research Articles

Cost-effectiveness analysis of COVID-19 vaccination in Poland.

IntroductionThe aim of our study was to assess the potential value of the Comirnaty vaccine (BNT162b2) in Poland. A model was used to estimate patient events, direct medical costs, utilities, and cost-effectiveness for 1 year with and without implementation of the vaccine.Material and methodsThe Markov model with 1-week cycles was used to estimate patient events, direct medical costs, utilities, and cost-effectiveness for 1 year with and without implementing the Comirnaty vaccine in Poland. The incremental cost per quality-adjusted life-year (QALY) gained vs. no vaccine was calculated for the general population and selected age-groups. All costs are reported in PLN (average exchange rate in 2020: 1 EUR = 4.44 PLN).ResultsIn the base case analysis the incremental cost per QALY gained associated with vaccinating the whole population is 6249 PLN. For individuals aged 60–69 years and > 80 years vaccination is less costly and more effective than no vaccination. The incremental cost per QALY gained when vaccinating individuals aged 40–49 and 30–39 years is 28,135 PLN and 67,823 PLN, respectively. In the general population and in younger subpopulations the incremental cost-effectiveness ratio is most sensitive to the vaccine effectiveness, vaccine price, and SARS-CoV-2 infection rates.ConclusionsWhen prioritization is required due to supply constraints, vaccination of the elderly is justified because it gives the highest number of QALY gained and generates savings for the health care system. Continual updates of the model concerning vaccine real-life effectiveness and epidemic course are required to refine the prioritisation scheme in the future.

Service Prioritization in Information Centric Networking With Heterogeneous Content Providers

Service prioritization brings reasonable allocation of network resources and improves the overall quality of experience (QoE) of users, but it has not been thoroughly investigated in information centric networking (ICN). Existing works lack adaptability and they cannot ensure specific content provider (CP) get well caching service which is one of the most important functions in ICN. In this paper, we firstly propose a service prioritization scheme to flexibly provide different caching services for heterogeneous CPs to improve the overall network efficiency. The main idea is to allocate dedicated cache space for paying CPs and provide prioritized caching service for them, while normal CPs only enjoy the normal caching service. The scheme can be divided into two phases. First, we select a group of nodes with higher importance as core nodes based on network topology, and pair each edge node to a core node following the two-sided many-to-one matching algorithm. Second, we dynamically allocate and manage the dedicated cache space for core nodes. We model the allocation of dedicated cache space and convert it into a convex optimization problem to solve. After that, a practical caching strategy and system design are implemented in the ndnSIM simulator. Finally, we evaluate our scheme and conduct comparative experiments with the most representative work diff-caching, simulation results show that our scheme outperform it in terms of both delay and cache hit ratio.

EV Prioritization and Power Allocation During Outages: A Lexicographic Method-Based Multiobjective Optimization Approach

The growth in number of electric vehicles (EVs) has resulted in increased dependence of transportation on the power sector. During power outages, especially for elongated time spans, the locally available energy may not be sufficient to fulfill the energy needs of all the EVs. Therefore, a multicriteria EV prioritization scheme is proposed in this study to fairly allocate available energy among EVs during power outages. The five major factors considered for EV prioritization are trip purpose, EV occupants, energy gap, departure time, and customer behavior. With different combinations of the five prioritization factors, three indices are formulated, one each for social welfare, community wellbeing, and individual satisfaction of the EV owners. To this end, a multiobjective optimization problem is formulated, based on the three indices, to allocate the available power among EVs with higher index values. The formulated multiobjective optimization problem is solved using the lexicographic method, which has superior performance over the conventionally used weighted-sum method and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\varepsilon $ </tex-math></inline-formula> -constraint (EC) method. The proposed method is not sensitive to the weights of individual functions and has the ability to handle multiple priority levels. In order to quantify the results, percent served and unserved indices are formulated for each of the three parameters (social welfare, community wellbeing, and individual satisfaction) and the results of the proposed method are compared with those of the weighted-sum method and the EC method. Sensitivity analysis of different uncertain factors, such as number of EVs, uncertainty in EV demand, uncertainty in renewable power, and error in battery state-of-charge estimation, is also carried out. Simulation results have shown the superiority of the proposed method in allocating power to EVs during outages.

Optimising the impact of COVID-19 vaccination on mortality and hospitalisations using an individual additive risk measuring approach based on a risk adjustment scheme.

In this population-based cohort study, billing data from German statutory health insurance (BARMER, 10% of population) are used to develop a prioritisation model for COVID-19 vaccinations based on cumulative underlying conditions. Using a morbidity-based classification system, prevalence and risks for COVID-19-related hospitalisations, ventilations and deaths are estimated. Trisomies, behavioural and developmental disorders (relative risk: 2.09), dementia and organic psychoorganic syndromes (POS) (2.23) and (metastasised) malignant neoplasms (1.99) were identified as the most important conditions for escalations of COVID-19 infection. Moreover, optimal vaccination priority schedules for participants are established on the basis of individual cumulative escalation risk and are compared to the prioritisation scheme chosen by the German Government. We estimate how many people would have already received a vaccination prior to escalation. Vaccination schedules based on individual cumulative risk are shown to be 85% faster than random schedules in preventing deaths, and as much as 57% faster than the German approach, which was based primarily on age and specific diseases. In terms of hospitalisation avoidance, the individual cumulative risk approach was 51% and 28% faster. On this basis, it is concluded that using individual cumulative risk-based vaccination schedules, healthcare systems can be relieved and escalations more optimally avoided.Supplementary InformationThe online version contains supplementary material available at 10.1007/s10198-021-01408-8.

Protect, manage and then restore lands for climate mitigation

Limited time and resources remain to constrain the climate crisis. Natural climate solutions represent promising options to protect, manage and restore natural lands for additional climate mitigation, but they differ in (1) the magnitude and (2) immediacy of mitigation potential, as well as (3) cost-effectiveness and (4) the co-benefits they offer. Counter to an emerging preference for restoration, we use these four criteria to propose a general rule of thumb to protect, manage and then restore lands, but also show how these criteria explain alternative prioritization and portfolio schemes. This hierarchy offers a decision-making framework for public and private sector actors to optimize the effectiveness of natural climate solutions in an environment in which resources are constrained, and time is short.

Projected redistribution of sea turtle foraging areas reveals important sites for conservation

Identification of important habitats of charismatic marine megafauna is essential to enhance our conservation capacity. Still, for species such as sea turtles that have a long-life span, a complex life history and a highly migratory nature, spatially delineating important marine areas is not a simple task. Even in the case that such areas are identified, our ability to draw effective measures and propose conservation prioritization schemes faces additional challenges, due to the dynamic climate-driven redistribution of habitats. Here, we compile a database on foraging locations of loggerhead sea turtles across the Mediterranean Sea and use climatic niche models to predict the distribution of foraging grounds for juvenile and adult life stages. We explore potential shifts due to future changes in ocean temperature and identify sites, considered as important for both life stages, that will persist under climate change. We found extensive areas which could host foraging sites for juvenile loggerheads, distributed at the central and western Mediterranean, while adults’ foraging grounds had a more sparse and patchy distribution, mostly at the central and eastern part of the basin. Under future changes, expansions prevail over contractions, but projected redistribution of foraging space for both life stages will probably lead to remarkable losses of climatic suitability at certain sites. The coverage of important areas, hosted primarily at the neritic zone, will be extended in the future. Our analyses add a missing dimension to conservation efforts, related to the basin-wide distribution of important areas, offering novel insights towards incorporating climate change into conservation planning.

Spatial Feature-Based Prioritization for Transmission of Point Cloud Data in 3D-Image Sensor Networks

A sensor network that connects multiple 3D image sensor devices using light detection and ranging (LIDAR) is effective for collecting spatial information to detect potential risks associated with people’s movements. However, due to the large volume and high frame rate of point cloud data obtained by LIDAR devices, under the condition of strictly limited bandwidth, some part of the data can go missing when detection is performed from point cloud data, causing a degradation of the accuracy. As the communication traffic volume of other applications increases, the communication available bandwidth for spatial information applications becomes insufficient. This paper proposes a scheme of spatial feature-based prioritization for the transmission of point cloud data with strictly limited communication bandwidth. It estimates how much each piece of point cloud data contributes to the accuracy improvement of a machine learning task for spatial prediction and assigns a higher score to those with a larger contribution. These scores prioritize the control for the transmission of point cloud data from sensor devices to an edge server. Feature selection with machine learning is helpful for estimating data importance. To improve the estimation accuracy, the proposed scheme complements missing entries when performing feature selection. We developed an indoor experimental environment and found that the prediction accuracy was sufficiently maintained compared to two benchmark schemes, random and heuristic, with limited communication bandwidth. Comparison with the perturbation method, which is a conventional method of feature selection, demonstrated the effectiveness to complement missing values in the proposed scheme.

Advocating for Greater Inclusion of Marginalized and Forgotten Populations in COVID19 Vaccine Rollouts.

Objectives: Many countries recently approved a number of SARS-CoV-2 vaccines. There is therefore growing optimism around the world about their future availability and effectiveness. However, supplies are likely to be limited and restricted to certain categories of individuals, at least initially. Thus, governments have suggested prioritization schemes to allocate such limited supplies. The majority of such schemes are said to be developed to safeguard the weakest sections of society; that is, healthcare personnel and the elderly. Methods: In this work, we analyse three case studies (incarcerated people; homeless people, asylum seekers and undocumented migrants). We propose a bioethical argument that frames the discussion by describing the salient facts about each of the three populations and then argue that these characteristics entail inclusion and prioritization in the queue for vaccination in their country of residence. Results: Through an analysis informed by ethical considerations revolving around the concepts of fairness and equality, we try to raise awareness of these important issues among decision makers. Conclusion: Our goal is to advocate for the development of more inclusive policies and frameworks in SARS-CoV-2 vaccine allocation and, in general, in all scenarios in which there is a shortage of optimal care and treatments.

Protected-area targets could be undermined by climate change-driven shifts in ecoregions and biomes

Expanding the global protected area network is critical for addressing biodiversity declines and the climate crisis. However, how climate change will affect ecosystem representation within the protected area network remains unclear. Here we use spatial climate analogs to examine potential climate-driven shifts in terrestrial ecoregions and biomes under a +2 °C warming scenario and associated implications for achieving 30% area-based protection targets. We find that roughly half of land area will experience climate conditions that correspond with different ecoregions and nearly a quarter will experience climates from a different biome. Of the area projected to remain climatically stable, 46% is currently intact (low human modification). The area required to achieve protection targets in 87% of ecoregions exceeds the area that is intact, not protected, and projected to remain climatically stable within those ecoregions. Therefore, we propose that prioritization schemes will need to explicitly consider climate-driven changes in patterns of biodiversity.

Invasive alien plants in plant health revisited: another 10 years

AbstractTen years ago, the authors gave an overview of the early history of invasive alien plants in plant health. In the last decade, the field has seen further development, which is reported here. This includes new activities at the global scale, e.g. in the International Plant Protection Convention and the Convention on Biological Diversity, on a regional scale, e.g. in the EU and the region of the European and Mediterranean Plant Protection Organization, and on a national scale. New activities include a prioritization scheme for the pest risk analysis of invasive alien plants, new Standards and regulations, and a further development of the cooperation between the environmental and plant health sectors.

Interspecific Sample Prioritization Can Improve QTL Detection With Tree-Based Predictive Models.

Due to increasing demand for new advanced crops, considerable efforts have been made to explore the improvement of stress and disease resistance cultivar traits through the study of wild crops. When both wild and interspecific hybrid materials are available, a common approach has been to study two types of materials separately and simply compare the quantitative trait locus (QTL) regions. However, combining the two types of materials can potentially create a more efficient method of finding predictive QTLs. In this simulation study, we focused on scenarios involving causal marker expression suppressed by trans-regulatory mechanisms, where the otherwise easily lost associated signals benefit the most from combining the two types of data. A probabilistic sampling approach was used to prioritize consistent genotypic phenotypic patterns across both types of data sets. We chose random forest and gradient boosting to apply the prioritization scheme and found that both facilitated the investigation of predictive causal markers in most of the biological scenarios simulated.

Target properties optimization on capacitive-type humidity sensor: Ingredients hybrid and integrated passive devices fabrication

Optimized hygroscopic film preparation and high-precision manufacturing guarantee the humidity sensor expected properties on sensitivity, hysteresis, response/recovery speed, reliability, etc. This paper demonstrated a comprehensive prioritization scheme on the premise of industrial production. Raw materials mixtures such as pyromellitic dianhydride (PMDA)/p-phenylenediamine (p-PDA), and PMDA/oxydianiline (ODA) were investigated to solve the issue of film surface collapse. Polyacrylonitrile (PAN) is adopted as an additive to enhance the film reliability (maximum of 0.15 % measurement error rate in 120 h continuous testing) as well as assistance in the film coating process. Rutile TiO2 with the average particle size of 0.33 μm was employed as doping elements to reduce the hysteresis to 0.95 % relative humidity (RH), increase the sensitivity to 0.94 pF/% RH, and limit the response/recovery time within 40 s. The film-growth quality and the consistency of production performance were assured by the integrated-passive-device (IPD) fabrication process.

Why we should not ‘just use age’ for COVID-19 vaccine prioritisation

Older age is one of the greatest risk factors for severe outcomes from COVID-19. If we believe it is important to use limited supplies of COVID-19 vaccines to protect the...

Aesthetic Interleaving of Character Performance Requests

We have constructed a system that supports unscripted social interaction between a player and virtual characters, where the participants pursue internal agendas and respond to one another in real-time. Our emphasis on unscripted interaction means that the characters must accept dynamically generated performance requests, while our concern with social interaction implies that the characters must interleave performances with an attention to natural flow that encourages social engagement. We present initial work on a performance management mechanism that produces this interleaving. It initiates and suspends character performances by allocating animation resources to requests via a utility function representing aesthetic concerns. That function weighs extrinsic factors reflecting the purpose of taking an action against intrinsic ones that concern features of a given performance. We show, via multiple short videos, that the features are individually material to the aesthetic quality of the result and that the mechanism can produce aesthetically pleasing performances on par with the best hand-generated prioritization scheme. We argue, anecdotally, that the parameters of the model are easy to identify, suggesting that the feature vocabulary is both intuitive and useful for shaping character performances.

Multifactor Algorithm for Test Case Selection and Ordering

Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls short. The current research is motivated by this concept and proposes a multifactor algorithm incorporated with genetic operators and powerful features. A factor-based prioritizer is introduced for proper handling of tied test cases that emerged while implementing re-ordering. Besides this, a Cost-based Fine Tuner (CFT) is embedded in the study to reveal the stable test cases for processing. The effectiveness of the outcome procured through the proposed minimization approach is anatomized and compared with a specific heuristic method (rule-based) and standard genetic methodology. Intra-validation for the result achieved from the reduction procedure is performed graphically. This study contrasts randomly generated sequences with procured re-ordered test sequence for over '10' benchmark codes for the proposed prioritization scheme. Experimental analysis divulged that the proposed system significantly managed to achieve a reduction of 35-40% in testing effort by identifying and executing stable and coverage efficacious test cases at an earlier phase.

Ang Isyu ng Katarungan sa Panahon ng Pandemya

Given the usually limited supply of resources needed to meet our healthcare needs during a pandemic, coming up with a fair system of prioritization by which such resources are to be distributed is both extremely urgent and morally obligatory. In the area of political morality, the issue of what counts as a fair allocation of resources, which may generally come in the form of being benefits or burdens, is referred to as the issue of distributive justice. In this essay, I look into the issue of distributive justice in the context of the current COVID-19 pandemic. After examining the basic claims of the various theories of distributive justice and how they apply to healthcare resource allocations, I then advance a framework for evaluating the moral justifiability of prioritization schemes for a fair allocation of healthcare resources, especially the vaccines, during the pandemic. The framework basically incorporates moral considerations based on welfare, capabilities, and opportunities. © 2021. Napoleon M. Mabaquiao, Jr.

Prioritization of Vulnerable Species Under Scenarios of Anthropogenic-Driven Change in Georgia's Coastal Plain

Abstract Effective management of wildlife populations benefits from an understanding of the long-term vulnerability of species to anthropogenic stressors. Exposure to potential habitat change is one measure of vulnerability that wildlife managers often use to assess and prioritize individual species or groups of species for resource allocation or direct management actions. We used species distribution models for 15 species occurring in the coastal plain ecoregion of Georgia to estimate the current amount and distribution of potential habitat and then predict exposure to changes in habitat due to inundation from sea level rise (using the Sea Level Affecting Marshes model) and urban growth (using the Slope Land-use Excluded Urban Topology Hillshade Growth model) for four future time points. Our results predict that all focal species were likely to experience some exposure to habitat change from either sea level rise or urbanization, but few species will experience high exposure to change from both stressors. Species that use salt marsh or beach habitats had the highest predicted exposure from sea level rise (25–69%), while species that use more inland habitats had the highest predicted exposure to urban growth (10–20%). Our models are a resource for managers considering tradeoffs between prioritization schemes under two future stressors. Results suggest that managers may need to prioritize species (or their habitats) based on the predicted magnitude of habitat loss, while also contextualizing prioritization with respect to the current amount of available protected habitat and species global vulnerability.

Population-based serology reveals risk factors for RSV infection in children younger than 5\xa0years

Respiratory syncytial virus (RSV) infection is a leading cause of hospitalization in infants. Underlying risk factors for RSV infection in the general population are not well understood, as previous work has focused on severe outcomes of infection in a clinical setting. Here we use RSV-specific IgG and IgA antibody measurements from two population-based cross-sectional serosurveys carried out in the Netherlands (n = 682) to classify children up to 5 years as seronegative or seropositive. We employ a generalized additive model to estimate the probability of prior RSV infection as function of age, date of birth within the year, and other risk factors. The analyses show that the majority of children have experienced a RSV infection before the age of 2 years. Age and birthdate are strong predictors of RSV infection in the first years of life, and children born in summer have higher estimated probability of infection than those born in winter [e.g., 0.56 (95% CI 0.45–0.66) vs. 0.32 (0.21–0.45) at age 1 year]. Our analyses reveal that the mean age at infection depends on date of birth, which has implications for the design of vaccination programmes and prioritisation schemes for the prophylactic use of monoclonal antibodies.

Prioritizing Conservation of Coastal Ponds for Wintering Redheads

ABSTRACTThe Laguna Madres of Texas, USA, and Tamaulipas, Mexico, are the most important wintering areas for redheads (Aythya americana) as most of the continental population winters in these lagoons. Redheads forage in the saline waters of the Laguna Madre and make daily flights to coastal freshwater ponds on the adjacent mainland to drink. The abundance and spatial distribution of coastal ponds varies depending on precipitation and can influence the foraging pressure on adjacent seagrass meadows. We conducted weekly aerial surveys to monitor coastal pond use by wintering redheads from mid‐October through mid‐March along the entire length of the Laguna Madre of Texas, during 2000–2003 and in 2012–2014. We developed 3 parameters to provide a measure of biological value of each coastal pond to redheads: amount of foraging habitat within 10 km of each pond, water permanence of the pond, and the potential to distribute redheads if inundated. During 101 aerial surveys across 5 years of study, we identified 140 coastal ponds that were used by redheads. We developed a prioritization scheme to identify wetlands that remain inundated in all years and targeted them for conservation protection. We identified those coastal ponds that, if enhanced through increasing their water permanence, would provide additional drinking sites during dry years and help distribute redheads on more foraging habitat, thereby reducing potential overgrazing on seagrass meadows. We identified 3,624 ha of foraging habitat (21.5% of all foraging habitat) in the lower Laguna Madre that had no coastal ponds within a 10‐km radius and, thus, was proximal to potential areas for coastal pond creation. Our results provide guidance for resource managers to protect, enhance, or create coastal ponds to reduce foraging pressure on seagrass meadows in the Laguna Madre and help sustain future populations of wintering redheads. © 2021 The Wildlife Society.

Emerging Organic Contaminants in Chinese Surface Water: Identification of Priority Pollutants

• Prioritizing 405 EOCs by exposure and hazard potential in Chinese surface water. • Hazard potentials were defined using persistence, bioaccumulation, and toxicity. • Potential risk to human health or ecological effects was identified for 96 EOCs. • The top- and high-priority categories included 11 and 37 compounds, respectively. • Environmental quality standards were recommended for 20 EOCs. The occurrence and impacts of emerging organic contaminants (EOCs) in the aquatic environment have gained widespread attention over the past two decades. Due to large number of potential contaminants, monitoring campaigns, treatment plants, and proposed regulations should preferentially focus on specific pollutants with the highest potential for ecological and human health effects. In the present study, a multi-criteria screening approach based on hazard and exposure potentials was developed for prioritization of 405 unregulated EOCs already present in Chinese surface water. Hazard potential, exposure potential, and risk quotients for ecological and human health effects were quantitatively analyzed and used to screen contaminants. The hazard potential was defined by contaminant persistence, bioaccumulation, ecotoxicity, and human health effects; similarly, the exposure potential was a function of contaminant concentration and detection frequency. In total, 123 compounds passed the preselection process, which involved a priority index equal to the normalized hazard potential multiplied by the normalized exposure potential. Based on the prioritization scheme, 11 compounds were identified as top-priority, and 37 chemicals were defined as high-priority. The results obtained by the priority index were compared with four other prioritization schemes based on exposure potential, hazard potential, or risk quotients for ecological effects or human health. The priority index effectively captured and integrated the results from the more simplistic prioritization schemes. Based on identified data gaps, four uncertainty categories were classified to recommend: ① regular monitoring, derivation of environmental quality standards, and development of control strategies; ② increased monitoring; ③ fortified hazard assessment; and ④ increased efforts to collect occurrence and toxicity data. Overall, 20 pollutants were recommended as priority EOCs. The prioritized list of contaminants provides the necessary information for authoritative regulations to monitor, control, evaluate, and manage the risks of environmentally-relevant EOCs in Chinese surface water.