Analysis of cost of various topical and oral antifungal drugs for superficial fungal infections available in India

Background: In tropical countries like India, superficial fungal infections are quite common and certain infections like tinea is rampantly spreading in epidemic proportions and frequent relapses after treatment have increased the need for long term therapy significantly increasing the cost of treatment, so the treatment of fungal infection can raise economic burden on the patient. The aim of the study was to analyze the cost variation of topical antifungal drugs and oral antifungal drugs of various brands for superficial fungal infection available in India.Methods: Cost in Indian Rupees (INR) of antifungal agents manufactured by different pharmaceutical companies in India was collected from the Current index of medical specialities (CIMS) October to December 2019. Minimum cost, maximum cost, cost ratio, cost variation was calculated.Results: In oral dosage form, fluconazole, Itraconazole show the maximum cost variation. In topical single drug therapy luliconazole, terbinafine show maximum cost variation.Conclusions: There is wide cost variation among antifungal agents available in Indian Market. There is need of strict actions for cost policy regulation and sensitization of doctor for selection of appropriate brand drugs.

The impact of blood transcriptomic biomarker targeted tuberculosis preventive therapy in people living with HIV: a mathematical modelling study

Background Tuberculosis (TB) preventive therapy is recommended for all people living with HIV (PLHIV). Despite the elevated risk of TB amongst PLHIV, most of those eligible for preventive therapy would never develop TB. Tests which can identify individuals at greatest risk of disease would allow more efficient targeting of preventive therapy. Methods We used mathematical modelling to estimate the potential impact of using a blood transcriptomic biomarker (RISK11) to target preventive therapy amongst PLHIV. We compared universal treatment to RISK11 targeted treatment and explored the effect of repeat screening of the population with RISK11. Results Annual RISK11 screening, with preventive therapy provided to those testing positive, could avert 26% (95% CI 13–34) more cases over 10 years compared to one round of universal treatment. For the cost per case averted to be lower than universal treatment, the maximum cost of the RISK11 test was approximately 10% of the cost of preventive therapy. The benefit of RISK11 screening may be greatest amongst PLHIV on ART (compared to ART naïve individuals) due to the increased specificity of the test in this group. Conclusions Biomarker targeted preventive therapy may be more effective than universal treatment amongst PLHIV in high incidence settings but would require repeat screening.

Designing the Maximum Permissible Production Cost of Oil and Gas Project Using Control Chart Analysis

During the period of 2005 to 2020, the oil prices reached the highest level in 2008 (99.67 US$/bbl) and the lowest level in 2020 (39.16 US$/bbl). The fluctuation in oil prices will affect the expenditures for both investment and production in oil and gas projects. Based on this condition, the standardization of the costs of investment and production is needed to help the government and contractor in estimating the costs needed in an oil and gas project. As of December 2018, 471 projects (POD) have been approved by the government of Indonesia. All of them are projects that produce oil (oil projects) and gas (gas projects). In these projects, details of operating (Production) costs are included in the economic evaluation. For the purpose of this paper, Indonesia was divided into 2 areas (Onshore and Offshore). Each of the areas had 2 different types of projects (oil project and gas project). Then, to collect the data related to the cost of production and reserves, the maximum cost of production per BOE was calculated and produced using the Control Chart Analysis method. Lastly, the result was distributed to those aforementioned areas. Based on the evaluation and analysis of the cost of production from 273 oil and gas projects in Indonesia, oil and gas projects in Indonesia are economically acceptable as the maximum cost of production (US$ per BOE) is still far below the oil price (~65 US$/BBL). The following is the estimated Maximum Cost of Production generated in Indonesia: Onshore – Oil Projects (28.00 US$/BOE), Onshore - Gas Projects (12.27 US$/BOE), Offshore - Oil Projects (21.20 US$/BOE), Offshore - Gas Projects (15.95 US$/BOE). Finally, this paper will show how to produce the maximum cost of productions per BOE using control chart analysis. This paper is expected to provide references (method) for the government of Indonesia in giving approval to the cost of production proposed by contractors. In addition, this paper may provide contractors with a quick look at oil and gas industry in Indonesia, especially those who plan to invest in Indonesia. It may also help them create their petroleum exploration and exploitation strategy in Indonesia if they take this information into consideration, which will benefit both the government and contractors.

Scheduling computations with provably low synchronization overheads

We present a Work Stealing scheduling algorithm that provably avoids most synchronization overheads by keeping processors’ deques entirely private by default and only exposing work when requested by thieves. This is the first paper that obtains bounds on the synchronization overheads that are (essentially) independent of the total amount of work, thus corresponding to a great improvement, in both algorithm design and theory, over state-of-the-art Work Stealing algorithms. Consider any computation with work T1 and critical-path length T1 executed by P processors using our scheduler. Our analysis shows that the expected execution time is O T1 P + T1 , and the expected synchronization overheads incurred during the execution are at most O ((CCAS + CMF ence) P T1), where CCAS and CMF ence respectively denote the maximum cost of executing a Compare-And-Swap instruction and a Memory Fence instruction.

Utility-Scale PV-Battery versus CSP-Thermal Storage in Morocco: Storage and Cost Effect under Penetration Scenarios

In this study, we examine how Battery Storage (BES) and Thermal Storage (TES) combined with solar Photovoltaic (PV) and Concentrated Solar Power (CSP) technologies with an increased storage duration and rental cost together with diversification would influence the Moroccan mix and to what extent the variability (i.e., adequacy risk) can be reduced; this is done using recent (2013) cost data and under various penetration scenarios. To do this, we use MERRA-2 climate reanalysis to simulate hourly demand and capacity factors (CFs) of wind, solar PV and CSP without and with increasing storage capabilities—as defined by the CSP Solar Multiple (SM) and PV Inverter Loading Ratio (ILR). We adjust these time series to observations for the four Moroccan electrical zones over the year 2018. Our objective is to maximize the renewable (RE) penetration and minimize the imbalances between RE production and consumption considering three optimization strategies. We analyze mixes along Pareto fronts using the Mean-Variance Portfolio approach—implemented in the E4CLIM model—in which we add a maximum-cost constraint to take into account the different rental costs of wind, PV and CSP. We propose a method to calculate the rental cost of storage and production technologies taking into account the constraints on storage associated with the increase of SM and ILR in the added PV-BES and CSP-TES modules, keeping the mean solar CFs fixed. We perform some load bands-reduction diagnostics to assess the reliability benefits provided by each RE technology. We find that, at low penetrations, the maximum-cost budget is not reached because a small capacity is needed. The higher the ILR for PV, the larger the share of PV in the mix compared to wind and CSP without storage is removed completely. Between PV-BES and CSP-TES, the latter is preferred as it has larger storage capacity and thus stronger impact in reducing the adequacy risk. As additional BES are installed, more than TES, PV-BES is favored. At high penetrations, optimal mixes are impacted by cost, the more so as CSP (resp., PV) with high SM (resp., ILR) are installed. Wind is preferably installed due to its high mean CF compared to cost, followed by either PV-BES or CSP/CSP-TES. Scenarios without or with medium storage capacity favor CSP/CSP-TES, while high storage duration scenarios are dominated by low-cost PV-BES. However, scenarios ignoring the storage cost and constraints provide more weight to PV-BES whatever the penetration level. We also show that significant reduction of RE variability can only be achieved through geographical diversification. Technological complementarity may only help to reduce the variance when PV and CSP are both installed without or with a small amount of storage. However, the diversification effect is slightly smaller when the SM and ILR are increased and the covariances are reduced as well since mixes become less diversified.

Nash Welfare in the Facility Location Problem

In most facility location research, either an efficient facility placement which minimizes the total cost or a fairer placement which minimizes the maximum cost are typically proposed. To find a solution that is both fair and efficient, we propose converting the agent costs to utilities and placing the facility/ies such that the product of utilities, also known as the Nash welfare, is maximized. We ask whether the Nash welfare's well-studied balance between fairness and efficiency also applies to the facility location setting, and what agent strategic behaviour may occur under this facility placement.

Exploration of Maximum-to-Minimum Shifts in Generic Methods for Departure Time Choice Models

Vickrey’s seminal departure time choice model is based on a penalty function which is a linear combination of travel time, earliness, and lateness. The original model depicts a single link from a single origin to a single destination, serving homogeneous travelers by a deterministic point-queue regime. Numerous variants of the basic model, relaxing one or more of these assumptions, have been used in a wide range of contexts. The equilibrium solution of the basic model can be computed directly by exact formula. Specific convergent methods have been proposed for certain variants. One of the troubling challenges in this model is the need for a generic iterative numeric approach, that may address complex models in which departure time choice is embedded. Natural candidates were shown to fail even on the basic model. In this paper we explore a fairly naive approach, where, in each iteration, demand is shifted from the maximum cost time interval to the minimum cost time interval. Results for the basic model are promising, demonstrating that, with a fixed shift, solutions converge to a deviation which is proportional to the shift size and that semi-adaptive or adaptive shift size may offer convergence to any desirable level of approximation of the exact equilibrium.

Cost of Personal Protective Equipment During the First Wave of COVID-19

Background: As the world prepared for and responded to the COVID-19 pandemic in early 2020, a rapid increase in demand for personal protective equipment (PPE) led to severe shortages worldwide. Acquisition of PPE in the general market was an integral part of pandemic response, along with the safeguarding of hospital supplies. We seek to quantify the difference in cost per unit (CPU) of PPE during the first wave of COVID-19 compared to prepandemic prices. Methods: We performed a retrospective review of market prices for PPE during the first surge of the pandemic in Chicago. Cost of PPE was tabulated and compared with prepandemic prices. The maximum cost per unit (CPU) of PPE was tabulated for each week, and the average cost throughout the pandemic was calculated. Disposable gowns, washable gowns, N95 respirators, face masks, and gloves were included in our analysis. Results: PPE prices were significantly higher during the pandemic compared to prepandemic prices (Figure 1). Disposable gown CPU peaked at $12 during the first week of March, 13.7 times higher than prepandemic prices, and the average gown CPU was 7.5 times higher than prepandemic prices. N95 respirators had a peak CPU of $12, and average CPU was 8 times higher than prepandemic prices. Face-mask CPU peaked at $0.55, 11 times higher, and averaged 9 times higher the regular price. Gloves averaged 2.5 times higher than the prepandemic CPU. Conclusions: Market prices for PPE were significantly elevated during the first weeks of the pandemic and remained high throughout the first wave of COVID-19. Multiple factors likely contributed to high prices, including demand shock, disrupted supply chains, and a rush to acquisition by healthcare systems and the general population alike. The impact of COVID-19 on prices highlights the importance of supply chains and national stockpiles for pandemic preparedness.Funding: NoDisclosures: None