Comparative Costs of Different Renal Replacement Therapies in Lower Middle Income Countries on the Example of Georgia

End-Stage Renal Disease (ESRD) represents one of the most challenging social and medical problems mainly due to substantial treatment-associated costs. The chronic nature of the disease needs expensive continuous care that majority of the patients cannot afford. Therefore, in many countries expenses associated with the ESRD treatment is paid by state government. These treatment options include: hemodialysis, peritoneal dialysis and kidney transplantation. Multiple studies have been conducted throughout the world to assess cost-effectiveness of these treatment modalities. The studies suggest that kidney transplantation not only reduces mortality and morbidity but improves a quality of life of ESRD patients. Furthermore, it is the most cost-effective treatment for the ESRD at least in high-income countries. The goal of our study was to determine whether above-mentioned is true for lower middle income countries, where the cost of the ESRD treatment is substantially lower. Despite the low dialysis costs, transplantation remains the cheapest form of renal replacement therapy RRT in lower income countries like Georgia. Our results reveal, that kidney transplantation is most expensive modality of Renal Replacement Therapy (RRT) at month 1, but count of costs reveals that after the 10th month of treatment, the cumulative cost of transplantation is less than the cumulative cost of peritoneal dialysis and after the 23rd month, cumulative cost of hemodialysis also surpasses the cumulative cost of transplantation-related treatment and this cost comparison is in line with global data from upper-middle and high income countries.

A review of refinery complexity applications

Refinery complexity quantifies the sophistication and capital intensity of a refinery and has found widespread application in facility classification, cost estimation, sales price models, and other uses. Despite the ubiquity and widespread use of refining complexity, however, surprisingly little material has been written on its applications. The pur- pose of this review is to describe the primary applications of refinery complexity and some recent extensions. A secondary purpose of this review is to provide a framework that unifies complexity applications and suggests avenues for future research. Examples illustrate the applications considered.

Economic valuation of water storage function of forest ecosystems (case study: Zagros Forests, Iran)

Forest ecosystem services contribute to human welfare, both directly and indirectly. Here the economic value of water conservation by Bazoft basin located in Zagros forests in western Iran was estimated, using simulation models and Geographic Information System （GIS） as a tool for analyzing the effects of ecological factors on ecosystem services. Rainfall-runoff simulation was carried out by using Curve Number （CN） method in HEC-HMS model. The model requires the inputs of land cover, soil and short term rainfall and discharge data. The efficiency of simu-lated model was revised using observed data and doing calibration stages. The role of forest on water retention and surface runoff reduction by devising four hypothetical scenarios and then the effects of land use changes associated with these scenarios on rainfall-runoff behavior of the region were determined. The results show that under the case of scenario one which assumes that the entire of basin area is covered by forests, total outflow would be in the minimum amount and rainfall initial loss will increase. Forest hydrological services related to water retention was economically assessed using Replacement Cost Method. Valuation results show that each hectare of Bazoft forests can store 84.8 m3 water with 0.5 US$/m3 annual value. So the water retention value of each hectare of these forests will be 43US$. This could have positive economic consequences for the region and would help decision-makers in selecting appropriate and economically feasible development strategies.

THE OPTIMAL REPLACEMENT FOR ADDITIVE DAMAGE MODELS IN DISCRETE SETTING

A system receives shocks at successive random points of discrete time, and each shock causes a positive integer-valued random amount of damage which accumulates on the system one after another. The system is subject to failure and it fails once the total cumulative damage level first exceeds a fixed threshold. Upon failure the system must be replaced by a new and identical one and a cost is incurred. If the system is replaced before failure, a lower cost is incurred.On the basis of some assumptions, we specify a replacement rule which minimizes the longrun (expected) average cost per unit time and possesses the control limit property, Finally, an algorithm is discussed in a special case.