Objective: Mortality has been shown to increase with heat waves. Serbia experienced the hottest heat wave in July 2007. In this study, we examined patterns of non-traumatic excess mortality in Belgrade during this event. Methods: The numbers of deaths observed during the 9-day heat wave were compared to those expected on the basis of mortality rates reported for the previous eight years and two following years. Excess mortality was analyzed by age, gender and cause of death. Results: There was a total of 167 excess deaths (38%) between 16 and 24 July. People aged 75 years and older accounted for 151 (90%) of all excess deaths. An increase of mortality among elderly was 76% in comparison to the baseline mortality. Excess female mortality was over two times higher than excess male mortality (54% : 23%). The biggest increase in mortality was from diabetes mellitus (286%), chronic kidney disease (200%), respiratory system diseases (73%), and nervous system diseases (67%). Cardiovascular and malignant neoplasms mortality accounted for the highest absolute numbers of excess deaths (77 and 49, respectively). There was no decrease in mortality in the 60-day period after the heat wave. Conclusions: There are several causes of an increase in heat-related mortality. The most vulnerable population group is the elderly females.
One of the essential activities for sustainable local economic development is continuous improvement of business environment which can be carried out through the business-friendly certification as objective benchmarking process, which is influenced by many factors - criteria that could be analyzed using multi-criteria decision-making methods. Determining criteria weights is the most important task regarding these methods for which a number of methodologies based on different approaches were developed. These methodologies could be generally divided into two groups: subjective and objective. Shortly, these methodologies quantify given preferences using knowledge of experts if they are subjective or using calculations from available data if they are objective. Methodologies from these two groups give different results in a wide range of values. Therefore, it is useful to create composite indicators using aggregation of both approaches in order to reduce the influence of their bad individual characteristics and, therefore, achieve a balanced symmetrical approach. The purpose of this paper is constructing one efficient model that solves a problem of the planning of sustainable local economic development in the Republic of Serbia. Our approach uses the aggregation of the entropy method, as one objective approach, and the analytical hierarchy process, as a subjective approach, in executing business-friendly certification process. The implementation of the proposed approach has been demonstrated as a part of a business-to-government (B2G) platform called “Multi-Criteria Support System for Analysis of the Local Economic Environment” in the City of Niš.
Local self-government has the task of enabling stable economic development, in addition to enabling a normal quality of life for citizens. This is why the state government should provide guidelines that will improve the local business climate, and by doing so enable local economic development. This can be done through the introduction of a business-friendly certification procedure, which is influenced by uncertain inputs and influences many output factors. Each local government has the important task of determining its rank of efficiency in this process. A number of methodologies developed to solve this problem are generally divided into two groups: Parametric and non-parametric. These two groups of methodologies could provide quite different results. Therefore, the purpose of this paper was to create a model using both approaches to achieve a balanced symmetrical approach that produces better results than each approach individually. For this purpose, the paper describes a multicriteria decision aid-based model of optimization to evaluate the effectiveness of this process, integrating classification, data envelopment analysis, and stochastic frontier analysis, as well as its application in a case study of business-friendly certification in the Republic of Serbia.
One of the key problems in the application of multicriteria analysis methods is identifying the importance of the model criteria. The relevance and validity of the decisions are directly conditioned by the relevance of a given set of criteria used for evaluating alternatives, and the correct determination of the weights of these criteria. Several methodologies have been developed to calculate the importance of each criterion for a given problem. All methodologies are classified into two main groups: subjective and objective. In this paper, we present a new procedure to integrate two recognized methods for determining the weights of factors—the analytic hierarchy method as a subjective method and entropy as an objective method. We apply our methodology to a contemporary local economic problem in Serbia—the process of certifying cities and municipalities as favorable to business. We also discuss its implementation in a software tool on a local government website.
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