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Background:Regarding cases of infectious diseases tuberculosis (TB) is the most important cause of death and according to the DALY criteria, this disease has the seventh position in global disease ranking. In this study, we aim to determine the risk factors, which have a significant effect on the treatment completion and mortality of TB patients.Methods:This study is a retrospective cohort study. The sample is made up of registered TB patients in the Isfahan Province from 2006 to 2011. Information of the patients was collected from their files in health centers in the Isfahan Province. Variables such as age, sex, weight, nationality, residence, type of TB, imprisonment, human immunodeficiency virus, TB case were measured. Descriptive statistics (including frequency, percentage, mean and standard deviation) and statistical analysis (including Cox proportional hazard model) were used.Results:The result showed that imprisonment (hazard ratio [HR] = 4.76, P = 0.019), age (HR = 4.44, P = 0.001) and the TB case (HR = 2.73, P = 0.037) of pulmonary TB had significant impacts on mortality of the patients, also in the case of treatment completion, the TB case (HR = 0.34, P < 0.001) proved to have a significant impact on completion of the treatment. Type of extra-pulmonary TB in extra-pulmonary TB patients also had an effect on treatment completion.Conclusions:We can conclude that factors such as age, imprisonment, TB case and type of extra-pulmonary TB are effective on the treatment completion and mortality of the patients. It may be useful for policy makers to make more control of high-risk patients.

Background:Diagnosis and typing of Mycobacterium genus provides basic tools for investigating the epidemiology and pathogenesis of this group of bacteria. Polymerase chain reaction (PCR)-restriction fragment length polymorphism analysis (PRA) is an accurate method providing diagnosis and typing of species of mycobacteria. The present study is conducted by the purpose of determining restriction fragment profiles of common types of mycobacteria by PRA method of rpoB gene in this geographical region.Materials and Methods:Totally 60 clinical and environmental isolates from February to October, 2013 were collected and subcultured and identified by phenotypic methods. A 360 bp fragment of the rpoB gene amplified by PCR and products were digested by MspI and HaeIII enzymes.Results:In the present study, of all mycobacteria isolates identified by PRA method, 13 isolates (21.66%) were Mycobacterium tuberculosis, 34 isolates (56.66%) were rapidly growing Nontuberculosis Mycobacteria (NTM) that including 26 clinical isolates (43.33%) and 8 environmental isolates (13.33%), 11 isolates (18.33%) were clinical slowly growing NTM. among the clinical NTM isolates, Mycobacterium fortuitum Type I with the frequency of 57.77% was the most prevalent type isolates. Furthermore, an unrecorded of the PRA pattern of Mycobacterium conceptionense (HeaIII: 120/90/80, MspI: 120/105/80) was found. This study demonstrated that the PRA method was high discriminatory power for identification and typing of mycobacteria species and was able to identify 96.6% of all isolates.Conclusion:Based on the result of this study, rpoB gene could be a potentially useful tool for identification and investigation of molecular epidemiology of mycobacterial species.

Nowadays, sustainable supply chain (SSC) selection of aviation fuels is one of the hot topics around world aviation industries. Existing of diverse intuitive and interrelated criteria that should be considered during the decision-making process turned it into one of the complex decision-making problems. Also, there exists tremendous uncertainty around all parameters and alternatives in the problem. The q-Rung Orthopair Fuzzy Sets (q-ROFSs), which is a generalization of Intuitionistic Fuzzy Sets (IFSs), provide a more proper space for decision-makers. q-ROFSs capable of expressing uncertain information with more flexibility. In this article it is tried to show the reliability of applying the analytical hierarchy process (AHP) in q-ROFSs environment for SSC of aviation fuel. First, properties of q-ROFSs are evaluated then the AHP method is discussed in detail based on q-ROFSs. Afterward, by considering the hardness of the SSC in aviation fuel problem, it is proposed a MAGDM method based on AHP in q-ROFSs environment. Finally, an application of AHP based on q-ROFSs to solve the SSC of the aviation fuel problem is presented to test the effectiveness of the proposed method.

By outbreaking COVID-19, the sanitarium site selection for coronavirus patients turned into a hot topic. In this article, it is tried to help managers to come up with the hardness of such a complex problem. The quarantine procedure of COVID-19 patients is an essential factor which is suggested by the World Health Organization (WHO) for preventing the outbreak. The numerous significant criteria together with many alternatives that could be selected in the real-world cases increase the uncertainty of the problem. So, a hybrid multi-criteria group decision making (MCGDM) process based on outranking methods is applied to make use of the advantages of those methods. In the decision process, the ELECTRE and VIKOR methods are integrated in the q-rung orhtopair fuzzy sets (q-ROFSs) environment is introduced. As a preliminary part the properties of the q-ROFSs are discussed in detail, and then the ELECTRE and VIKOR methods are investigated. Then the integrated ELECTRE-VIKOR method in a MCGDM algorithm is proposed. To show the effectiveness and validity of the proposed method, a case study of sanitarium site selection in Iran is conducted, and results are evaluated in detail.