Modeling comorbidity of chronic diseases using coupled hidden Markov model with bivariate discrete copula.

A range of chronic diseases have a significant influence on each other and share common risk factors. Comorbidity, which shows the existence of two or more diseases interacting or triggering each other, is an important measure for actuarial valuations. The main proposal of the study is to model parallel interacting processes describing two or more chronic diseases by a combination of hidden Markov theory and copula function. This study introduces a coupled hidden Markov model with the bivariate discrete copula function in the hidden process. To estimate the parameters of the model and deal with the numerical intractability of the log-likelihood, we use a variational expectation maximization algorithm. To perform the variational expectation maximization algorithm, a lower bound of the model's log-likelihood is defined, and estimators of the parameters are computed in the M-part. A possible numerical underflow occurring in the computation of forward-backward probabilities is solved. The simulation study is conducted for two different levels of association to assess the performance of the proposed model, resulting in satisfactory findings. The proposed model was applied to hospital appointment data from a private hospital. The model defines the dependency structure of unobserved disease data and its dynamics. The application results demonstrate that the model is useful for investigating disease comorbidity when only population dynamics over time and no clinical data are available.

CD-vine model for capturing complex dependence.

Copula based finite mixture models allow us to capture the dependence between random variables more flexibly. Although bivariate case of finite mixture models has been commonly studied, limited efforts have been spent on finite mixture of vines. Instead of using classical mixture models, it is possible to incorporate C-vines into the D-vine model (CD-vine) to understand both the dependence among the variables over different time points. The aim of this study is to create a CD-vine mixture model expressing the dependencies between variables in temporal order. To achieve this, cumulative distribution function values generated within the time components are tied together with D-vine probabilistically. With this approach, dependence structure between variables at each time point is explained by C-vine and the dependence among the time points is captured by the D-vine model. The performance of the proposed CD-vine model is validated using simulated data and applied on four stock market indices.

Mutual information model selection algorithm for time series.

Time series model selection has been widely studied in recent years. It is of importance to select the best model among candidate models proposed for a series in terms of explaining the procedure that governs the series and providing the most accurate forecast for the future observations. In this study, it is aimed to create an algorithm for order selection in Box-Jenkins models that combines penalized natural logarithm of mutual information among the original series and predictions coming from each candidate. The penalization is achieved by subtracting the number of parameters in each candidate and empirical information the data provide.Simulation studies under various scenarios and applications on real data sets imply that our algorithm offers a promising and satisfactory alternative to its counterparts.

An analysis of the incidence of measles in Turkey since 1960.

BACKGROUND/AIM: The aims of this study were to evaluate measles incidence and the effect of elimination strategy interventions on the disease from 1960 to 2014 in Turkey. The administration of measles vaccine started in the rural regions in 1970; it was carried out as a campaign along with the National Vaccine Campaign in 1985, and it has been employed as combined measles, mumps, and rubella under the scope of the Measles Elimination Program (MEP) since 2006 in Turkey. While a dramatic decrease in the reporting of measles was observed between 2000 and 2010, the number of the cases has increased since 2011. MATERIALS AND METHODS: The time series of measles incidence was evaluated for possible structural changes with regression models using dummy variables, autocorrelated with error terms. RESULTS: The incidence of measles showed a statistically significant decline between 1985 and 1988 (P = 0.0072) and between 2005 and 2011 (P < 0.0001). However, a statistically significant increase in incidence was noted after 2013 (P = 0.0008). CONCLUSION: Over the last 54 years, the pattern of measles cases demonstrated a significant decline in incidence. However, the increase in incidence in 2013 should be carefully analyzed and interpreted in terms of the MEP.

Impact of alternating wet and dry periods on long-term seasonal phosphorus and nitrogen budgets of two shallow Mediterranean lakes.

The water balance, with large seasonal and annual water level fluctuations, has a critical influence on the nitrogen and phosphorus dynamics of shallow lakes in the semi-arid climate zone. We constructed seasonal water and nutrient budgets for two connected shallow lakes, Lakes Mogan and Eymir, located in Central Anatolia, Turkey. The study period covered 20years with alternations between dry and wet years as well as restoration efforts including sewage effluent diversion and biomanipulations in Lake Eymir. Both lakes experienced a 1-2m water level drop during a drought period and a subsequent increase during the wet period, with seasonal water level fluctuations of 0.60 to 0.70m. During wet years with high water levels, small seasonal differences were observed with a nutrient peak in spring caused by external loading and nutrient loss via retention during summer. During years with low water levels, nutrient concentrations increased due to internal and external loading, exacerbated by evaporative water loss. In Lake Eymir, a shift to eutrophic conditions with turbid water occurred under low water level conditions and consequent internal loading of P from the sediment, causing high nutrient concentrations in summer. Our results indicate a threat of lakes drying out in the semi-arid climate zone if evaporation increases and precipitation decreases as anticipated from the global climate change predictions. In addition, our results show the influence of the water balance on the eutrophication of shallow lakes in the Mediterranean climate zone and highlight the ultimate consequences for lake management.

Psychological well-being, health, and stress sources in Turkish dental students.

This study investigated the psychological well-being and overall health of a group of Turkish dental students and their sources of stress. Two hundred and seventy-seven students (57 percent female) from Gazi University Dental Faculty completed the Dental Environment Stress (DES) questionnaire, the Psychological General Well-Being (PGWB) index, and the SF-36 Health Survey. The results showed that the DES scores increased over the five-year period. Pressure to perform, faculty and administration, workload, and students' perceptions of their self-efficacy were the most stress-provoking factors. Students whose first choice was dentistry experienced less stress and fewer health problems (p<0.05) than students whose first choice had not been dentistry. Psychological well-being and overall health were significantly associated with year of study. Statistically significant gender differences were observed on depressed mood and anxiety dimension scores of PGWB. Female students experienced greater stress than males, while male students had better overall health than females (p<0.01). Students who lived with their parents had lower PGWB scores (p<0.05). Age was significantly related with the DES and PGWB scores. These results found that stress among these Turkish dental students was influenced by gender, year of study, social background, and lifestyle. Based on the results of this study, recommendations can be made for changes in the dental education system in order to reduce stress among dental students especially during the last two years of study.

An analysis of the prevalence of malaria in Turkey over the last 85 years.

BACKGROUND: Affecting 106 countries, malaria is a major global burden. Though intensive antimalaria efforts in Turkey have been successful in bringing down the number of cases, historically malaria was a serious public health concern. METHODS: This paper reviews the prevalence rates of malaria in Turkey over the last 85 years (1925-2010). The time series of malaria prevalence was evaluated for possible structural changes by using Chow breakpoint tests and regression models using dummy variables, with autocorrelated errors and generalized autoregressive conditional heteroscedasticity models to assess the impact of volatility in prevalence. RESULTS: Seventy-eight cases of malaria were diagnosed in Turkey in 2010. Malaria prevalence rates in the country show a statistically significant volatility, which underlines the fragility of efforts to control the disease. CONCLUSIONS: It is necessary to analyse the national malaria control programme to evaluate to what extent its programmatic capacity, financial resources, and political commitment are sufficient to avoid eroding the gains that have already been made and, ultimately, eradicate malaria. It is essential that there should be no lessening in the long-standing efforts to reduce malaria.