A statistical analysis and inter-comparison of the broadband ultraviolet-A (UVA) radiation at two sites in Cyprus representing two different climate regimes of the island (Athalassa-inland plain vs Larnaca-coastal location) covering the period January 2013-December 2015 is presented. Mean annual and mean monthly daily totals of the UVA irradiation and their frequency distribution at both sites are computed and discussed. Daily maximum of hourly average irradiance values occur in July, 58W m-2 and minimum, 22 W m-2, in December at solar noon at Athalassa. The respective values at Larnaca are slightly higher (68 W m-2 and 28 W m-2, respectively). UVA daily values follow the pattern of the solar altitude angle; the total accumulated UVA irradiation along a mean year reaches 385.8 MJ m-2 at Athalassa and 476.5 MJ m-2; maximum stability of UVA takes place at midday hours and during the summer. Large fluctuations of the daily UVA irradiation are observed in the winter and spring months, which are mainly due to unstable meteorological conditions during the transition from cold to warm weather and vice versa. During summer the daily UVA radiation exceeds the value of 1700 kJ m-2 at Athalassa and 2100 kJ m-2 at Larnaca, while during the winter season the lowest is about 250 kJ m-2 at both stations. The UVA potential and extraterrestrial irradiation have also been calculated in order to estimate the attenuation of UVA radiation through the atmosphere. The UVA transmittance, kUVA , is approximately 6 to 7% of the hemispherical transmittance for the whole spectrum (kt ). Statistical relationships between UVA and other radiation components were established using linear or power relationships.

Vector-borne diseases, such as Malaria, are major causes of human mortality in many areas of world, especially in the developing countries. Statistical and data-based models can provide an explicit framework to develop an understanding of infectious disease transmission dynamics. Application of different time series models to analyse and predict financial data as well as epidemiological data is of long interest to researchers. It is always interesting to see how the time series models that are extensively used in the analysis of financial data can be applied and extended to explain epidemiological data. In this paper, we have studied epidemiological data (malaria prevalence) related to Slide Positivity Rates and deaths due to Plasmodium vivax, using three major classes of time series models, namely Auto-Regressive Integrated Moving Average (ARIMA), Generalised Auto-Regressive Conditional Heteroskedastic (GARCH) and Random Walk. Our results show that as expected the chosen models fit excellently with the financial data but also show good potentiality to fit epidemiological data and provide excellent predictions. The results demonstrate the applicability of such time series models in epidemiology, specifically for malaria prevalence, where these models with appropriate choice of parameters have not been used extensively. As far as future prevalence pattern is concerned, the prediction of these models may help researchers and public health professionals to design control programmes for malaria.

Purpose: Adequate reliability of Body Composition (BC) assessment is a requirement before such measures can be considered valid. Many studies to date have only examined a single source of measurement error such as that from trials (test-retest). Generalizability Theory (G-theory) is a statistical technique that allows for the examination of different sources of measurement error simultaneously in a single analysis. Therefore, the aim of this study was to examine the different sources of error seen in the assessment of BC. A secondary purpose was to determine the appropriate number of facet conditions required to gain a reliable BC measure.

Methods: This measurement study included 38 participants who had been assessed on two different occasions (in the same week) and on each of four different BC field methods: Percent Body Fat (PBF) by Skinfold Technique (SF), Waist Circumference (WC), Body Mass Index (BMI) and PBF by Hand-Held Bioelectrical Impedance (HH). Two different G-theory designs were used in this research. First, a two-facet crossed p×t×m design was analyzed treating all facets as random. Then, the same design was performed treating BC method as a fixed facet. In both designs, a Generalizability Study (G-study) and Decision Study (D-study) were conducted. Three different software packages were used to ensure consistent and valid results (GENOVA, SPSS macro, and SAS GLM).

Results: The completely random design showed the largest variance component for persons (p) (57.8%). Variance components for both trials (t) and BC method (m) were negligible. However, the interaction between person and method (p×m) was substantial (38.6%). D-study results indicated reliable BC scores for measurement designs administered once using three different methods (G=.803). The mixed design, averaging over BC method, showed majority of variance due to persons (98.5%) and each of the four BC methods showed reliable scores with a single trial (G’s>.945).

Conclusion: Results from this G-theory research indicate that the equivalence reliability of commonly administered BC assessments may be inadequate. Although different BC assessments individually are reliable, for dependable BC trait generalization to the universe, a minimum of three different methods administered once may be required.