Generalised additive model of DIR based on region, monsoon and state in Peninsular Malaysia

A generalised additive model (GAM) framework for dengue incidence rate (DIR) as a response in Peninsular Malaysia for three areas which as region, monsoon and state has been adopted in this study. A spatio-temporal series of 1296 observations with the following explanatory variables; state, latitude and longitude of state capital, land area of state, year, month, total dengue cases, estimated state population pertaining to the year, population density of state, maximum, minimum and average monthly rainfall, maximum, minimum and average monthly temperature, monthly number of rainy days and Nino 4. Result presents three basis model with statistically significant explanatory variables consist of mean rainfall (current month and lag 3-month), mean temperature (current month and lag 1-month), number of rainy day (current month and lag 3-month), Nino 4 (lag 6-month), DIR (lag 3-month) and interaction between temperature lag 1-month and Nino 4 (lag 6-month), population, population density, year, month, monsoon area, state and region. Model 1, Model 2 and Model 3 with the lowest deviance, AIC and BIC are the best models of DIR that successfully developed for three areas mentioned

New approach to calculate the denominator for the relative risk equation

Disease frequency is used to measure the situation of the disease with reference to the population size and time period which is in a fractional form. The lower part of the fraction, known as denominator is the important part as it was used to calculate a rate or ratio. Since the disease frequency is based on a ratio estimator, the results are highly dependent upon the value of denominator. Therefore, the main aim of this paper was to propose a new method in calculating the denominator for the relative risk equation with the application to chikungunya disease data from Malaysia. The new method of calculating the denominator of the relative risk equation includes the use of discrete time-space stochastic SIR-SI (susceptible-infective-recovered for human population and susceptible-infective for vector population) disease transmission model instead of the total disease counts. The results of the analysis showed that the estimation of expected disease counts based on total posterior means can overcome the problem of expected counts estimation based on the total number of disease especially when there is no observed disease count in certain regions. The proposed new approach to calculate the denominator for the relative risk equation is suitable for the case of rare disease in which it offers a better method of expected disease counts estimation

Mapping lung cancer disease in Libya using Standardized Morbidity Ratio, BYM model and mixture model, 2006 to 2011: Bayesian Epidemiological Study

Cancer represents a significant burden on both patients and their families and their societies, especially in developing countries, including Libya. Therefore, the aim of this study was to model the geographical distribution of lung cancer incidence in Libya. The correct choice of a statistical model is a very important step to producing a good map of disease in question. Therefore, in this study will use three models to estimate the relative risk for lung cancer disease, they are initially Standardized Morbidity Ratio, which is the most common statistic used in disease mapping, BYM model, and Mixture model. As an initial step, this study begins by providing a review of all models are proposed, which we then apply to lung cancer data in Libya. In this paper, we show some preliminary results, which are displayed and compared by using maps, tables, graphics and goodness-of-fit, the last measure of displaying the results is common in statistical modelling to compare fitted models. The main general results presented in this study show that the last two models, BYM and Mixture have been demonstrated to overcome the problem of the first model when there no observed lung cancer cases in certain districts. Also, other results show that Mixture model is most robust and gives a better relative risk estimate across compared it with a range of models

Development and validation of early childhood care and education pre-service lecturer instrument

This paper presents to develop and validate the Early Childhood Care and Pre-Service Lecturer Instrument constructed to determine their level of competencies toward the quality of early childhood carers-educators’ professionalism in Malaysia. Components which affect the early childhood quality were characterized through inclusive literature reviews alongside interviews conducted with experts and experienced lecturers. In this study, two experts were elected to review this instrument so as to enhance its validity while 70 more lecturers in Malaysia were involved. There are four scales in principal component analysis pertaining the quality of early childhood professionalism, namely: (1) disposition, (2) knowledge, (3) skills, and (4) practices. The component loading range or respective instrument item were between 0.56 and 0.79, while the range for respective scales the alpha reliability coefficient were between 0.90 and 0.94. Concisely, the findings from this study corroborated the weight and consistency of the ECCE Pre-Service Lecturer Instrument

Augmented Reality Learning in Mathematics Education: A Systematic Literature Review

The main purpose of this study was to review existing studies which are related to the characteristics of AR learning by using Systematic Literature Review (SLR). The following studies identified the implementation of AR in learning mathematics education and other studies that explored the effectiveness of AR learning towards mathematics education. The review was conducted with the processes of identification, screening, eligibility, inclusion and data analysis on five search engines which were Scopus, ProQuest, Springer Link, Science Direct and EBSCOhost. In reporting this study, the PRISMA guidelines were followed. The data were only selected from the included studies which had been sorted and this resulted in a total of 20 articles. Our findings identified that AR learning was implemented in several topics of mathematics which were geometry; algebra; statistics and probability; and others including mathematical modelling and mathematics technology. The effectiveness of AR learning towards mathematics education also included cognitive, affective, and psychomotor effect. This SLR also included research designs and distribution of studies in terms of trend and country

Mapping Libya’s prostate cancer based on the SMR method: a geographical analysis

Disease mapping has become an important method used in public health research and disease epidemiology. It is a spatial representation of epidemiology data. A very common disease mapping method is called Standardized Morbidity Ratio (SMR). Many researchers used this method to estimate the relative risk of the disease as a preliminary analysis. In this study, the SMR method displays the high and low risk areas of prostate cancer for all districts in Libya. SMR is the ratio of the observed to the expected number of prostate cancer cases and was applied to the observed prostate cancer data from Libya for the years 2010 and 2011. The results were presented in graphs and maps. The highest risk of prostate cancer (all type of cancers) is in the West of Libya probably due to the oil installations in this area such as Mellitah Oil and Gas B.v, the Azawia Oil Refining Company and Bouri Oil Field, as well as the electrical power stations. Susceptible people located in the Eastern part of the country have the lowest risk when compared to the overall population. In conclusion the results show that the use of the SMR method to estimate the relative risk in maps provides high-low risk appearances in maps compared to using the total number of cancer incidence alone. In other words, the SMR method can be considered a basic procedure because it takes into account the total human population for each district