ABSTRACT
@#Dengue is an increasing threat in Malaysia, particularly in the more densely populated regions of the country. We present an Artificial Intelligence driven model in predicting Aedes outbreak, using predictors of weather variables and vector indices sourced from the Ministry of Health. Analysis and predictions to estimate Aedes populations were conducted, with its results being used to infer the possibility of dengue outbreaks at pre-determined localities around the Klang Valley, Malaysia. A Bayesian Network machine learning technique was employed, with the model being trained using predictor variables such as temperature, rainfall, date of onset and notification, and vector indices such as the Ae. albopictus count, Ae. aegypti count and larval count. The interfaces of the system were developed using the C# language for Server-side configuration and programming, and HTML, CSS and JavaScript for the Client Side programming. The model was then used to predict the population of Aedes at periods of 7, 14, and 30 days. Using the Bayesian Network technique utilising the above predictor variables we proposed a finalised model with predictive accuracy ranging from 79%-84%. This model was developed into a Graphical User Interface, which was purposed to assist and educate the general public of regions at risk of developing dengue outbreak. This remains a valuable case-study on the importance of public data in the context of combating a public health risk via the development of models for predicting outbreaks of dengue which will hopefully spur further sharing of data by all parties in combating public health threats.
ABSTRACT
The aim of this study was to evaluate the effectiveness of individual-focused stress management training namely Deep Breathing Exercise [DBE] on self-perceived occupational stress among male automotive assembly-line workers. A quasi-experimental study was conducted at 2 automotive assembly plants in Malaysia over 9 months, from January 2012 to September 2012. Assembly-line workers from Plant A received DBE training while Plant B acted as a control by receiving pamphlets on stress and its ill-effects. Intention-to-treat analysis was conducted among the self-voluntary respondents in Plant A [n=468] and Plant B [n=293]. The level of stress was measured using Depression Anxiety Stress Scales-21 [DASS-21] stress subscale. Significant favorable intervention effects were found in Plant A [Effect size=0.6] as compared to Plant B [Effect size=0.2] at the end of the study in those receiving DBE. Time and group interaction effects were examined using the repeated measure ANOVA test in which there was a significant group *time interaction effect [F [1, 1] = 272.45, P<0.001]. The improvement in stress levels showed the potential of DBE training as part of Employee Assistance Program in the automotive assembly plant. Future studies should be carried out to assess the long term effects of an on-site relaxation training to provide stronger evidence for the introduction of DBE among assembly-line workers as a coping strategy to alleviate occupational stress