|Commenced in January 1999 || Frequency: Monthly || Edition: International|| Paper Count: 2 |
Medical, Health, Biomedical, Bioengineering and Pharmaceutical Engineering
Modelling Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) Outbreak Using Poisson and Negative Binomial Model
Dengue fever has become a major concern for health
authorities all over the world particularly in the tropical countries.
These countries, in particular are experiencing the most worrying
outbreak of dengue fever (DF) and dengue haemorrhagic fever
(DHF). The DF and DHF epidemics, thus, have become the main
causes of hospital admissions and deaths in Malaysia. This paper,
therefore, attempts to examine the environmental factors that may
influence the recent dengue outbreak. The aim of this study is twofold,
firstly is to establish a statistical model to describe the
relationship between the number of dengue cases and a range of
explanatory variables and secondly, to identify the lag operator for
explanatory variables which affect the dengue incidence the most.
The explanatory variables involved include the level of cloud cover,
percentage of relative humidity, amount of rainfall, maximum
temperature, minimum temperature and wind speed. The Poisson and
Negative Binomial regression analyses were used in this study. The
results of the analyses on the 915 observations (daily data taken from
July 2006 to Dec 2008), reveal that the climatic factors comprising of
daily temperature and wind speed were found to significantly
influence the incidence of dengue fever after 2 and 3 weeks of their
occurrences. The effect of humidity, on the other hand, appears to be
significant only after 2 weeks.
Flow Regime Characterization in a Diseased Artery Model
Cardiovascular disease mostly in the form of atherosclerosis is responsible for 30% of all world deaths amounting to 17 million people per year. Atherosclerosis is due to the formation of plaque. The fatty plaque may be at risk of rupture, leading typically to stroke and heart attack. The plaque is usually associated with a high degree of lumen reduction, called a stenosis. The initiation and progression of the disease is strongly linked to the hemodynamic environment near the vessel wall. The aim of this study is to validate the flow of blood mimic through an arterial stenosis model with computational fluid dynamics (CFD) package. In experiment, an axisymmetric model constructed consists of contraction and expansion region that follow a mathematical form of cosine function. A 30% diameter reduction was used in this study. Particle image velocimetry (PIV) was used to characterize the flow. The fluid consists of rigid spherical particles suspended in waterglycerol- NaCl mixture. The particles with 20 μm diameter were selected to follow the flow of fluid. The flow at Re=155, 270 and 390 were investigated. The experimental result is compared with FLUENT simulated flow that account for viscous laminar flow model. The results suggest that laminar flow model was sufficient to predict flow velocity at the inlet but the velocity at stenosis throat at Re =390 was overestimated. Hence, a transition to turbulent regime might have been developed at throat region as the flow rate increases.