Mazrura Sahani

Transboundary smoke haze pollution in Malaysia: Inpatient health impacts and economic valuation

This study assessed the economic value of health impacts of transboundary smoke haze pollution in Kuala Lumpur and adjacent areas in the state of Selangor, Malaysia. Daily inpatient data from 2005, 2006, 2008, and 2009 for 14 haze-related illnesses were collected from four hospitals. On average, there were 19 hazy days each year during which the air pollution levels were within the Lower Moderate to Hazardous categories. No seasonal variation in inpatient cases was observed. A smoke haze occurrence was associated with an increase in inpatient cases by 2.4 per 10,000 populations each year, representing an increase of 31 percent from normal days. The average annual economic loss due to the inpatient health impact of haze was valued at MYR273,000 (

Predictive models for dengue outbreak using multiple rulebase classifiers

91,000 USD).

Comprehensive assessment of PM2.5 physicochemical properties during the Southeast Asia dry season (southwest monsoon)

The paper aims to develop the predictive models for dengue outbreak detection using Multiple Rule Based Classifiers. The rule based classifiers used are the Decision Tree, Rough Set Classifier, Naive Bayes, and Associative Classifier. Dengue fever (DF) and dengue hemorrhagic fever (DHF) have been continuously becoming a public health related issues in Malaysia and growing pandemic as reported by World Health Organization (WHO). It is important for the government to able to make early detection for dengue outbreak. Thus, to improve early detection of the dengue outbreak and making such strategic planning and decision, being able to predict or forecast the possible dengue outbreak in an area is critically important. The purpose of the classification modelling is to build a predictive model for predicting the dengue outbreak. Since to date there is no research uses this data for predictive modelling, several classifiers are investigated to study the performance of various rule based classifiers individually and the combination of the classifiers. The experimental results show that the multiple classifiers are able produce better accuracy (up to 70%) with more quality rules compared to the single classifier.

Multiple attribute frequent mining-based for dengue outbreak

A comprehensive assessment of fine particulate matter (PM2.5) compositions during the Southeast Asia dry season is presented. Samples of PM2.5 were collected between 24 June and 14 September 2014 using a high-volume sampler. Water-soluble ions, trace species, rare earth elements, and a range of elemental carbon (EC) and organic carbon were analyzed. The characterization and source apportionment of PM2.5 were investigated. The results showed that the 24 h PM2.5 concentration ranged from 6.64 to 68.2 µg m−3. Meteorological driving factors strongly governed the diurnal concentration of aerosol, while the traffic in the morning and evening rush hours coincided with higher levels of CO and NO2. The correlation analysis for non sea-salt K+-EC showed that EC is potentially associated with biomass burning events, while the formation of secondary organic carbon had a moderate association with motor vehicle emissions. Positive matrix factorization (PMF) version 5.0 identified the sources of PM2.5: (i) biomass burning coupled with sea salt [I] (7%), (ii) aged sea salt and mixed industrial emissions (5%), (iii) road dust and fuel oil combustion (7%), (iv) coal-fired combustion (25%), (v) mineral dust (8%), (vi) secondary inorganic aerosol (SIA) coupled with F− (15%), and (vii) motor vehicle emissions coupled with sea salt [II] (24%). Motor vehicle emissions, SIA, and coal-fired power plant are the predominant sources contributing to PM2.5. The response of the potential source contribution function and Hybrid Single-Particle Lagrangian Integrated Trajectory backward trajectory model suggest that the outline of source regions were consistent to the sources by PMF 5.0.

Physicochemical factors and their potential sources inferred from long-term rainfall measurements at an urban and a remote rural site in tropical areas

Dengue fever (DF) and dengue hemorrhagic fever (DHF) are vector borne disease which is notifiable diseases in Malaysia since 1974. Early notification is essential for control measures as delayed notification will lead to further occurrences of outbreak cases. In this study we identify the number of attributes to be used in determining outbreaks rather than using only case counts. The experiment is conducted using multiple attribute value based on Apriori concept. The outcomes are promising when we can identify more than one attributes showing similar graph in vector-borne diseases outbreaks. Our methods also outperform in term of detection rate, false positive rate and overall performance. We prove through our experiment that more than one attributes can be used to better detect outbreaks.

Spatial occurrence of dengue fever and its relationship with land use in Selangor, Malaysia

Air pollution can be detected through rainwater composition. In this study, long-term measurements (2000-2014) of wet deposition were made to evaluate the physicochemical interaction and the potential sources of pollution due to changes of land use. The rainwater samples were obtained from an urban site in Kuala Lumpur and a highland-rural site in the middle of Peninsular Malaysia. The compositions of rainwater were obtained from the Malaysian Meteorological Department. The results showed that the urban site experienced more acidity in rainwater (avg=277mm, range of 13.8 to 841mm; pH=4.37) than the rural background site (avg=245mm, range of 2.90 to 598mm; pH=4.97) due to higher anthropogenic input of acid precursors. The enrichment factor (EF) analysis showed that at both sites, SO42-, Ca2+ and K+ were less sensitive to seawater but were greatly influenced by soil dust. NH4+ and Ca2+ can neutralise a larger fraction of the available acid ions in the rainwater at the urban and rural background sites. However, acidifying potential was dominant at urban site compared to rural site. Source-receptor relationship via positive matrix factorisation (PMF 5.0) revealed four similar major sources at both sites with a large variation of the contribution proportions. For urban, the major sources influence on the rainwater chemistry were in the order of secondary nitrates and sulfates>ammonium-rich/agricultural farming>soil components>marine sea salt and biomass burning, while at the background site the order was secondary nitrates and sulfates>marine sea salt and biomass burning=soil components>ammonia-rich/agricultural farming. The long-term trend showed that anthropogenic activities and land use changes have greatly altered the rainwater compositions in the urban environment while the seasonality strongly affected the contribution of sources in the background environment.

Mercury in Dental Amalgam: Are Our Health Care Workers at Risk?

Background Dengue fever has a profound impact in Malaysia, and globally, it has a strong potential to spread to new territories as a consequence of human activities and climate change that modify the environment. Environmental factors can affect the disease epidemic via their influence on vector’s habitat and propagation. Among the economic costs borne in dealing with this matter related to epidemic identification and vector surveillance. The relationship between dengue fever and environmental factors namely land use and degree of urbanisation were investigated in the state of Selangor, Malaysia.

Airborne particles in the city center of Kuala Lumpur: Origin, potential driving factors, and deposition flux in human respiratory airways

ABSTRACT Dental amalgam in fillings exposes workers to mercury. The exposure to mercury was investigated among 1871 dental health care workers. The aim of the study was to evaluate the risk of mercury exposure among dental compared to nondental health care workers and to determine other risk factors for mercury exposure. Respondents answered questionnaires to obtain demographic, personal, professional, and workplace information and were examined for their own amalgam fillings. Chronic mercury exposure was assessed through urinary mercury levels. In total, 1409 dental and 462 nondental health care workers participated in the study. Median urine mercury levels for dental and nondental health care workers were 2.75 μg/L (interquartile range [IQR] = 3.0175) and 2.66 μg/L (IQR = 3.04) respectively. For mercury exposure, there were no significant risk factor found among the workers involved within the dental care. The Mann–Whitney test showed that urine mercury levels were significantly different between respondents who eat seafood more than 5 times per week compared to those who eat it less frequently or not at all (p = 0.003). The urinary mercury levels indicated significant difference between dental workers in their practice using squeeze cloths (Mann–Whitney test, p = 0.03). Multiple logistic regression showed that only the usage of cosmetic products that might contain mercury was found to be significantly associated with the urinary mercury levels (odds ratio [OR] = 15.237; CI: 3.612–64.276). Therefore, mean urinary mercury levels of health care workers were low. Exposure to dental amalgam is not associated with high mercury exposure. However, usage of cosmetic products containing mercury and high seafood consumption may lead to the increase of exposure to mercury. Implications: Exposure to the high levels of mercury from dental amalgam can lead to serious health effects among the dental health care workers. Nationwide chronic mercury exposure among dental personnel was assessed through urinary mercury levels. Findings suggest low urinary mercury levels of these health care workers. Exposure to dental amalgam is not associated with high mercury exposure. However, the usage of cosmetic products containing mercury and high seafood consumption may lead to the increase of exposure to mercury.

Concentration and source identification of polycyclic aromatic hydrocarbons (PAHs) in PM10 of urban, industrial and semi-urban areas in Malaysia

Equatorial warming conditions in urban areas can influence the particle number concentrations (PNCs), but studies assessing such factors are limited. The aim of this study was to evaluate the level of size-resolved PNCs, their potential deposition rate in the human respiratory system, and probable local and transboundary inputs of PNCs in Kuala Lumpur. Particle size distributions of a 0.34 to 9.02 μm optical-equivalent size range were monitored at a frequency of 60 s between December 2016 and January 2017 using an optical-based compact scanning mobility particle sizer (SMPS). Diurnal and correlation analysis showed that traffic emissions and meteorological confounding factors were potential driving factors for changes in the PNCs (Dp ≤1 μm) at the modeling site. Trajectory modeling showed that a PNC <100/cm3 was influenced mainly by Indo-China region air masses. On the other hand, a PNC >100/cm3 was influenced by air masses originating from the Indian Ocean and Indochina regions. Receptor models extracted five potential sources of PNCs: industrial emissions, transportation, aged traffic emissions, miscellaneous sources, and a source of secondary origin coupled with meteorological factors. A respiratory deposition model for male and female receptors predicted that the deposition flux of PM1 (particle mass ≤1 μm) into the alveolar (AL) region was higher (0.30 and 0.25 μg/h, respectively) than the upper airway (UA) (0.29 and 0.24 μg/h, respectively) and tracheobronchial (TB) regions (0.02 μg/h for each). However, the PM2.5 deposition flux was higher in the UA (2.02 and 1.68 μg/h, respectively) than in the TB (0.18 and 0.15 μg/h, respectively) and the AL regions (1.09 and 0.91 μg/h, respectively); a similar pattern was also observed for PM10.