Socio-Environmental Factors and Tuberculosis: an Exploratory Spatial Analysis in Peninsular Malaysia

Rasam, Abdul Rauf Abdul; Shariff, Noresah Mohd; Dony, Jiloris F.; Misni, Alamah

doi:10.14419/ijet.v7i3.11.15958

Cited by 7 publications

References 10 publications

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Geospatial-Based Model for Diagnosing Potential High-Risk Areas of Tuberculosis Disease in Malaysia

2019

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Malaysia has a medium burden of tuberculosis (TB) incidence based on World Health Organization (WHO) indicator, but the current trend of TB cases is generally alarming. The Ministry of Health (MOH), Malaysia has set up several guidelines to control the disease, however, the national TB technical report in 2015 addressed that existing detection methods of TB on the site still need to be integrated with relevant alternatives. A geospatial based model is proposed to identify potential high-risk areas of TB especially for targeting missing cases and undiagnosed people. The model was developed with three core stages; framework construction, data collection, and risk analysis and modelling. Eight risk factors: urbanisation, distance to factory, socio-economic status (SES), risk group, human mobility, house type, distance to healthcare centres, and number of population were utilised to determine risk rate of TB modelling. This innovative model has successfully estimated a 65 % of potential high-risk TB areas and targeted 106 high-risk localities in the 10 risk sections of the study area. These risk localities have general similarities with other endemic areas worldwide, but there are some interesting findings revealed in this local study towards in the TB control programme. Most of these cases did not only occur in high rise housing areas, but they are concentrated at industrial location, mobility pattern and socio-economic status in urban city. Although, urban areas are favoured area for the local TB, the disease could also potentially occur in semi-urban or rural areas.

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Geospatial-Based Model for Diagnosing Potential High-Risk Areas of Tuberculosis Disease in Malaysia

2019

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Socio-Economic Characteristics of Urban Tuberculosis Areas in Petaling, Selangor: A Current Spatial Exploratory Scenario

Zaini

Rasam²,

Ahmad³

2022

IOP Conf. Ser.: Earth Environ. Sci.

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World Health Organization (WHO) has estimated one-third of the world population as potentially infected with tuberculosis (TB) in 2020. Almost nine (9) million people are detected with TB with approximately two (2) million deaths every year. Selangor state reported among the highest cases of current TB trend in Malaysia. Poverty, immunosuppressive and co-morbidities would relate to the recent TB scenario and urban socioeconomic status (SES) in the state. The study was conducted to exploratory analyse the contemporary effects of SES on the disease in Petaling using a geospatial approach. The main SES factors applied in this study are level of job, income, and education, while Empirical Bayesian Kriging (EBK) of geostatistical interpolation and correlation analysis method were utilised to visualize and estimate the SES-based risk index map and determine the possible socio-economic characteristics. Based on a five likert scale and index method, the risk map was categorised into proposed five (5) classes from Class 1 (blue = very low risk) to Class 5 (red = very high risk). The overall risk map was suggested in a Class 3 (medium-low level) as closely consistent with the correlation analysis (r = 0.37), suggesting that both TB cases and SES factors increased in response to each other but have a medium - weak direct implication. The result has shown that overall SES factor does not greatly affect the local TB cases in 2017, but further study need to be explored on the other potential mediating variables.

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Spatial and Statistics for Profiling Risk Factors of Diseases: A Case Study of Tuberculosis in Malaysia

Rasam

Shariff

Dony

et al. 2019

IOP Conf. Ser.: Earth Environ. Sci.

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Understanding concepts of a proper disease transmission risk is not a straightforward process. In the context of tuberculosis (TB) dynamics, the concepts require the exploration of two meticulous criteria to produce an accurate epidemic modelling of the risk areas of the disease. The criteria include interpreting the biological transmission of the disease and applying multidisciplinary approaches. Spatial statistics were used to evaluate the preferences of risk factors in Shah Alam, Malaysia. GIS-multicriteria decision making (MCDM) method and logistic regression method were specifically integrated to select the local risk factors and seven influential factors were ranked accordingly i.e. human mobility, high risk group, socio-economic status (SES), population, type of house, distance of factory and urbanisation. Each has relative risk rate that affects the cases and the combination of them will even impact more on the overall risk concentration of TB. Human–based factors are identified as dominant effects to the risk than biophysical factors, for example, a location of TB risk will be increased by four times if individuals are living together with people who have TB disease for a particular time period. This geospatial method is expected to predict a better factor prediction in identifying hotspot areas of the disease.

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Socio-Environmental Factors and Tuberculosis: an Exploratory Spatial Analysis in Peninsular Malaysia

Cited by 7 publications

References 10 publications

Geospatial-Based Model for Diagnosing Potential High-Risk Areas of Tuberculosis Disease in Malaysia

Geospatial-Based Model for Diagnosing Potential High-Risk Areas of Tuberculosis Disease in Malaysia

Socio-Economic Characteristics of Urban Tuberculosis Areas in Petaling, Selangor: A Current Spatial Exploratory Scenario

Spatial and Statistics for Profiling Risk Factors of Diseases: A Case Study of Tuberculosis in Malaysia

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