Abstract
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.
Highlights
Ministry of Health (MOH) Malaysia reported that the country has a slightly increasing trend of tuberculosis (TB) cases starts from 16 665 in 2006 to 25 739 in 2016
The findings from the national technical report on TB in 2015 asserted that the existing methods for TB screening among high-risk groups need to be strengthened in order to increase TB cases detection rate (CDR). [1] of World Health Organization (WHO) agreed that the current method still fails to address inequitable distribution of disease and does not diagnose many TB patients in marginalised areas
The regression output of risk model indicates that the selected risk factors of TB patient were significantly associated with the probability of potential TB risk locations (p=0.008, Wald test).The output provides the coefficients for intercept = -46.807 and risk factors with their coefficients
Summary
Ministry of Health (MOH) Malaysia reported that the country has a slightly increasing trend of tuberculosis (TB) cases starts from 16 665 in 2006 to 25 739 in 2016. [1] of WHO agreed that the current method still fails to address inequitable distribution of disease and does not diagnose many TB patients in marginalised areas This situation is caused by several factors especially the inefficiency of the existing method or system to comprehensively detect the TB cases. The biomedical method has advantages in terms of TB diagnosis on human body, the method does not consider geographical or environmental factors This is because TB cases are influenced by humanbased factors, and are driven by environmental risk factors such as land use, human movement and housing condition. This existing method needs to be combined with other techniques [2,3,4] in order to improve management of cases and analytical power
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