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

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.