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ABSTRACT:Development of an innovative method to enhance the detection of tuberculosis (TB) in Malaysia is the latest agenda of the Ministry of Health. Therefore, a geographical information system (GIS) based index model is proposed as an alternative method for defining potential high-risk areas of local TB cases at Section U19, Shah Alam. It is adopted a spatial multi-criteria decision making (MCDM) method for ranking environmental risk factors of the disease in a standardised five-score scale. Scale 1 and 5 illustrate the lowest and the highest risk of the TB spread respectively, while scale from 3 to 5 is included as a potential risk level. These standardised scale values are then combined with expert normalised weights (0 to 1) to calculate the overall index values and produce a TB ranked map using a GIS overlay analysis and weighted linear combination. It is discovered that 71.43% of the Section is potential as TB high risk areas particularly at urban and densely populated settings. This predictive result is also reliable with the current real cases in 2015 by 76.00% accuracy. A GIS based MCDM method has demonstrated analytical capabilities in targeting high-risk spots and TB surveillance monitoring system of the country, but the result could be strengthened by applying other uncertainty assessment method.

Background: The monkey parasite Plasmodium knowlesi is an emerging public health issue in Southeast Asia. In Sabah, Malaysia, P. knowlesi is now the dominant cause of human malaria. Molecular detection methods for P. knowlesi are essential for accurate diagnosis and in monitoring progress towards malaria elimination of other Plasmodium species. However, recent commercially available PCR malaria kits have unpublished P. knowlesi gene targets or have not been evaluated against clinical samples. Methods: Two real-time PCR methods currently used in Sabah for confirmatory malaria diagnosis and surveillance reporting were evaluated: the QuantiFast ™ Multiplex PCR kit (Qiagen, Germany) targeting the P. knowlesi 18S SSU rRNA; and the abTES ™ Malaria 5 qPCR II kit (AITbiotech, Singapore), with an undisclosed P. knowlesi gene target. Diagnostic accuracy was evaluated using 52 P. knowlesi, 25 Plasmodium vivax, 21 Plasmodium falciparum, and 10 Plasmodium malariae clinical isolates, and 26 malaria negative controls, and compared against a validated reference nested PCR assay. The limit of detection (LOD) for each PCR method and Plasmodium species was also evaluated. Results: The sensitivity of the QuantiFast ™ and abTES ™ assays for detecting P. knowlesi was comparable at 98.1% (95% CI 89.7-100) and 100% (95% CI 93.2-100), respectively. Specificity of the QuantiFast ™ and abTES ™ for P. knowlesi was high at 98.8% (95% CI 93.4-100) for both assays. The QuantiFast ™ assay demonstrated falsely-positive mixed Plasmodium species at low parasitaemias in both the primary and LOD analysis. Diagnostic accuracy of both PCR kits for detecting P. vivax, P. falciparum, and P. malariae was comparable to P. knowlesi. The abTES ™ assay demonstrated a lower LOD for P. knowlesi of ≤ 0.125 parasites/µL compared to QuantiFast ™ with a LOD of 20 parasites/µL. Hospital

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