Predicting risk areas of tuberculosis (TB) epidemics needs a proper understanding of the disease transmission process in identifying holistic risk factors. This study was performed to determine the causative factors triggering the epidemics in Shah Alam, Malaysia by utilising spatial analysis techniques and participation of local-expert knowledge or local spatial knowledge (LSK) approach. LSK approach was conducted to collect data on TB risk factors by combining experienced local experts' opinions, multi-criteria decision making (MCDM) analysis, and GIS mapping. The combination of experts participatory GIS and knowledge elicitation can generate a useful spatial knowledge framework for risk assessment of local epidemics. Keywords: Local spatial knowledge, MCDM method, experts participatory GIS, tuberculosis. eISSN: 2398-4287 © 2020. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v5iSI2.2522.

The World Health Organization (WHO) recognizes the capabilities of a health information tool for disease preparedness and emergency responses. In Malaysia, the Ministry of Health (MOH) has been using MyTB system to support the national tuberculosis (TB) control program through data decision-making management. However, this present system does not seem to be considering geospatial element which is one of the important factors affecting TB control. Integrating the MyTB system with geospatial functions would enhance the explicit cognitive and behavior analyses of TB by proposing a MyGeoTBIS© to assist the local health authorities in exploring TB dynamics and multi-level infection control. Keywords: Geospatial, GIS, MyGeoTBIS, MyTB, tuberculosis disease eISSN: 2398-4287© 2020. The Authors. Published for AMER ABRA cE-Bsby e-International Publishing House, Ltd., UK. This is an open access article under the CC BYNC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v5iSI3.2564

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.

A365for the FDA, EMA, Health Canada and Australia the Australian Therapeutic Goods Administration. The studies used to make regulatory decisions were then compared to the studies used in the reimbursement decisions of France, Scotland, Canada and Australia. Results: In all 15 cases reviewed the FDA, EMA and Health Canada used at least one of the same studies to come to their decision and in 13 of the cases Australia also used that same study. In 14 cases the FDA approved the drug before the other regulatory authorities; the longest time before another regulatory agency approved a drug was 15 months for rilpivirine. In six cases the FDA commissioned studies that other regulatory bodies and reimbursement agencies used later. All of the studies were interventional studies. Reimbursement agencies always used studies that were previously cited in regulatory documents. These agencies would also use studies intended for the regulatory approval of another drug as a source for information in a review. ConClusions: Reimbursement agencies and other regulatory agencies are influenced by the FDA in the studies they consider, as illustrated by at least six cases in which other agencies used studies commissioned by the FDA after approval. This influence is easier to see in the last five years, but may be older than that due to improvements in published reports.