Dengue is a vector borne disease which is one of the major threats to public health in Malaysia. Mapping of dengue distribution in spatial and spatial-temporal aspects can be a useful method in assessing the risk of dengue to the community. This study aimed to map the spatial and spatial-temporal distribution of dengue cases in Seremban district. The Geographical Information System specifically the spatial and spatial-temporal analyses was applied. Spatial statistical analysis of dengue cases used the Moran’s Index, average nearest neighbourhood (ANN) and kernel density estimation. Spatial-temporal analysis was determined through frequency, duration and intensity indices to identify timely dengue risk area. A total of 6076 dengue cases were reported in Seremban Health District Office from 2003-2009. The result showed a high incidence rate in 2003, 2008 dan 2009 with ratio of dengue: dengue hemorrhagic fever of 21.6:1. Moran’s I showed dengue cases occurred in cluster with Z-score of 16.384 (p=0.000). ANN analysis of 0.264 (p= 0.000) where the mean distance between every dengue case is 55 m. Kernel density estimation showed the dengue hotspots concentrated in Nilai and Ampangan. Spatial-temporal analysis with the highest mean of frequency, duration and intensity indices of above 0.023, 0.614 and 0.657 showed that the high risk dengue areas were Nilai, Seremban and Ampangan. The dengue control activities should be targeted at these high risk areas.

There is a growing trend in complementary and alternative medicine (CAM) usage among the population with medical conditions. However, there is hesitancy for medical practitioners to integrate its application with the current treatment modality, despite governance by the authority. Hence, our objective is to systematically evaluate the healthcare perception towards integrating CAM in their practices. We systematically searched three large and renowned databases i.e., Scopus, Web of Science and PubMed, regarding “Perception on Integrating CAM Usage in Patient's Treatment among Healthcare Practitioners” from 2016 until 2020. At least two independent reviewers comprehensively screened and extracted the data from the accepted articles. A total of 15 studies were included in the final qualitative synthesis following a strict and rigorous assessment checked using MMAT 2018 checklist. The studies included providing the richness of information due to the qualitative nature of the study design. There were three main domains extracted i.e. knowledge, attitude, and perspective of the healthcare practitioner towards CAM integration. Limited knowledge of CAM among healthcare providers may be the possible main reason for non-supportive attitude and negative perspective on CAM. However, those who showed an inclination towards CAM were found to be more open and ready to learn about CAM if it provides benefits to the patients. There is a heterogeneity of perception towards CAM integration from healthcare providers' point of view. A proactive and systematic CAM literacy awareness program may help to improve their understanding and possibly gain more trust in its application

The rising trend of Colorectal Cancer (CRC) incidence has become a global concern. Spatial determinants may play an important role as suggested by registered geographical variations of CRC incidence. The current study was designed to identify the spatial distribution pattern of CRC at the neighbourhood level in Malaysia by geocoding the addresses of CRC cases registered by the National Cancer Registry between 2010 and 2016. Cluster analysis was performed to examine the spatial dependence of CRC cases as well as group differences with regard to socio demographic characteristics. Identified clusters were categorized into urban and rural areas based on the population background. Most of the 18,405 individuals included in the study were male (56%) and people aged between 60 and 69 years (30.3%). Among patients with available information on their CRC stage, 71.3% presented for care late (at stages III or IV of the disease). The Malaysian states shown to have CRC clusters were Kedah, Penang, Perak, Selangor, Kuala Lumpur, Melaka, Johor, Kelantan and Sarawak. Spatial autocorrelation detected significant clustering (Moran’s I = 0.244, p < 0.01, Z-score >2.58). The CRC clusters in Penang, Selangor, Kuala Lumpur, Melaka, Johor and Sarawak occurred in urbanized areas, while those in Kedah, Perak and Kelantan were in rural areas. Factors associated with urban CRC clusters as shown by Odds Ratio (OR) included late-stage presentation (1.27, CI 1.15-1.41); post-mortem diagnosis (0.82, CI 0.76-0.89); and adenocarcinoma type of the cancer (0.81, CI 0.67- 0.98). We conclude that the presence of several clusters in urban ized and rural areas implies the impact of ecological determinants at the neighbourhood level. These findings can be used to guide the policymakers in resource allocation and cancer control.

Dengue is a major public health threat in Malaysia, which is known for the hyperendemicity with all the four serotypes of the dengue virus circulating concurrently. Annual dengue cases reported were 43,000 cases for 2013, and this imposed a heavy toll on the resources for dengue prevention and control program. The objective of mapping in our study is to determine the spatial clustering of the dengue cases and to identify the areas that are vulnerable to dengue outbreaks. A Geographical Information System (GIS) was used to assess the vulnerability of Seremban district. Dengue data were obtainedfrom the Ministry ofHealth. We determined the spatial distribution, the average distance of dengue cases and identified hotspots areas using the Moran'-s -I, Average Nearest Neighbourhood (ANN), Kernel density estimation. Vulnerability to dengue was assessed with the spatial temporal analyses and Local Indicator for Spatial Autocorrelation (LISA). From 2003-2009 Seremban recorded 6076 dengue cases. Moran'-s I showed the cases occurred in clusters with a Z-score of 16.384 (p<0.001). ANN 0.264 (p<0.001) indicated the mean distance between every dengue case was 55 meters. Kernel density estimation showed hotspots of dengue were concentrated in two subdistricts. This paper discusses how spatial-temporal approach can be used to assess the vulnerability of Seremban to dengue where control activities can be more focused to these high risk areas. Mapping the dengue distribution using spatial-temporal approach is useful and guides the public health management of dengue.