METHODS: Malaria is a notifiable infection in Malaysia. The data used in this study were extracted from the Disease Control Division, Ministry of Health Malaysia, contributed by the hospitals and health clinics throughout Malaysia. The population data used in this study was extracted from the Department of Statistics Malaysia. Data analyses were performed using Microsoft Excel. Data used for mapping are available at EPSG:4326 WGS84 CRS (Coordinate Reference System). Shapefile was obtained from igismap. Mapping and plotting of the map were performed using QGIS.
RESULTS: Between 2000 and 2007, human malaria contributed 100% of reported malaria and 18-46 deaths per year in Malaysia. Between 2008 and 2017, indigenous malaria cases decreased from 6071 to 85 (98.6% reduction), while during the same period, zoonotic Plasmodium knowlesi cases increased from 376 to 3614 cases (an 861% increase). The year 2018 marked the first year that Malaysia did not report any indigenous cases of malaria caused by human malaria parasites. However, there was an increasing trend of P. knowlesi cases, with a total of 4131 cases reported in that year. Although the increased incidence of P. knowlesi cases can be attributed to various factors including improved diagnostic capacity, reduction in human malaria cases, and increase in awareness of P. knowlesi, more than 50% of P. knowlesi cases were associated with agriculture and plantation activities, with a large remainder proportion linked to forest-related activities.
CONCLUSIONS: Malaysia has entered the elimination phase of malaria control. Zoonotic malaria, however, is increasing exponentially and becoming a significant public health problem. Improved inter-sectoral collaboration is required in order to develop a more integrated effort to control zoonotic malaria. Local political commitment and the provision of technical support from the World Health Organization will help to create focused and concerted efforts towards ensuring the success of the National Malaria Elimination Strategic Plan.
METHODS: We used the 11-item Duke Social Support Index to assess perceived social support through a face-to-face interview. Higher scores indicate better social support. Linear regression analysis was carried out to determine the factors that influence perceived social support by adapting the conceptual model of social support determinants and its impact on health.
RESULTS: A total of 3959 respondents aged ≥60 years completed the Duke Social Support Index. The estimated mean Duke Social Support Index score was 27.65 (95% CI 27.36-27.95). Adjusted for confounders, the factors found to be significantly associated with social support among older adults were monthly income below RM1000 (-0.8502, 95% CI -1.3523, -0.3481), being single (-0.5360, 95% CI -0.8430, -0.2290), no depression/normal (2.2801, 95% CI 1.6666-2.8937), absence of activities of daily living (0.9854, 95% CI 0.5599-1.4109) and dependency in instrumental activities of daily living (-0.3655, 95% CI -0.9811, -0.3259).
CONCLUSION: This study found that low income, being single, no depression, absence of activities of daily living and dependency in instrumental activities of daily living were important factors related to perceived social support among Malaysian older adults. Geriatr Gerontol Int 2020; 20: 63-67.