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 AND METHODS: This retrospective population-based case-control study was conducted in Ranau district to assess sociodemographic, behavioural and medical history risk factors using a pretested questionnaire. The data were entered and analyzed using IBM SPSS version 23. Bivariate analysis was conducted using binary logistic regression whereas multivariate analysis was conducted using multivariable logistic regression. We set a statistical significance at p-value less than or equal to 0.05.
RESULTS: A total of 266 cases and 532 controls were included in the study. Male gender (AOR = 2.71; 95% CI: 1.63-4.50), spending overnight in forest (AOR = 1.92; 95% CI: 1.20-3.06), not using mosquito repellent (AOR = 2.49; 95% CI: 1.36-4.56) and history of previous malaria infection (AOR = 49.34; 95% CI: 39.09-78.32) were found to be independent predictors of P. knowlesi infection.
CONCLUSIONS: This study showed the need to strengthen the strategies in preventing and controlling P. knowlesi infection specifically in changing the practice of spending overnight in forest and increasing the usage of personal mosquito repellent.