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: Microscopy-based malaria notification data and polymerase chain reaction (PCR) results were obtained from the Sabah Department of Health and State Public Health Laboratory, respectively, from January 2015 to December 2017. From January 2016 this was complemented by a statewide prospective hospital surveillance study. Databases were matched, and species was determined by PCR, or microscopy if PCR was not available.
RESULTS: A total of 3867 malaria cases were recorded between 2015 and 2017, with PCR performed in 93%. Using PCR results, and microscopy if PCR was unavailable, P. knowlesi accounted for 817 (80%), 677 (88%), and 2030 (98%) malaria cases in 2015, 2016, and 2017, respectively. P. falciparum accounted for 110 (11%), 45 (6%), and 23 (1%) cases and P. vivax accounted for 61 (6%), 17 (2%), and 8 (0.4%) cases, respectively. Of those with P. knowlesi, the median age was 35 (interquartile range: 24-47) years, and 85% were male.
CONCLUSIONS: Malaysia is approaching elimination of the human-only Plasmodium species. However, the ongoing increase in P. knowlesi incidence presents a major challenge to malaria control and warrants increased focus on knowlesi-specific prevention activities. Wider molecular surveillance in surrounding countries is required.
METHODS AND ANALYSIS: A population-based case-control study will be conducted over a 2-year period at two adjacent districts in north-west Sabah, Malaysia. Confirmed malaria cases presenting to the district hospital sites meeting relevant inclusion criteria will be requested to enrol. Three community controls matched to the same village as the case will be selected randomly. Study procedures will include blood sampling and administration of household and individual questionnaires to evaluate potential exposure risks associated with acquisition of P. knowlesi malaria. Secondary outcomes will include differences in exposure variables between P. knowlesi and other Plasmodium spp, risk of severe P. knowlesi malaria, and evaluation of P. knowlesi case clustering. Primary analysis will be per protocol, with adjusted ORs for exposure risks between cases and controls calculated using conditional multiple logistic regression models.
ETHICS: This study has been approved by the human research ethics committees of Malaysia, the Menzies School of Health Research, Australia, and the London School of Hygiene and Tropical Medicine, UK.
METHODS: We did this population-based case-control study over a 2 year period in the state of Sabah in Malaysia. We enrolled cases with microscopy-positive, PCR-confirmed malaria who presented to two primary referral hospitals serving the adjacent districts of Kudat and Kota Marudu. We randomly selected three malaria-negative community controls per case, who were matched by village within 2 weeks of case detection. We obtained questionnaire data on demographics, behaviour, and residential malaria risk factors, and we also assessed glucose-6-phosphate dehydrogenase (G6PD) enzyme activity. We used conditional logistic regression models to evaluate exposure risk between P knowlesi cases and controls, and between P knowlesi and human-only Plasmodium spp malaria cases.
FINDINGS: From Dec 5, 2012, to Jan 30, 2015, we screened 414 patients and subsequently enrolled 229 cases with P knowlesi malaria mono-infection and 91 cases with other Plasmodium spp infection. We enrolled 953 matched controls, including 683 matched to P knowlesi cases and 270 matched to non-P knowlesi cases. Age 15 years or older (adjusted odds ratio [aOR] 4·16, 95% CI 2·09-8·29, p<0·0001), male gender (4·20, 2·54-6·97, p<0·0001), plantation work (3·50, CI, 1·34-9·15, p=0·011), sleeping outside (3·61, 1·48-8·85, p=0·0049), travel (2·48, 1·45-4·23, p=0·0010), being aware of the presence of monkeys in the past 4 weeks (3·35, 1·91-5·88, p<0·0001), and having open eaves or gaps in walls (2·18, 1·33-3·59, p=0·0021) were independently associated with increased risk of symptomatic P knowlesi infection. Farming occupation (aOR 1·89, 95% CI 1·07-3·35, p=0·028), clearing vegetation (1·89, 1·11-3·22, p=0·020), and having long grass around the house (2·08, 1·25-3·46, p=0·0048) increased risk for P knowlesi infection but not other Plasmodium spp infection. G6PD deficiency seemed to be protective against P knowlesi (aOR 0·20, 95% CI 0·04-0·96, p=0·045), as did residual insecticide spraying of household walls (0·52, 0·31-0·87, p=0·014), with the presence of young sparse forest (0·35, 0·20-0·63, p=00040) and rice paddy around the house (0·16, 0·03-0·78, 0·023) also associated with decreased risk.
INTERPRETATION: Adult men working in agricultural areas were at highest risk of knowlesi malaria, although peri-domestic transmission also occurrs. Human behavioural factors associated with P knowlesi transmission could be targeted in future public health interventions.
FUNDING: United Kingdom Medical Research Council, Natural Environment Research Council, Economic and Social Research Council, and Biotechnology and Biosciences Research Council.
METHODS: A clinical efficacy study of oral artesunate (total target dose 12 mg/kg) daily for 3 days was conducted in patients with uncomplicated falciparum malaria and a parasite count
METHODS: This is a secondary data review of all diagnosed and reported malaria confirmed cases notified to the Ministry of Health, Malaysia between January 2013 and December 2017.
RESULTS: From 2013 to 2017, a total of 16,500 malaria cases were notified in Malaysia. The cases were mainly contributed from Sabah (7150; 43.3%) and Sarawak (5684; 34.4%). Majority of the patients were male (13,552; 82.1%). The most common age group in Peninsular Malaysia was 20 to 29 years (1286; 35.1%), while Sabah and Sarawak reported highest number of malaria cases in age group of 30 to 39 years (2776; 21.6%). The top two races with malaria in Sabah and Sarawak were Bumiputera Sabah (5613; 43.7%) and Bumiputera Sarawak (4512; 35.1%), whereas other ethnic group (1232; 33.6%) and Malays (1025; 28.0%) were the two most common races in Peninsular Malaysia. Plasmodium knowlesi was the commonest species in Sabah and Sarawak (9902; 77.1%), while there were more Plasmodium vivax cases (1548; 42.2%) in Peninsular Malaysia. The overall average incidence rate, mortality rate and case fatality rates for malaria from 2013 to 2017 in Malaysia were 0.106/1000, 0.030/100,000 and 0.27%, respectively. Sarawak reported the highest average incidence rate of 0.420/1000 population followed by Sabah (0.383/1000). Other states in Peninsular Malaysia reported below the national average incidence rate with less than 0.100/1000.
CONCLUSIONS: There were different trends and characteristics of notified malaria cases in Peninsular Malaysia and Sabah and Sarawak. They provide useful information to modify current prevention and control measures so that they are customised to the peculiarities of disease patterns in the two regions in order to successfully achieve the pre-elimination of human-only species in the near future.
METHODS: A randomized 4 × 4 Latin square designed experiment was conducted to compare the efficiency of the Mosquito Magnet against three other common trapping methods: human landing catch (HLC), CDC light trap and human baited trap (HBT). The experiment was conducted over six replicates where sampling within each replicate was carried out for 4 consecutive nights. An additional 4 nights of sampling was used to further evaluate the Mosquito Magnet against the "gold standard" HLC. The abundance of Anopheles sampled by different methods was compared and evaluated with focus on the Anopheles from the Leucosphyrus group, the vectors of knowlesi malaria.
RESULTS: The Latin square designed experiment showed HLC caught the greatest number of Anopheles mosquitoes (n = 321) compared to the HBT (n = 87), Mosquito Magnet (n = 58) and CDC light trap (n = 13). The GLMM analysis showed that the HLC method caught significantly more Anopheles mosquitoes compared to Mosquito Magnet (P = 0.049). However, there was no significant difference in mean nightly catch of Anopheles mosquitoes between Mosquito Magnet and the other two trapping methods, HBT (P = 0.646) and CDC light traps (P = 0.197). The mean nightly catch for both An. introlatus (9.33 ± 4.341) and An. cracens (4.00 ± 2.273) caught using HLC was higher than that of Mosquito Magnet, though the differences were not statistically significant (P > 0.05). This is in contrast to the mean nightly catch of An. sinensis (15.75 ± 5.640) and An. maculatus (15.78 ± 3.479) where HLC showed significantly more mosquito catches compared to Mosquito Magnet (P