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
METHODS: Anopheles mosquitoes were collected from the location where P. knowlesi cases were reported. Cases of knowlesi malaria from 2011 to 2019 in Johor were analyzed. Internal transcribed spacers 2 (ITS2) and cytochrome c oxidase subunit I (COI) genes were used to identify the Leucosphyrus Group of Anopheles mosquitoes. In addition, spatial analysis was carried out on the knowlesi cases and vectors in Johor.
RESULTS: One hundred and eighty-nine cases of P. knowlesi were reported in Johor over 10 years. Young adults between the ages of 20-39 years comprised 65% of the cases. Most infected individuals were involved in agriculture and army-related occupations (22% and 32%, respectively). Four hundred and eighteen Leucosphyrus Group Anopheles mosquitoes were captured during the study. Anopheles introlatus was the predominant species, followed by Anopheles latens. Spatial analysis by Kriging interpolation found that hotspot regions of P. knowlesi overlapped or were close to the areas where An. introlatus and An. latens were found. A significantly high number of vectors and P. knowlesi cases were found near the road within 0-5 km.
CONCLUSIONS: This study describes the distribution of P. knowlesi cases and Anopheles species in malaria-endemic transmission areas in Johor. Geospatial analysis is a valuable tool for studying the relationship between vectors and P. knowlesi cases. This study further supports that the Leucosphyrus Group of mosquitoes might be involved in transmitting knowlesi malaria cases in Johor. These findings may provide initial evidence to prioritize diseases and vector surveillance.
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.
MATERIALS AND METHODS: Blood samples on filter papers were subject to conventional PCR methods using primers designed by us in multiplex PCR and previously designed primers of nested PCR. Both sets of results were compared with microscopic identification.
RESULTS: Of the 129 samples identified as malaria-positive by microscopy, 15 samples were positive for P. falciparum, 14 for P. vivax, 6 for P. knowlesi, 72 for P. malariae, and 2 for mixed infection of P. falciparum/P. malariae. Both multiplex and nested PCR identified 12 P. falciparum single infections. For P. vivax, 9 were identified by multiplex and 12 by nested PCR. For 72 P. malariae cases, multiplex PCR identified 58 as P. knowlesi and 10 as P. malariae compared to nested PCR, which identified 59 as P. knowlesi and 7 as P. malariae.
CONCLUSION: Multiplex PCR could be used as alternative molecular diagnosis for the identification of all Plasmodium species as it requires a shorter time to screen a large number of samples.
METHODS: Two real-time PCR methods currently used in Sabah for confirmatory malaria diagnosis and surveillance reporting were evaluated: the QuantiFast™ Multiplex PCR kit (Qiagen, Germany) targeting the P. knowlesi 18S SSU rRNA; and the abTES™ Malaria 5 qPCR II kit (AITbiotech, Singapore), with an undisclosed P. knowlesi gene target. Diagnostic accuracy was evaluated using 52 P. knowlesi, 25 Plasmodium vivax, 21 Plasmodium falciparum, and 10 Plasmodium malariae clinical isolates, and 26 malaria negative controls, and compared against a validated reference nested PCR assay. The limit of detection (LOD) for each PCR method and Plasmodium species was also evaluated.
RESULTS: The sensitivity of the QuantiFast™ and abTES™ assays for detecting P. knowlesi was comparable at 98.1% (95% CI 89.7-100) and 100% (95% CI 93.2-100), respectively. Specificity of the QuantiFast™ and abTES™ for P. knowlesi was high at 98.8% (95% CI 93.4-100) for both assays. The QuantiFast™ assay demonstrated falsely-positive mixed Plasmodium species at low parasitaemias in both the primary and LOD analysis. Diagnostic accuracy of both PCR kits for detecting P. vivax, P. falciparum, and P. malariae was comparable to P. knowlesi. The abTES™ assay demonstrated a lower LOD for P. knowlesi of ≤ 0.125 parasites/µL compared to QuantiFast™ with a LOD of 20 parasites/µL. Hospital microscopy demonstrated a sensitivity of 78.8% (95% CI 65.3-88.9) and specificity of 80.4% (95% CI 67.6-89.8) compared to reference PCR for detecting P. knowlesi.
CONCLUSION: The QuantiFast™ and abTES™ commercial PCR kits performed well for the accurate detection of P. knowlesi infections. Although the QuantiFast™ kit is cheaper, the abTES™ kit demonstrated a lower LOD, supporting its use as a second-line referral-laboratory diagnostic tool in Sabah, Malaysia.