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: Gerbils, 5-7 weeks old were infected by PbA via intraperitoneal injection of 1 × 106 (0.2 mL) infected red blood cells. Parasitemia, weight gain/loss, hemoglobin concentration, red blood cell count and body temperature changes in both control and infected groups were monitored over a duration of 13 days. RNA was extracted from the brain, spleen and whole blood to assess the immune response to PbA infection. Organs including the brain, spleen, heart, liver, kidneys and lungs were removed aseptically for histopathology.
RESULTS: Gerbils were susceptible to PbA infection, showing significant decreases in the hemoglobin concentration, RBC counts, body weights and body temperature, over the course of the infection. There were no neurological signs observed. Both pro-inflammatory (IFNγ and TNF) and anti-inflammatory (IL-10) cytokines were significantly elevated. Splenomegaly and hepatomegaly were also observed. PbA parasitized RBCs were observed in the organs, using routine light microscopy and in situ hybridization.
CONCLUSION: Gerbils may serve as a good model for severe malaria to further understand its pathogenesis.
METHODS: A total of 189 whole blood samples were collected from Telupid Health Clinic, Sabah, Malaysia, from 2008 to 2011. All patients who participated in the study were microscopically malaria positive before recruitment. Complete demographic details and haematological profiles were obtained from 85 patients (13 females and 72 males). Identification of Plasmodium species was conducted using PlasmoNex™ targeting the 18S ssu rRNA gene.
RESULTS: A total of 178 samples were positive for Plasmodium species by using PlasmoNex™. Plasmodium falciparum was identified in 68 samples (38.2%) followed by 64 cases (36.0%) of Plasmodium vivax, 42 (23.6%) cases of P. knowlesi, two (1.1%) cases of Plasmodium malariae and two (1.1%) mixed-species infections (i e, P. vivax/P. falciparum). Thirty-five PlasmoNex™ positive P. knowlesi samples were misdiagnosed as P. malariae by microscopy. Plasmodium knowlesi was detected in all four districts of Sandakan division with the highest incidence in the Kinabatangan district. Thrombocytopaenia and anaemia showed to be the most frequent malaria-associated haematological complications in this study.
CONCLUSIONS: The discovery of P. knowlesi in Sandakan division showed that prospective studies on the epidemiological risk factors and transmission dynamics of P. knowlesi in these areas are crucial in order to develop strategies for effective malaria control. The availability of advanced diagnostic tool PlasmoNex™ enhanced the accuracy and accelerated the speed in the diagnosis of malaria.
METHODS: The prevalence of Wolbachia in Culicinae mosquitoes was assessed via PCR with wsp primers. For some of the mosquitoes, in which the wsp primers failed to amplify a product, Wolbachia screening was performed using nested PCR targeting the 16S rRNA gene. Wolbachia sequences were aligned using Geneious 9.1.6 software, analyzed with BLAST, and the most similar sequences were downloaded. Phylogenetic analyses were carried out with MEGA 7.0 software. Graphs were drawn with GraphPad Prism 8.0 software.
RESULTS: A total of 217 adult mosquitoes representing 26 mosquito species were screened. Of these, infections with Wolbachia were detected in 4 and 15 mosquito species using wsp and 16S rRNA primers, respectively. To our knowledge, this is the first time Wolbachia was detected using 16S rRNA gene amplification, in some Anopheles species (some infected with Plasmodium), Culex sinensis, Culex vishnui, Culex pseudovishnui, Mansonia bonneae and Mansonia annulifera. Phylogenetic analysis based on wsp revealed Wolbachia from most of the mosquitoes belonged to Wolbachia Supergroup B. Based on 16S rRNA phylogenetic analysis, the Wolbachia strain from Anopheles mosquitoes were more closely related to Wolbachia infecting Anopheles from Africa than from Myanmar.
CONCLUSIONS: Wolbachia was found infecting Anopheles and other important disease vectors such as Mansonia. Since Wolbachia can affect its host by reducing the life span and provide resistance to pathogen infection, several studies have suggested it as a potential innovative tool for vector/vector-borne disease control. Therefore, it is important to carry out further studies on natural Wolbachia infection in vector mosquitoes' populations as well as their long-term effects in new hosts and pathogen suppression.
METHODOLOGY/PRINCIPAL FINDINGS: Spatiotemporal analysis of national notified CHIKV case addresses was performed. Between 2009-2022, 12,446 CHIKV cases were reported, with peaks in 2009 and 2020, and a significant shift from predominantly rural cases in 2009-2011 (85.1% rural), to urban areas in 2017-2022 (86.1% urban; p<0.0001). Two Ae. aegypti strains, field-collected MC1 and laboratory Kuala Lumpur (KL) strains, were fed infectious blood containing constructed CHIKV clones, pCMV-p2020A (E1-226A) and pCMV-p2020V (E1-226V) to measure CHIKV replication by real-time PCR and/or virus titration. The pCMV-p2020A clone replicated better in Ae. aegypti cell line Aag2 and showed higher replication, infection and dissemination efficiency in both Ae. aegypti strains, compared to pCMV-p2020V.
CONCLUSIONS/SIGNIFICANCE: This study revealed that a change in circulating CHIKV variants can be associated with changes in vector competence and outbreak epidemiology. Continued genomic surveillance of arboviruses is important.
METHODS: We used macaque and mosquito species presence data, background data that captured sampling bias in the presence data, a boosted regression tree model and environmental datasets, including annual data for land classes, to predict the distributions of each vector and host species. We then compared the predicted distribution of each species with cover of each land class.
RESULTS: Fine-scale distribution maps were generated for three macaque host species (Macaca fascicularis, M. nemestrina and M. leonina) and two mosquito vector complexes (the Dirus Complex and the Leucosphyrus Complex). The Leucosphyrus Complex was predicted to occur in areas with disturbed, but not intact, forest cover (> 60% tree cover) whereas the Dirus Complex was predicted to occur in areas with 10-100% tree cover as well as vegetation mosaics and cropland. Of the macaque species, M. nemestrina was mainly predicted to occur in forested areas whereas M. fascicularis was predicted to occur in vegetation mosaics, cropland, wetland and urban areas in addition to forested areas.
CONCLUSIONS: The predicted M. fascicularis distribution encompassed a wide range of habitats where humans are found. This is of most significance in the northern part of its range where members of the Dirus Complex are the main P. knowlesi vectors because these mosquitoes were also predicted to occur in a wider range of habitats. Our results support the hypothesis that conversion of intact forest into disturbed forest (for example plantations or timber concessions), or the creation of vegetation mosaics, will increase the probability that members of the Leucosphyrus Complex occur at these locations, as well as bringing humans into these areas. An explicit analysis of disease risk itself using infection data is required to explore this further. The species distributions generated here can now be included in future analyses of P. knowlesi infection risk.
METHODOLOGY/PRINCIPAL FINDINGS: A total of 439 records of P. knowlesi infections in humans, macaque reservoir and vector species were collated. To predict spatial variation in disease risk, a model was fitted using records from countries where the infection data coverage is high. Predictions were then made throughout Southeast Asia, including regions where infection data are sparse. The resulting map predicts areas of high risk for P. knowlesi infection in a number of countries that are forecast to be malaria-free by 2025 (Malaysia, Cambodia, Thailand and Vietnam) as well as countries projected to be eliminating malaria (Myanmar, Laos, Indonesia and the Philippines).
CONCLUSIONS/SIGNIFICANCE: We have produced the first map of P. knowlesi malaria risk, at a fine-scale resolution, to identify priority areas for surveillance based on regions with sparse data and high estimated risk. Our map provides an initial evidence base to better understand the spatial distribution of this disease and its potential wider contribution to malaria incidence. Considering malaria elimination goals, areas for prioritised surveillance are identified.