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 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.
METHODS: Plasma Flt3L concentration and blood CD141+ DC, CD1c+ DC and plasmacytoid DC (pDC) numbers were assessed in (i) volunteers experimentally infected with P. falciparum and in Malaysian patients with uncomplicated (ii) P. falciparum or (iii) P. knowlesi malaria.
RESULTS: Plasmodium knowlesi caused a decline in all circulating DC subsets in adults with malaria. Plasma Flt3L was elevated in acute P. falciparum and P. knowlesi malaria with no increase in a subclinical experimental infection. Circulating CD141+ DCs, CD1c+ DCs and pDCs declined in all adults tested, for the first time extending the finding of DC subset decline in acute malaria to the zoonotic parasite P. knowlesi.
CONCLUSIONS: In adults, submicroscopic Plasmodium infection causes no change in plasma Flt3L but does reduce circulating DCs. Plasma Flt3L concentrations increase in acute malaria, yet this increase is insufficient to restore or expand circulating CD141+ DCs, CD1c+ DCs or pDCs. These data imply that haematopoietic factors, yet to be identified and not Flt3L, involved in the sensing/maintenance of circulating DC are impacted by malaria and a submicroscopic infection. The zoonotic P. knowlesi is similar to other Plasmodium spp in compromising DC in adult malaria.
METHODS: Mosquitoes found landing on humans and resting on leaves over a 5-day period at two sites in the Lawas District of northern Sarawak were collected and identified. DNA samples extracted from salivary glands of Anopheles mosquitoes were subjected to nested PCR malaria-detection assays. The small subunit ribosomal RNA (SSU rRNA) gene of Plasmodium was sequenced, and the internal transcribed spacer 2 (ITS2) and mitochondrial cytochrome c oxidase subunit 1 (cox1) gene of the mosquitoes were sequenced from the Plasmodium-positive samples for phylogenetic analysis.
RESULTS: Totals of 65 anophelines and 127 culicines were collected. By PCR, 6 An. balabacensis and 5 An. donaldi were found to have single P. knowlesi infections while 3 other An. balabacensis had either single, double or triple infections with P. inui, P. fieldi, P. cynomolgi and P. knowlesi. Phylogenetic analysis of the Plasmodium SSU rRNA gene confirmed 3 An. donaldi and 3 An. balabacensis with single P. knowlesi infections, while 3 other An. balabacensis had two or more Plasmodium species of P. inui, P. knowlesi, P. cynomolgi and some species of Plasmodium that could not be conclusively identified. Phylogenies inferred from the ITS2 and/or cox1 sequences of An. balabacensis and An. donaldi indicate that they are genetically indistinguishable from An. balabacensis and An. donaldi, respectively, found in Sabah, Malaysian Borneo.
CONCLUSIONS: Previously An. latens was identified as the vector for P. knowlesi in Kapit, central Sarawak, Malaysian Borneo, and now An. balabacensis and An. donaldi have been incriminated as vectors for zoonotic malaria in Lawas, northern Sarawak.
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.