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.
METHODS: A total of 95 blood samples from long-tailed macaques in the Philippines were collected from three locations; 30 were from captive macaques at the National Wildlife Rescue and Rehabilitation Center (NWRRC) in Luzon, 25 were from captive macaques at the Palawan Wildlife Rescue and Conservation Center (PWRCC) in Palawan and 40 were from wild macaques from Puerto Princesa Subterranean River National Park (PPSRNP) in Palawan. The Plasmodium spp. infecting the macaques were identified using nested PCR assays on DNA extracted from these blood samples.
RESULTS: All 40 of the wild macaques from PPSRNP in Palawan and 5 of 25 captive macaques from PWRCC in Palawan were Plasmodium-positive; while none of the 30 captive macaques from the NWRRC in Luzon had any malaria parasites. Overall, P. inui was the most prevalent malaria parasite (44.2%), followed by P. fieldi (41.1%), P. cynomolgi (23.2%), P. coatneyi (21.1%), and P. knowlesi (19%). Mixed species infections were also observed in 39 of the 45 Plasmodium-positive macaques. There was a significant difference in the prevalence of P. knowlesi among the troops of wild macaques from PPSRNP.
CONCLUSION: Wild long-tailed macaques from the island of Palawan, the Philippines are infected with P. knowlesi, P. inui, P. coatneyi, P. fieldi and P. cynomolgi. The prevalence of these Plasmodium spp. varied among the sites of collection and among troops of wild macaques at one site. The presence of these simian Plasmodium parasites, especially P. knowlesi and P. cynomolgi in the long-tailed macaques in Palawan presents risks for zoonotic transmission in the area.
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.