METHODS: We did an environmentally stratified, population-based, cross-sectional survey across households in the Kudat, Kota Marudu, Pitas, and Ranau districts in northern Sabah, Malaysia, encompassing a range of ecologies. Using blood samples, the transmission intensity of P knowlesi and other malaria species was measured by specific antibody prevalence and infection detected using molecular methods. Proportions and configurations of land types were extracted from maps derived from satellite images; a data-mining approach was used to select variables. A Bayesian hierarchical model for P knowlesi seropositivity was developed, incorporating questionnaire data about individual and household-level risk factors with selected landscape factors.

FINDINGS: Between Sept 17, 2015, and Dec 12, 2015, 10 100 individuals with a median age of 25 years (range 3 months to 105 years) were sampled from 2849 households in 180 villages. 5·1% (95% CI 4·8-5·4) were seropositive for P knowlesi, and marked historical decreases were observed in the transmission of Plasmodium falciparum and Plasmodium vivax. Nine Plasmodium spp infections were detected. Age, male sex, contact with macaques, forest use, and raised house construction were positively associated with P knowlesi exposure, whereas residing at higher geographical elevations and use of insecticide were protective. Agricultural and forest variables, such as proportions and fragmentation of land cover types, predicted exposure at different spatial scales from households.

INTERPRETATION: Although few infections were detected, P knowlesi exposure was observed in all demographic groups and was associated with occupational factors. Results suggest that agricultural expansion and forest fragmentation affect P knowlesi exposure, supporting linkages between land use change and P knowlesi transmission.

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).

METHODOLOGY/PRINCIPAL FINDINGS: Anopheles spp. were sampled using human landing catch (HLC) method at Paradason village in Kudat district of Sabah. The collected Anopheles were identified morphologically and then subjected to total DNA extraction and polymerase chain reaction (PCR) to detect Plasmodium parasites in the mosquitoes. Identification of Plasmodium spp. was confirmed by sequencing the SSU rRNA gene with species specific primers. MEGA4 software was then used to analyse the SSU rRNA sequences and bulid the phylogenetic tree for inferring the relationship between simian malaria parasites in Sabah. PCR results showed that only 1.61% (23/1,425) of the screened An. balabacensis were infected with one or two of the five simian Plasmodium spp. found in Sabah, viz. Plasmodium coatneyi, P. inui, P. fieldi, P. cynomolgi and P. knowlesi. Sequence analysis of SSU rRNA of Plasmodium isolates showed high percentage of identity within the same Plasmodium sp. group. The phylogenetic tree based on the consensus sequences of P. knowlesi showed 99.7%-100.0% nucleotide identity among the isolates from An. balabacensis, human patients and a long-tailed macaque from the same locality.