METHODS: Phylogenetic analysis of locally acquired P. knowlesi infections, based on circumsporozoite, small subunit ribosomal ribonucleic acid (SSU rRNA), merozoite surface protein 1 and COX1 gene targets, was performed. The results were compared with the published sequences of regional isolates from Malaysia and Thailand.
RESULTS: Phylogenetic analysis of the circumsporozoite, SSU rRNA and merozoite surface protein 1 gene sequences for regional P. knowlesi isolates showed no obvious differentiation that could be attributed to their geographical origin. However, COX1 gene analysis showed that it was possible to differentiate between Singapore-acquired P. knowlesi infections and P. knowlesi infections from Peninsular Malaysia and Sarawak, Borneo, Malaysia.
CONCLUSION: The ability to differentiate between locally acquired P. knowlesi infections and imported P. knowlesi infections has important utility for the monitoring of P. knowlesi malaria control programmes in Singapore.
METHODS: A total of 1917 samples with adequate volume for RT-PCR analysis were collected from patients hospitalised with HFMD throughout Vietnam and 637 were positive for EV71. VP1 gene (n=87) and complete genome (n=9) sequencing was performed. Maximum-likelihood phylogenetic analysis was performed to characterise the B5, C4 and C5 strains detected.
RESULTS: Sequence analyses revealed that the dominant subgenogroup associated with the 2012 outbreak was C4, with B5 and C5 strains representing a small proportion of these cases.
CONCLUSIONS: Numerous countries in the region including Malaysia, Taiwan and China have a large influence on strain diversity in Vietnam and understanding the transmission of EV71 throughout Southeast Asia is vital to inform preventative public health measures and vaccine development efforts.
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.