To ensure that malaria transmission continues to decline in the Asia-Pacific region, it is critical that national malaria control programs be able to more efficiently target specific areas of high transmission and populations at highest risk. In order to do this they need to be able to accurately identify and delineate pockets of residual transmission and identify the presence and nature of high-risk groups. This will require new approaches and more efficient epidemiological study designs that are based on an in-depth understanding of key host and parasite factors that contribute to sustaining residual transmission in different scenarios. In particular, unraveling the biological basis (e.g. parasite population genetics, host genetics, immunity) for the relatively high prevalence of asymptomatic infections is now more important than ever before. The overall aim of the Asia-Pacific ICEMR Epidemiology Project is thus to better understand host and parasite factors that contribute to sustaining residual malaria transmission despite intensified control and to apply this knowledge to develop novel ways of accurately identifying and delineating pockets of residual transmission. In order to achieve this spatio-temporal patterns of risk of malaria infection and disease will be investigated through a combination of large cross-sectional and longitudinal cohort studies that combine rigorous epidemiological study designs with state-of-the-art molecular detection and genotyping of Plasmodium spp. infections and an assessment of host immune responses and their link to exposure and protection from clinical symptoms of malaria. This information will then be used to evaluate improved surveillance strategies through an innovative combination of computer simulations and field application. This combination of in-depth malaria epidemiology, ecology and application of molecular and antibody profiling feeding into mathematical modeling to allow in silico experimentation, followed by application in the field is highly innovative and has previously received very little attention in the context of malaria surveillance.
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Lerch, Anita; Koepfli, Cristian; Hofmann, Natalie E et al. (2017) Development of amplicon deep sequencing markers and data analysis pipeline for genotyping multi-clonal malaria infections. BMC Genomics 18:864 |
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