After a marked reduction in malaria burden in Cambodia over the last decades, case numbers increased again in 2017–2018. In light of the national goal of malaria elimination by 2025, remaining pockets of high risk need to be well defined and strategies well-tailored to identify and target the persisting burden cost-effectively. This study presents species-specific prevalence estimates and risk stratification for a remote area in Cambodia.
Genetic surveillance of malaria parasites supports malaria control programmes, treatment guidelines and elimination strategies. Surveillance studies often pose questions about malaria parasite ancestry (e.g. how antimalarial resistance has spread) and employ statistical methods that characterise parasite population structure. Many of the methods used to characterise structure are unsupervised machine learning algorithms which depend on a genetic distance matrix, notably principal coordinates analysis (PCoA) and hierarchical agglomerative clustering (HAC).
Clinical failure of primaquine (PQ) has been demonstrated in people with CYP450 2D6 genetic polymorphisms that result in reduced or no enzyme activity. The distribution of CYP2D6 genotypes and predicted phenotypes in the Cambodian population is not well described. Surveys in other Asian countries have shown an approximate 50% prevalence of the reduced activity CYP2D6 allele *10, which could translate into increased risk of PQ radical cure failure and repeated relapses, making interruption of transmission and malaria elimination difficult to achieve.
High rates of dihydroartemisinin–piperaquine (DHA–PPQ) treatment failures have been documented for uncomplicated Plasmodium falciparum in Cambodia. The genetic markers plasmepsin 2 (pfpm2), exonuclease (pfexo) and chloroquine resistance transporter (pfcrt) genes are associated with PPQ resistance and are used for monitoring the prevalence of drug resistance and guiding malaria drug treatment policy.
In the absence of an effective vaccine, the efficacy of antimalarial chemotherapies underpins the success of malaria control programmes. Artemisinin-based combination therapies (ACTs), which combine fast-acting artemisinin derivatives and longer-acting partner drugs, are the mainstay of treatment of uncomplicated falciparum malaria in endemic regions.
Artesunate-amodiaquine is a potential therapy for uncomplicated malaria in Cambodia.
Cambodia has targeted malaria elimination within its territory by 2025 and is developing a model elimination package of strategies and interventions designed to achieve this goal.
Cambodia targets malaria elimination by 2025. Rapid elimination will depend on successfully identifying and clearing malaria foci linked to forests. Expanding and maintaining universal access to early diagnosis and effective treatment remains the key to malaria control and ultimately malaria elimination in the Greater Mekong Subregion (GMS) in the foreseeable future. Mass Drug Administration (MDA) holds some promise in the rapid reduction of Plasmodium falciparum infections, but requires considerable investment of resources and time to mobilize the target communities.
Understanding the genetic structure of natural populations provides insight into the demographic and adaptive processes that have affected those populations. Such information, particularly when integrated with geospatial data, can have translational applications for a variety of fields, including public health. Estimated effective migration surfaces (EEMS) is an approach that allows visualization of the spatial patterns in genomic data to understand population structure and migration. In this study, we developed a workflow to optimize the resolution of spatial grids used to generate EEMS migration maps and applied this optimized workflow to estimate migration of Plasmodium falciparum in Cambodia and bordering regions of Thailand and Vietnam.
Aedes-transmitted diseases, especially dengue, are increasing throughout the world and the main preventive methods include vector control and the avoidance of mosquito bites. A simple Premise Condition Index (PCI) categorizing shade, house, and yard conditions was previously developed to help prioritize households or geographical areas where resources are limited. However, evidence about the accuracy of the PCI is mixed.