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Malaria transmission is heterogeneous in the Greater Mekong Subregion with most of the cases occurring along international borders. Knowledge of transmission hotspots is essential for targeted malaria control and elimination in this region. This study aimed to determine the dynamics of malaria transmission and possible existence of transmission hotspots on a microgeographical scale along the China-Myanmar border. Microscopically confirmed clinical malaria cases were recorded in five border villages through a recently established surveillance system between January 2011 and December 2014. A total of 424 clinical cases with confirmed spatial and temporal information were analyzed, of which 330 (77.8%) were Plasmodium vivax and 88 (20.8%) were Plasmodium falciparum, respectively. The P. vivax and P. falciparum case ratio increased dramatically from 2.2 in 2011 to 4.7 in 2014, demonstrating that P. vivax malaria has become the predominant parasite species. Clinical infections showed a strong bimodal seasonality. There were significant differences in monthly average incidence rates among the study villages with rates in a village in China being 3-8 folds lower than those in nearby villages in Myanmar. Spatial analysis revealed the presence of clinical malaria hotspots in four villages. This information on malaria seasonal dynamics and transmission hotspots should be harnessed for planning targeted control.

Understanding disease vector composition is of priority in designing effective disease control programs. In integrated vector control management, understanding of disease vector species among species complexes simplifies priorities for effective control tools selection. This study identified members of the Anopheles funestus complex sampled in western Kenya from 2002 to 2011 from different breeding sites. Larval sampling was carried out using the standard dipper (350ml) in larval habitats in western Kenya highlands from January 2002 to December 2012. The morphologically identified An. funestus larvae were preserved in absolute ethanol for molecular identification using polymerase chain reaction (PCR). Among the 184 identified specimens of An. funestus sampled, only 76 specimens were clearly identified after DNA amplification and PCR. Among these, 25 (32.9%) were An. funestus s.s, 22 (28.9%) An. leesoni, 9 (11.8%) An. rivulorum and 20 (26.3%) were An. vaneedeni. None was identified as An. parensis. This study has demonstrated the existence of the siblings species of An. funestus complex in western Kenya highlands. However, there is need for further studies to evaluate the dynamics of the adults and sporozoite infectivity rates throughout the region based on these findings.

Levels of genetic diversity of the malaria parasites and multiclonal infections are correlated with transmission intensity. In order to monitor the effect of strengthened malaria control efforts in recent years at the China-Myanmar border area, we followed the temporal dynamics of genetic diversity of three polymorphic antigenic markers msp1, msp2, and glurp in the Plasmodium falciparum populations. Despite reduced malaria prevalence in the region, parasite populations exhibited high levels of genetic diversity. Genotyping 258 clinical samples collected in four years detected a total of 22 PCR size alleles. Multiclonal infections were detected in 45.7% of the patient samples, giving a minimum multiplicity of infection of 1.41. The majority of alleles experienced significant temporal fluctuations through the years. Haplotype diversity based on the three-locus genotypes ranged from the lowest in 2009 at 0.33 to the highest in 2010 at 0.80. Sequencing of msp1 fragments from 36 random samples of five allele size groups detected 13 different sequences, revealing an additional layer of genetic complexity. This study suggests that despite reduced prevalence of malaria infections in this region, the parasite population size and transmission intensity remained high enough to allow effective genetic recombination of the parasites and continued maintenance of genetic diversity.

Despite significant improvement in the malaria situation of the Greater Mekong Subregion (GMS), malaria control for the region continues to face a multitude of challenges. The extremely patchy malaria distribution, especially along international borders, makes disease surveillance and targeted control difficult. The vector systems are also diverse with dramatic differences in habitat ecology, biting behavior, and vectorial capacity, and there is a lack of effective transmission surveillance and control tools. Finally, in an era of heavy deployment of artemisinin-based combination therapies, the region acts as an epicenter of drug resistance, with the emergence of artemisinin resistant Plasmodium falciparum posing a threat to both regional and global malaria elimination campaigns. This problem is further exacerbated by the circulation of counterfeit and substandard artemisinin drugs. Accordingly, this Southeast Asian Malaria Research Center, consisting of a consortium of US and regional research institutions, has proposed four interlinked projects to address these most urgent problems in malaria control. The aims of these projects will help to substantially improve our understanding of malaria epidemiology, vector systems and their roles in malaria transmission, as well as the mechanisms of drug resistance in parasites. Through the training of next-generation scientists in malaria research, this program will help build up and strengthen regional research infrastructure and capacities, which are essential for sustained malaria control in this region.

The Greater Mekong Subregion (GMS), comprised of six countries including Cambodia, China's Yunnan Province, Lao PDR, Myanmar (Burma), Thailand and Vietnam, is one of the most threatening foci of malaria. Since the initiation of the WHO's Mekong Malaria Program a decade ago, malaria situation in the GMS has greatly improved, reflected in the continuous decline in annual malaria incidence and deaths. However, as many nations are moving towards malaria elimination, the GMS nations still face great challenges. Malaria epidemiology in this region exhibits enormous geographical heterogeneity with Myanmar and Cambodia remaining high-burden countries. Within each country, malaria distribution is also patchy, exemplified by 'border malaria' and 'forest malaria' with high transmission occurring along international borders and in forests or forest fringes, respectively. 'Border malaria' is extremely difficult to monitor, and frequent malaria introductions by migratory human populations constitute a major threat to neighboring, malaria-eliminating countries. Therefore, coordination between neighboring countries is essential for malaria elimination from the entire region. In addition to these operational difficulties, malaria control in the GMS also encounters several technological challenges. Contemporary malaria control measures rely heavily on effective chemotherapy and insecticide control of vector mosquitoes. However, the spread of multidrug resistance and potential emergence of artemisinin resistance in Plasmodium falciparum make resistance management a high priority in the GMS. This situation is further worsened by the circulation of counterfeit and substandard artemisinin-related drugs. In most endemic areas of the GMS, P. falciparum and Plasmodium vivax coexist, and in recent malaria control history, P. vivax has demonstrated remarkable resilience to control measures. Deployment of the only registered drug (primaquine) for the radical cure of vivax malaria is severely undermined due to high prevalence of glucose-6-phosphate dehydrogenase deficiency in target human populations. In the GMS, the dramatically different ecologies, diverse vector systems, and insecticide resistance render traditional mosquito control less efficient. Here we attempt to review the changing malaria epidemiology in the GMS, analyze the vector systems and patterns of malaria transmission, and identify the major challenges the malaria control community faces on its way to malaria elimination.

The increasing spread of multi-drug resistant malaria in African highlands has highlighted the importance of malaria suppression through vector control. Its historical success has meant that larval control has been proposed as part of an integrated malaria vector control program. Due to high operation costs, larval control activities would benefit greatly if the locations of mosquito habitats could be identified quickly and easily, allowing for focal habitat source suppression. Several mosquito habitat models have been developed to predict the location of mosquito habitats. However, to what extent these models can be generalised across time and space to predict the distribution of dynamic mosquito habitats remains largely unexplored. This study used mosquito habitat data collected in six different time periods and four different modelling approaches to establish 24 mosquito habitat models. We systematically tested the generality of these 24 mosquito habitat models. We found that although habitat--environment relationships change temporally, a modest level of performance was attained when validating the models using data collected from different time periods. We also describe flexible approaches to the predictive modelling of mosquito habitats, that provide novel modelling architecture for future research efforts.

In the tropics, Anopheles mosquito abundance is greatest during the wet season and decline significantly during the dry season as larval habitats shrink. Population size fluctuations between wet and dry seasons may lead to variation in distribution of specific alleles within natural Anopheles populations, and a possible effect on the population genetic structure. We used 11 microsatellite markers to examine the effect of seasonality on population genetic structure of Anopheles gambiae s.s. at two sites along the Kenyan coast. All loci were highly polymorphic with the total number of alleles for pooled samples ranging from 7 (locus ND36) to 21 (locus AG2H46). Significant estimates of genetic differentiation between sites and seasons were observed suggesting the existence of spatio-temporal subpopulation structuring. Genetic bottleneck analysis showed no indication of excess heterozygosity in any of the populations. These findings suggest that along the Kenyan coast, seasonality and site specific ecological factors can alter the genetic structure of A. gambiae s.s. populations.