Abstract.Sensitive field-deployable diagnostic tests can assist malaria programs in achieving elimination. The performance of a new Alere™ Malaria Ag P.f Ultra Sensitive rapid diagnostic test (uRDT) was compared with the currently available SD Bioline Malaria Ag P.f RDT in blood specimens from asymptomatic individuals in Nagongera, Uganda, and in a Karen Village, Myanmar, representative of high- and low-transmission areas, respectively, as well as in pretreatment specimens from study participants from four Plasmodium falciparum-induced blood-stage malaria (IBSM) studies. A quantitative reverse transcription PCR (qRT-PCR) and a highly sensitive enzyme-linked immunosorbent assay (ELISA) test for histidine-rich protein II (HRP2) were used as reference assays. The uRDT showed a greater than 10-fold lower limit of detection for HRP2 compared with the RDT. The sensitivity of the uRDT was 84% and 44% against qRT-PCR in Uganda and Myanmar, respectively, and that of the RDT was 62% and 0% for the same two sites. The specificities of the uRDT were 92% and 99.8% against qRT-PCR for Uganda and Myanmar, respectively, and 99% and 99.8% against the HRP2 reference ELISA. The RDT had specificities of 95% and 100% against qRT-PCR for Uganda and Myanmar, respectively, and 96% and 100% against the HRP2 reference ELISA. The uRDT detected new infections in IBSM study participants 1.5 days sooner than the RDT. The uRDT has the same workflow as currently available RDTs, but improved performance characteristics to identify asymptomatic malaria infections. The uRDT may be a useful tool for malaria elimination strategies.

Local and cross-border importation remain major challenges to malaria elimination and are difficult to measure using traditional surveillance data. To address this challenge, we systematically collected parasite genetic data and travel history from thousands of malaria cases across northeastern Namibia and estimated human mobility from mobile phone data. We observed strong fine-scale spatial structure in local parasite populations, providing positive evidence that the majority of cases were due to local transmission. This result was largely consistent with estimates from mobile phone and travel history data. However, genetic data identified more detailed and extensive evidence of parasite connectivity over hundreds of kilometers than the other data, within Namibia and across the Angolan and Zambian borders. Our results provide a framework for incorporating genetic data into malaria surveillance and provide evidence that both strengthening of local interventions and regional coordination are likely necessary to eliminate malaria in this region of Southern Africa.

The growing prevalence of deadly microbes with resistance to previously life-saving drug therapies is a dire threat to human health. Detection of low abundance pathogen sequences remains a challenge for metagenomic Next Generation Sequencing (NGS). We introduce FLASH (Finding Low Abundance Sequences by Hybridization), a next-generation CRISPR/Cas9 diagnostic method that takes advantage of the efficiency, specificity and flexibility of Cas9 to enrich for a programmed set of sequences. FLASH-NGS achieves up to 5 orders of magnitude of enrichment and sub-attomolar gene detection with minimal background. We provide an open-source software tool (FLASHit) for guide RNA design. Here we applied it to detection of antimicrobial resistance genes in respiratory fluid and dried blood spots, but FLASH-NGS is applicable to all areas that rely on multiplex PCR.

As many malaria-endemic countries move towards elimination of Plasmodium falciparum, the most virulent human malaria parasite, effective tools for monitoring malaria epidemiology are urgent priorities. P. falciparum population genetic approaches offer promising tools for understanding transmission and spread of the disease, but a high prevalence of multi-clone or polygenomic infections can render estimation of even the most basic parameters, such as allele frequencies, challenging. A previous method, COIL, was developed to estimate complexity of infection (COI) from single nucleotide polymorphism (SNP) data, but relies on monogenomic infections to estimate allele frequencies or requires external allele frequency data which may not available. Estimates limited to monogenomic infections may not be representative, however, and when the average COI is high, they can be difficult or impossible to obtain. Therefore, we developed THE REAL McCOIL, Turning HEterozygous SNP data into Robust Estimates of ALelle frequency, via Markov chain Monte Carlo, and Complexity Of Infection using Likelihood, to incorporate polygenomic samples and simultaneously estimate allele frequency and COI. This approach was tested via simulations then applied to SNP data from cross-sectional surveys performed in three Ugandan sites with varying malaria transmission. We show that THE REAL McCOIL consistently outperforms COIL on simulated data, particularly when most infections are polygenomic. Using field data we show that, unlike with COIL, we can distinguish epidemiologically relevant differences in COI between and within these sites. Surprisingly, for example, we estimated high average COI in a peri-urban subregion with lower transmission intensity, suggesting that many of these cases were imported from surrounding regions with higher transmission intensity. THE REAL McCOIL therefore provides a robust tool for understanding the molecular epidemiology of malaria across transmission settings.

Background To better understand transmission dynamics, we characterized Plasmodium falciparum genetic diversity in Eswatini, where transmission is low and sustained by importation. Methods Twenty-six P. falciparum microsatellites were genotyped in 66% of confirmed cases (2014–2016; N = 582). Population and within-host diversity were used to characterize differences between imported and locally acquired infections. Logistic regression was used to assess the added value of diversity metrics to classify imported and local infections beyond epidemiology data alone. Results Parasite population in Eswatini was highly diverse (expected heterozygosity [HE] = 0.75) and complex: 67% polyclonal infections, mean multiplicity of infection (MOI) 2.2, and mean within-host infection fixation index (FWS) 0.84. Imported cases had comparable diversity to local cases but exhibited higher MOI (2.4 vs 2.0; P = .004) and lower mean FWS (0.82 vs 0.85; P = .03). Addition of MOI and FWS to multivariate analyses did not increase discrimination between imported and local infections. Conclusions In contrast to the common perception that P. falciparum diversity declines with decreasing transmission intensity, Eswatini isolates exhibited high parasite diversity consistent with high rates of malaria importation and limited local transmission. Estimates of malaria transmission intensity from genetic data need to consider the effect of importation, especially as countries near elimination.