Major advances in Plasmodium sequencing approaches, bioinformatic pipelines, and data analysis tools have provided valuable insights into malaria epidemiology from parasite genomic data. However, translating genetic data into actionable information for decision-makers remains a challenge. Significant barriers limit the integration of these advances into a functional data analysis ecosystem that produces standardized, interpretable results for use by national malaria control programs. The Plasmodium Genomic Epidemiology (PlasmoGenEpi) network convened 18 subject matter experts across 15 institutions at the Reproducibility, Accessibility, Documentation, and Interoperability Standards Hackathon in 2023 (RADISH23) to identify available analysis tools, evaluate software standards, improve documentation, and outline workflows. Eight use cases for genomic data were identified, and a subset were developed into analysis workflows in terms of a series of connected functionalities. Software tools were then mapped against functionalities to outline a modular approach to data analysis for these use cases. In addition to outlining workflows, a set of objective criteria were developed for evaluating software standards. Forty Plasmodium genomic analysis tools were identified, of which 22 were prioritized for software standards evaluation. Additional tutorials were developed for 10 tools in the form of reproducible code applied to shared datasets. These resources are available on PGEforge (mrc-ide.github.io/PGEforge), a new community resource that serves as a central, open repository for current and future resources for malaria genomic data analysis.

Reliable assessment of antimalarial drug efficacy is crucial for an effective response to emerging drug resistance, and therapeutic efficacy studies (TESs) are the primary means of estimating in vivo efficacy. The accuracy of such estimates rests on correctly classifying recurrent infections developed during follow-up as recrudescences or new infections. Genotyping is used to guide classification, but polyclonal infections and alleles matching by chance make classification challenging, especially in high transmission settings. Match-counting algorithms currently recommended by the World Health Organization are unreliable and produce biased results, necessitating the development of principled statistical approaches. Modern genotyping methods, such as multiplexed amplicon sequencing, hold great potential for resolving recurrences and motivate the need for corresponding statistical methods able to utilize the rich data they provide. We propose an Adaptive Statistical framework for Therapeutic Efficacy and Recrudescence (Aster) that delivers accurate and consistent results by explicitly incorporating the complexity of infection, population allele frequencies, and imperfect detection of alleles in minority strains. Using an identity-by-descent approach, Aster accounts for alleles matching by chance and for a background infection relatedness structure that can otherwise lead to misclassification. The flexible framework can also use external information, such as parasite density and performance characteristics of a genotyping panel. Using simulations, we show that Aster dramatically outperforms match-counting algorithms in a wide variety of transmission settings and demonstrates consistently balanced performance that improves with more informative genotyping panels. Aster is implemented in a fast, fully scalable, and user-friendly R software package, asterTES, and provides accurate estimates of treatment failure for TES with any type of genotyping data, facilitating reliable evaluation of drug efficacy and effective management of malaria.

Background:Malaria transmission in southwestern Uganda is low, but persists despite ongoing control efforts. Identifying whether infections are locally sustained or imported by travelers is critical for guiding interventions. We integrated epidemiologic surveillance with parasite genomics to characterize imported malaria episodes at three health facilities in southwestern Uganda. Methods:Between January 2023 and June 2024, we enrolled microscopy-confirmed malaria cases at three health facilities, Maziba and Muko (very low transmission) and Kamwezi (low-to-moderate transmission), administered travel history questionnaires, and collected dried blood spots for genotyping. Plasmodium falciparum infections were genotyped using MAD4HatTeR, a highly sensitive multiplex amplicon sequencing panel targeting 165 diversity markers and 38 drug resistance loci. Complexity of infection and pairwise relatedness were estimated using MOIRE and Dcifer, respectively. Plasmotrack, a Bayesian transmission network framework, was used to infer network structure, transmission directionality, reproduction numbers, and importation rates. Results:Amongst malaria cases, recent overnight travel was common in Maziba (87%) and Muko (96%) but infrequent in Kamwezi (12%). Most travel in cases from Maziba and Muko was from high-transmission regions in northern and eastern Uganda. Parasites in Maziba and Muko cases exhibited higher within-host diversity and lower within-site relatedness compared to those in Kamwezi cases. Transmission network inference identified most infections in Maziba and Muko as imported, with the majority of inferred secondary transmission linked to recent travelers. In contrast, Kamwezi showed multiple highly related clusters, indicating sustained local transmission. Validated and candidate markers of artemisinin partial resistance (K13 P441L and R561H) were more prevalent in Kamwezi. Conclusion:Malaria in Maziba and Muko was driven largely by importation from other parts of Uganda, while local transmission played a larger role in Kamwezi . Tailored interventions addressing travel-associated risks and local transmission, supported by travel histories and parasite genetic data will be valuable to advance malaria elimination in this region.

Abstract Motivation Molecular surveillance and infectious disease transmission network reconstruction can provide compelling evidence for estimating public-health quantities that are difficult to observe directly, including importation, source-sink structure, and differences in onward transmission across locations or intervention strata. These quantities can be expressed as functions of the underlying transmission network, but individual transmission events are rarely observed and many networks may be consistent with the same data. Existing transmission network reconstruction methods leveraging genetic data are often built for settings in which each infection has one dominant source, one representative haplotype, and mutation-driven genetic divergence along transmission chains. These assumptions are poorly matched to polyclonal infections, in which hosts carry multiple genetically distinct clones and recipient infections may reflect contributions from multiple sources. Such infections are common in malaria, tuberculosis, HIV, and many parasitic infections. Methods are needed that can accommodate these data. Results We present a modular Bayesian framework for estimating directed transmission on sampled cases, where an infection may have no sampled parent, one parent, or several parents, including sources outside the observed panel. Pathogen-specific modules supply likelihoods over candidate parent sets and connect to shared inference that yields marginal directed edge probabilities, posterior mean out-degree, and inclusion probabilities for unobserved parents. We demonstrate our framework with Plasmotrack, a transmission network model for Plasmodium falciparum that uses targeted amplicon sequencing data. We implemented these components with a per-locus allele-mixture transmission likelihood, an amplicon genotyping error model, and data augmentation allowing for unobserved parents. Simulations from a biologically informed generative model, under which the inferential per-locus allele-mixture likelihood is misspecified, showed recovery of aggregate network summaries including mean outdegree and mean unobserved-source inclusion, alongside high precision and recall for detecting directed transmission. Other pathogens can reuse the same modular composition after substituting transmission and observation likelihoods. Availability The Plasmotrack software and documentation are available at https://github.com/eppicenter/plasmotrack . Source code and example datasets are provided under an open-source license. Contact maxwell.murphy@ucsf.edu

Imported malaria is a critical obstacle to achieving elimination in low transmission settings, but importation classification tools combining human mobility and parasite genomics are lacking. A Bayesian model combining epidemiological, human mobility, and parasite genetic data was developed to estimate malaria importation and geographic origins of Plasmodium falciparum cases. Using microhaplotype-based genetic relatedness from 1605 samples across nine Mozambican provinces in 2022, the study focused on two low-transmission districts in the south: Magude and Matutuine. Parasites from southern Mozambique showed lower genetic relatedness to those from northern/central regions (0.021) than the national average (0.034, p<0.001), indicating limited connectivity. Overall, 42% (88/207) of infections in these districts were classified as imported, mainly originating from Inhambane province (63% [55/88]). Imported cases showed higher parasite complexity than local ones (odds ratios [OR] = 1.3). Importation rates differed markedly between districts – Matutuine (48.60%, 87/179) was far more affected than Magude (10.71%, 3/28) – highlighting the need for localised rather than uniform elimination strategies. In Matutuine, importation appears to be actively sustaining transmission, suggesting that reducing malaria burden in source regions (particularly Inhambane) and targeting travellers from central and northern Mozambique would have the greatest elimination impact.

Seasonal movement of less-immune people from low- to high- transmission regions increases malaria risk and may introduce parasite strains to both areas. This study examined Plasmodium falciparum genetic diversity and connectivity between low-transmission highlands and endemic lowlands in Ethiopia to assess the contribution of seasonal agricultural migration in sustaining transmission. P. falciparum qPCR-positive dried blood spots collected from highland health facilities and lowland agricultural worksites were sequenced using multiplexed amplicon sequencing. Complexity of infection (COI) and infection pairwise relatedness were estimated and used for clustering analysis. Lowland populations (seasonal workers and local residents) had higher COI and polyclonal infection rates (mean COI 2.62, 60%, n=581) than highland residents (mean COI 2.00, 42%, n=599). Similar expected heterozygosity (He ≈0.4) was observed, and P. falciparum infections from worksites showed high genetic connectivity between highland and lowland populations, with extensive parasite sharing, including 27 identical clusters in highland cases and 12 in seasonal workers. Integrating parasite genomic data with epidemiological information revealed strong connectivity and low genetic differentiation between these regions linked by seasonal migration. These findings highlight how agricultural mobility likely drives parasite diversity and gene flow, implicating its role in sustaining malaria transmission.

Motivation:The rapid increase in the generation of targeted sequencing data offers immense potential for research, medicine, and public health, however the lack of an established standard for these data has led to disparate solutions for data storage. A widely accepted standard is essential for data sharing, reuse, and the coordinated development of interoperable analysis tools. Results:We propose the Portable Microhaplotype Object (PMO), a standardized format for efficiently and losslessly storing phased targeted sequencing data (microhaplotypes). The PMO format is JSON-based, allowing efficient, relational storage of genetic data together with relevant metadata to minimize orphaned data. The format includes required fields and a curated set of optional fields leveraging established ontologies. To facilitate ease of use, we developed pmotools-python, an open-source package for creating, manipulating, and exporting PMO data into common formats. Additionally, we provide a simple web-based app to quickly create PMO files from tabular inputs, making the format accessible to a wide variety of users. Example datasets from Plasmodium, Anopheles, Escherichia coli, and Staphylococcus aureus demonstrate the broad applicability of the approach. PMO will streamline data sharing, foster interoperability, and accelerate the development of harmonized analysis tools. Availability and implementation:The Portable Microhaplotype Object (PMO) project, including the ontology specification, software tools, example datasets, and tutorials, is freely available at https://plasmogenepi.github.io/PMO_Docs/. Key software components and datasets have archived releases with DOIs to ensure permanence, detailed in the Supplementary Text 1-5.

Malaria parasite genetic data can provide insight into parasite phenotypes, evolution, and transmission. However, estimating key parameters such as allele frequencies, multiplicity of infection (MOI), and within-host relatedness from genetic data has been challenging, particularly in the presence of multiple related coinfecting strains. Existing methods often rely on single nucleotide polymorphism (SNP) data and do not account for within-host relatedness. In this study, we introduce a Bayesian approach called MOIRE (Multiplicity Of Infection and allele frequency REcovery), designed to estimate allele frequencies, MOI, and within-host relatedness from genetic data subject to experimental error. Importantly, MOIRE is flexible in accommodating both polyallelic and SNP data, making it adaptable to diverse genotyping panels. We also introduce a novel metric, the effective MOI (eMOI), which integrates MOI and within-host relatedness, providing a robust and interpretable measure of genetic diversity. Using extensive simulations and real-world data from a malaria study in Namibia, we demonstrate the superior performance of MOIRE over naive estimation methods, accurately estimating MOI up to 7 with moderate sized panels of diverse loci (e.g. microhaplotypes). MOIRE also revealed substantial heterogeneity in population mean MOI and mean relatedness across health districts in Namibia, suggesting detectable differences in transmission dynamics. Notably, eMOI emerges as a portable metric of within-host diversity, facilitating meaningful comparisons across settings, even when allele frequencies or genotyping panels are different. MOIRE represents an important addition to the analysis toolkit for malaria population dynamics. Compared to existing software, MOIRE enhances the accuracy of parameter estimation and enables more comprehensive insights into within-host diversity and population structure. Additionally, MOIRE's adaptability to diverse data sources and potential for future improvements make it a valuable asset for research on malaria and other organisms, such as other eukaryotic pathogens. MOIRE is available as an R package at https://eppicenter.github.io/moire/.

Background:High-grade Plasmodium falciparum resistance to sulfadoxine-pyrimethamine in East and Southern Africa has prompted numerous trials evaluating intermittent preventive treatment in pregnancy (IPTp) with dihydroartemisinin-piperaquine as an alternative to sulfadoxine-pyrimethamine. Methods:We conducted individual participant data meta-analyses of randomised trials comparing IPTp with dihydroartemisinin-piperaquine to sulfadoxine-pyrimethamine on maternal, birth, and infant outcomes. We searched the WHO International Clinical Trials Registry Platform, ClinicalTrials.Gov, PubMed, and the Malaria in Pregnancy Consortium Library. Eligible trials enrolled HIV-uninfected pregnant women, followed participants to delivery, included participants with no prior IPTp use during the current pregnancy, and were conducted in areas with high-level parasite resistance to sulfadoxine-pyrimethamine (i.e., PfDHPS 540E≥90% and/or 581G>0%). Only singleton pregnancies were analysed. Meta-analyses used a two-stage approach: first, study-specific estimates were generated and then pooled using a random-effects model. Gravidity subgroup analyses were performed. Causal mediation analyses were used to investigate the maternal mechanisms underlying the effect of IPTp regimens on birth outcomes. The meta-analysis is registered in PROSPERO (CRD42020196127). Findings:Of 85 screened records, six trials (one multi-country trial) contributed data on 6646 pregnancies. Compared to sulfadoxine-pyrimethamine, dihydroarteminsinin-piperaquine was associated with a 69% [95% CI: 45%-82%] lower incidence of clinical malaria during pregnancy, a 62% [37%-77%] lower risk of placental parasitaemia, and a 17% [0%-31%] lower incidence of moderate maternal anaemia (Hb<9 g/dL). In contrast, sulfadoxine-pyrimethamine was associated with higher mean weekly maternal weight gain (34 grams/week [17-51]). There were no statistically significant differences in the composite adverse pregnancy outcome between the two IPTp regimens (RR=1·05 [95% CI: 0·92-1·19]; I 2=48%), although the risk of small-for-gestational-age was 15% [3%-24%] lower in the sulfadoxine-pyrimethamine arm. Among multigravidae, participants of the sulfadoxine-pyrimethamine arm were 20% [8%-30%] and 35% [17%-49%] less likely to have stunted and underweight infants by two months compared to the dihydroartemisinin-piperaquine arm. Infant wasting by two months was 13% [3%-22%] lower in the sulfadoxine-pyrimethamine arm, regardless of gravidity. Mediation analyses indicated that 15% [0%-19%] of sulfadoxine-pyrimethamine's superior effect on reducing small-for-gestational-age risk was mediated by its greater impact on gestational weight gain. Interpretation:In areas of high P. falciparum sulfadoxine-pyrimethamine resistance, dihydroartemisin-inpiperaquine is a more efficacious antimalarial than sulfadoxine-pyrimethamine. However, replacing sulfadoxine-pyrimethamine with dihydroartemisinin-piperaquine alone will not result in better maternal, birth, or infant outcomes. It could increase the risk of SGA, since much of the effect of sulfadoxine-pyrimethamine may be exerted through non-malarial mechanisms. Future research evaluating the alternative strategies for IPTp are needed, including with the combination of sulfadoxine-pyrimethamine and dihydroartemisinin-piperaquine. Funding:This work was supported by the Bill and Melinda Gates Foundation and Eunice Kennedy Shriver National Institute of Child Health and Human Development.

While there has been significant progress in controlling falciparum malaria in the Lao People's Democratic Republic (PDR), sporadic cases persist in southern provinces where the extent and patterns of transmission remain largely unknown. To assess parasite transmission in this area, 53 Plasmodium falciparum (Pf) positive cases detected through active test and treat campaigns from December 2017 to November 2018 were sequenced, targeting 204 highly polymorphic amplicons. Two R packages, MOIRE and Dcifer, were applied to assess the multiplicity of infections (MOI), effective MOI (eMOI), within-host parasite relatedness, and between-host parasite relatedness ([Formula: see text]). Genomic data were integrated with survey data to characterize the temporal and spatial structures of identified clusters. The positive cases were mainly captured during the focal test and treat campaign conducted in 2018, and in the Pathoomphone area, which had the highest test positivity and forest activity. About 30% of the cases were polyclonal infections, with over half of theses (63%) showing within-host relatedness greater than 0.6, suggesting that cotransmission rather than superinfection was primarily responsible for maintaining polyclonality. A large majority of cases (81%) were infected by parasites genetically linked to one or more other cases. We identified five genetically distinct clusters in forest fringe villages within the Pathoomphone district, characterized by a high degree of genetic relatedness between parasites (mean [Formula: see text] = 0.8). Four smaller clusters of 2-3 cases linked Moonlapamok and Pathoomphone districts, with an average [Formula: see text] of 0.6, suggesting cross-district transmission. Most of the clustered cases occurred within 20 km and 2 months of each other, consistent with focal transmission. Transmission clusters identified in this study confirm the role of ongoing focal parasite transmission occurring within the forest or forest-fringe in the highly mobile population.

Anopheles stephensi, an Asian malaria vector, continues to expand across Africa. The vector is now firmly established in urban settings in the Horn of Africa. Its presence in areas where malaria resurged suggested a possible role in causing malaria outbreaks. Here, using a prospective case-control design, we investigated the role of An. stephensi in transmission following a malaria outbreak in Dire Dawa, Ethiopia in April-July 2022. Screening contacts of patients with malaria and febrile controls revealed spatial clustering of Plasmodium falciparum infections around patients with malaria in strong association with the presence of An. stephensi in the household vicinity. Plasmodium sporozoites were detected in these mosquitoes. This outbreak involved clonal propagation of parasites with molecular signatures of artemisinin and diagnostic resistance. To our knowledge, this study provides the strongest evidence so far for a role of An. stephensi in driving an urban malaria outbreak in Africa, highlighting the major public health threat posed by this fast-spreading mosquito.

Abstract Anopheles stephensi, an Asian urban malaria vector, continues to expand across Africa. We investigated the role of An. stephensi in malaria transmission following a dry season outbreak in Dire Dawa, Ethiopia, from April to July 2022, using a prospective case control design. Plasmodium falciparum microscopy-positive febrile patients (n = 101) and microscopy-negative controls (n = 189) were identified and their contacts (n = 662) screened. Spatial clustering of P. falciparum infections detected in the case contacts but not the controls which was strongly associated with detection of An. stephensi and the detection of sporozoites provides the strongest evidence to date for a role of An. stephensi in driving an urban malaria outbreak in Africa. Importantly, this outbreak involved clonal propagation of drug and diagnostic resistant parasites. This study provides the first epidemiological direct evidence linking An. stephensi with increase in malaria transmission in Africa, highlighting the major public health threat of this fast-spreading invasive mosquito.

Background Inference of person-to-person transmission networks using surveillance data is increasingly used to estimate spatiotemporal patterns of pathogen transmission. Several data types can be used to inform transmission network inferences, yet the sensitivity of those inferences to different data types is not routinely evaluated. Methods The influence of different combinations of spatial, temporal, and travel-history data on transmission network inferences for Plasmodium falciparum malaria were evaluated. Results The information content of these data types may be limited for inferring person-to-person transmission networks and may lead to an overestimate of transmission. Only when outbreaks were temporally focal or travel histories were accurate was the algorithm able to accurately estimate the reproduction number under control, R-c. Applying this approach to data from Eswatini indicated that inferences of R-c and spatiotemporal patterns therein depend upon the choice of data types and assumptions about travel-history data. Conclusions These results suggest that transmission network inferences made with routine malaria surveillance data should be interpreted with caution.

BACKGROUND:Malaria is a risk factor for adverse pregnancy outcomes. Indoor residual spraying with insecticide (IRS) reduces malaria infections, yet the effects of IRS on pregnancy outcomes are not well established. We evaluated the impact of a large-scale IRS campaign on pregnancy outcomes in Eastern Uganda. METHODS:Birth records (n = 59 992) were obtained from routine surveillance data at 25 health facilities from five districts that were part of the IRS campaign and six neighbouring control districts ∼27 months before and ∼24 months after the start of the campaign (January 2013-May 2017). Campaign effects on low birthweight (LBW) and stillbirth incidence were estimated using the matrix completion method (MC-NNM), a machine-learning approach to estimating potential outcomes, and compared with the difference-in-differences (DiD) estimator. Subgroup analyses were conducted by HIV and gravidity. RESULTS:MC-NNM estimates indicated that the campaign was associated with a 33% reduction in LBW incidence: incidence rate ratio (IRR) = 0.67 [95% confidence interval (CI): 0.49-0.93)]. DiD estimates were similar to MC-NNM [IRR = 0.69 (0.47-1.01)], despite a parallel trends violation during the pre-IRS period. The campaign was not associated with substantial reductions in stillbirth incidence [IRRMC-NNM = 0.94 (0.50-1.77)]. HIV status modified the effects of the IRS campaign on LBW [βIRSxHIV = 0.42 (0.05-0.78)], whereby HIV-negative women appeared to benefit from the campaign [IRR = 0.70 (0.61-0.81)], but not HIV-positive women [IRR = 1.12 (0.59-2.12)]. CONCLUSIONS:Our results support the effectiveness of the campaign in Eastern Uganda based on its benefit to LBW prevention, though HIV-positive women may require additional interventions. The IRS campaign was not associated with a substantively lower stillbirth incidence, warranting further research.

Background Targeted next generation sequencing offers the potential for consistent, deep coverage of information rich genomic regions to characterize polyclonal Plasmodium falciparum infections. However, methods to identify and sequence these genomic regions are currently limited. Methods A bioinformatic pipeline and multiplex methods were developed to identify and simultaneously sequence 100 targets and applied to dried blood spot (DBS) controls and field isolates from Mozambique. For comparison, WGS data were generated for the same controls. Results Using publicly available genomes, 4465 high diversity genomic regions suited for targeted sequencing were identified, representing the P. falciparum heterozygome. For this study, 93 microhaplotypes with high diversity (median H E = 0.7) were selected along with 7 drug resistance loci. The sequencing method achieved very high coverage (median 99%), specificity (99.8%) and sensitivity (90% for haplotypes with 5% within sample frequency in DBS with 100 parasites/µL). In silico analyses revealed that microhaplotypes provided much higher resolution to discriminate related from unrelated polyclonal infections than biallelic SNP barcodes. Discussion The bioinformatic and laboratory methods outlined here provide a flexible tool for efficient, low-cost, high throughput interrogation of the P. falciparum genome, and can be tailored to simultaneously address multiple questions of interest in various epidemiological settings.

Dried blood spots (DBS) typically prepared on filter papers are an ideal sample type for malaria surveillance by offering easy and cost-effective methods in terms of sample collection, storage, and transport. The objective of this study was to evaluate the applicability of DBS with a commercial multiplex malaria assay, developed to concurrently measure Plasmodium antigens, histidine-rich protein 2 (HRP2), Plasmodium lactate dehydrogenase (pLDH), and a host inflammatory biomarker, C-reactive protein (CRP), in whole blood. The assay conditions were optimized for DBS, and thermal stability for measurement of Plasmodium antigens and CRP in dried blood were determined. Performance of the multiplex assay on matched DBS and whole blood pellet samples was also evaluated using the clinical samples. The results indicate the acceptable performance in multiplex antigen detection using DBS samples. At cutoff levels for DBS, with a diagnostic specificity with a lower 95% confidence bound > 92%, diagnostic sensitivities against polymerase chain reaction (PCR)–confirmed malaria for HRP2, Pf LDH, Pv LDH, and Pan LDH were 93.5%, 80.4%, 21.3%, and 55.6%, respectively. The half-life of pLDH was significantly less than that of HRP2 in thermal stability studies. Results with DBS samples collected from Peru indicate that the uncontrolled storage conditions of DBS can result in inaccurate reporting for infection with P. falciparum parasites with hrp2/3 deletions. With careful consideration that minimizing the unfavorable DBS storage environment is essential for ensuring integrity of heat-labile Plasmodium antigens, DBS samples can be used as an alternative to liquid whole blood to detect P. falciparum with hrp2/3 deletions in malaria surveillance.

Malaria antigen detection through rapid diagnostic tests (RDTs) is widely used to diagnose malaria and estimate prevalence. To support more sensitive next-generation RDT development and screen asymptomatic malaria, we developed and evaluated the Q-Plex (TM) Human Malaria Array (Quansys Biosciences, Logan, UT), which quantifies the antigens commonly used in RDTs-Plasmodium falciparum-specific histidine-rich protein 2 (HRP2), P. falciparum-specific lactate dehydrogenase (Pf LDH), Plasmodium vivax-specific LDH (Pv LDH), and Pan malaria lactate dehydrogenase (Pan LDH), and human C-reactive protein (CRP), a biomarker of severity in malaria. At threshold levels yielding 99.5% or more diagnostic specificity, diagnostic sensitivities against polymerase chain reaction-confirmed malaria for HRP2, Pf LDH, Pv LDH, and Pan LDH were 92.7%, 71.5%, 46.1%, and 83.8%, respectively. P. falciparum culture strains and samples from Peru indicated that HRP2 and Pf LDH combined improves detection of P. falciparum parasites with hrp2 and hrp3 deletions. This array can be used for antigen-based malaria screening and detecting hrp2/3 deletion mutants of P. falciparum.