Applying next-generation sequencing to track falciparum malaria in sub-Saharan Africa

Genomics reveals heterogeneous Plasmodium falciparum transmission and selection signals in Zambia

BACKGROUND

Genomic surveillance is crucial for monitoring malaria transmission and understanding parasite adaptation to interventions. Zambia lacks prior nationwide efforts in malaria genomic surveillance among African countries.

METHODS

We conducted genomic surveillance of Plasmodium falciparum parasites from the 2018 Malaria Indicator Survey in Zambia, a nationally representative household survey of children under five years of age. We whole-genome sequenced and analyzed 241 P. falciparum genomes from regions with varying levels of malaria transmission across Zambia and estimated genetic metrics that are informative about transmission intensity, genetic relatedness between parasites, and selection.

RESULTS

We provide genomic evidence of widespread within-host polygenomic infections, regardless of epidemiological characteristics, underscoring the extensive and ongoing endemic malaria transmission in Zambia. Our analysis reveals country-level clustering of parasites from Zambia and neighboring regions, with distinct separation in West Africa. Within Zambia, identity by descent (IBD) relatedness analysis uncovers local spatial clustering and rare cases of long-distance sharing of closely related parasite pairs. Genomic regions with large shared IBD segments and strong positive selection signatures implicate genes involved in sulfadoxine-pyrimethamine and artemisinin combination therapies drug resistance, but no signature related to chloroquine resistance. Furthermore, differences in selection signatures, including drug resistance loci, are observed between eastern and western Zambian parasite populations, suggesting variable transmission intensity and ongoing drug pressure.

CONCLUSIONS

Our findings enhance our understanding of nationwide P. falciparum transmission in Zambia, establishing a baseline for analyzing parasite genetic metrics as they vary over time and space. These insights highlight the urgency of strengthening malaria control programs and surveillance of antimalarial drug resistance.

Genomic malaria surveillance of antenatal care users detects reduced transmission following elimination interventions in Mozambique

Routine sampling of pregnant women at first antenatal care (ANC) visits could make Plasmodium falciparum genomic surveillance more cost-efficient and convenient in sub-Saharan Africa. We compare the genetic structure of parasite populations sampled from 289 first ANC users and 93 children from the community in Mozambique between 2015 and 2019. Samples are amplicon sequenced targeting 165 microhaplotypes and 15 drug resistance genes. Metrics of genetic diversity and relatedness, as well as the prevalence of drug resistance markers, are consistent between the two populations. In an area targeted for elimination, intra-host genetic diversity declines in both populations (p = 0.002-0.007), while for the ANC population, population genetic diversity is also lower (p = 0.0004), and genetic relatedness between infections is higher (p = 0.002) than control areas, indicating a recent reduction in the parasite population size. These results highlight the added value of genomic surveillance at ANC clinics to inform about changes in transmission beyond epidemiological data.

Microsatellites reveal high polymorphism and high potential for use in anti-malarial efficacy studies in areas with different transmission intensities in mainland Tanzania

BACKGROUND

Tanzania is currently implementing therapeutic efficacy studies (TES) in areas of varying malaria transmission intensities as per the World Health Organization (WHO) recommendations. In TES, distinguishing reinfection from recrudescence is critical for the determination of anti-malarial efficacy. Recently, the WHO recommended genotyping polymorphic coding genes, merozoite surface proteins 1 and 2 (msp1 and msp2), and replacing the glutamate-rich protein (glurp) gene with one of the highly polymorphic microsatellites in Plasmodium falciparum to adjust the efficacy of antimalarials in TES. This study assessed the polymorphisms of six neutral microsatellite markers and their potential use in TES, which is routinely performed in Tanzania.

METHODS

Plasmodium falciparum samples were obtained from four TES sentinel sites, Kibaha (Pwani), Mkuzi (Tanga), Mlimba (Morogoro) and Ujiji (Kigoma), between April and September 2016. Parasite genomic DNA was extracted from dried blood spots on filter papers using commercial kits. Genotyping was done using six microsatellites (Poly-α, PfPK2, TA1, C3M69, C2M34 and M2490) by capillary method, and the data were analysed to determine the extent of their polymorphisms and genetic diversity at the four sites.

RESULTS

Overall, 83 (88.3%) of the 94 samples were successfully genotyped (with positive results for ≥ 50.0% of the markers), and > 50.0% of the samples (range = 47.6-59.1%) were polyclonal, with a mean multiplicity of infection (MOI) ranging from 1.68 to 1.88 among the four sites. There was high genetic diversity but limited variability among the four sites based on mean allelic richness (RS = 7.48, range = 7.27-8.03, for an adjusted minimum sample size of 18 per site) and mean expected heterozygosity (He = 0.83, range = 0.80-0.85). Cluster analysis of haplotypes using STRUCTURE, principal component analysis, and pairwise genetic differentiation (FST) did not reveal population structure or clustering of parasites according to geographic origin. Of the six markers, Poly-α was the most polymorphic, followed by C2M34, TA1 and C3M69, while M2490 was the least polymorphic.

CONCLUSION

Microsatellite genotyping revealed high polyclonality and genetic diversity but no significant population structure. Poly-α, C2M34, TA1 and C3M69 were the most polymorphic markers, and Poly-α alone or with any of the other three markers could be adopted for use in TES in Tanzania.

Genomics reveals heterogeneous Plasmodium falciparum transmission and population differentiation in Zambia and bordering countries

Genomic surveillance plays a critical role in monitoring malaria transmission and understanding how the parasite adapts in response to interventions. We conducted genomic surveillance of malaria by sequencing 241 Plasmodium falciparum genomes from regions with varying levels of malaria transmission across Zambia. We found genomic evidence of high levels of within-host polygenomic infections, regardless of epidemiological characteristics, underscoring the extensive and ongoing endemic malaria transmission in the country. We identified country-level clustering of parasites from Zambia and neighboring countries, and distinct clustering of parasites from West Africa. Within Zambia, our identity by descent (IBD) relatedness analysis uncovered spatial clustering of closely related parasite pairs at the local level and rare cases of long-distance sharing. Genomic regions with large shared IBD segments and strong positive selection signatures identified genes involved in sulfadoxine-pyrimethamine and artemisinin combination therapies drug resistance, but no signature related to chloroquine resistance. Together, our findings enhance our understanding of P. falciparum transmission nationwide in Zambia and highlight the urgency of strengthening malaria control programs and surveillance of antimalarial drug resistance.

Using a mobile nanopore sequencing lab for end-to-end genomic surveillance of Plasmodium falciparum: A feasibility study

Genomic epidemiology holds promise for malaria control and elimination efforts, for example by informing on Plasmodium falciparum genetic diversity and prevalence of mutations conferring anti-malarial drug resistance. Limited sequencing infrastructure in many malaria-endemic areas prevents the rapid generation of genomic data. To address these issues, we developed and validated assays for P. falciparum nanopore sequencing in endemic sites using a mobile laboratory, targeting key antimalarial drug resistance markers and microhaplotypes. Using two multiplexed PCR reactions, we amplified six highly polymorphic microhaplotypes and ten drug resistance markers. We developed a bioinformatics workflow that allows genotyping of polyclonal malaria infections, including minority clones. We validated the panels on mock dried blood spot (DBS) and rapid diagnostic test (RDT) samples and archived DBS, demonstrating even, high read coverage across amplicons (range: 580x to 3,212x median coverage), high haplotype calling accuracy, and the ability to explore within-sample diversity of polyclonal infections. We field-tested the feasibility of rapid genotyping in Zanzibar in close collaboration with the local malaria elimination program using DBS and routinely collected RDTs as sample inputs. Our assay identified haplotypes known to confer resistance to known antimalarials in the dhfr, dhps and mdr1 genes, but no evidence of artemisinin partial resistance. Most infections (60%) were polyclonal, with high microhaplotype diversity (median HE = 0.94). In conclusion, our assays generated actionable data within a few days, and we identified current challenges for implementing nanopore sequencing in endemic countries to accelerate malaria control and elimination.

The Laboratory Diagnosis of Malaria: A Focus on the Diagnostic Assays in Non-Endemic Areas

Even if malaria is rare in Europe, it is a medical emergency and programs for its control should ensure both an early diagnosis and a prompt treatment within 24-48 h from the onset of the symptoms. The increasing number of imported malaria cases as well as the risk of the reintroduction of autochthonous cases encouraged laboratories in non-endemic countries to adopt diagnostic methods/algorithms. Microscopy remains the gold standard, but with limitations. Rapid diagnostic tests have greatly expanded the ability to diagnose malaria for rapid results due to simplicity and low cost, but they lack sensitivity and specificity. PCR-based assays provide more relevant information but need well-trained technicians. As reported in the World Health Organization Global Technical Strategy for Malaria 2016-2030, the development of point-of-care testing is important for the improvement of diagnosis with beneficial consequences for prompt/accurate treatment and for preventing the spread of the disease. Despite their limitations, diagnostic methods contribute to the decline of malaria mortality. Recently, evidence suggested that artificial intelligence could be utilized for assisting pathologists in malaria diagnosis.

Amplicon deep sequencing of five highly polymorphic markers of Plasmodium falciparum reveals high parasite genetic diversity and moderate population structure in Ethiopia

BACKGROUND

Plasmodium falciparum genetic diversity can add information on transmission intensity and can be used to track control and elimination interventions.

METHODS

Dried blood spots (DBS) were collected from patients who were recruited for a P. falciparum malaria therapeutic efficacy trial in three malaria endemic sites in Ethiopia from October to December 2015, and November to December 2019. qPCR-confirmed infections were subject to amplicon sequencing of polymorphic markers ama1-D3, csp, cpp, cpmp, msp7. Genetic diversity, the proportion of multiclonal infections, multiplicity of infection, and population structure were analysed.

RESULTS

Among 198 samples selected for sequencing, data was obtained for 181 samples. Mean MOI was 1.38 (95% CI 1.24-1.53) and 17% (31/181) of infections were polyclonal. Mean He across all markers was 0.730. Population structure was moderate; populations from Metema and Metehara 2015 were very similar to each other, but distinct from Wondogent 2015 and Metehara 2019.

CONCLUSION

The high level of parasite genetic diversity and moderate population structure in this study suggests frequent gene flow of parasites among sites. The results obtained can be used as a baseline for additional parasite genetic diversity and structure studies, aiding in the formulation of appropriate control strategies in Ethiopia.

Genomic malaria surveillance of antenatal care users detects reduced transmission following elimination interventions in Mozambique

Routine sampling of pregnant women at first antenatal care (ANC) visits could make Plasmodium falciparum genomic surveillance more cost-efficient and convenient in sub-Saharan Africa. We compared the genetic structure of parasite populations sampled from 289 first ANC attendees and 93 children from the community in Mozambique between 2015 and 2019. Samples were amplicon sequenced targeting 165 microhaplotypes and 15 drug resistance genes. Metrics of genetic diversity and relatedness, as well as the prevalence of drug resistance markers, were consistent between the two populations. In an area targeted for elimination, intra-host genetic diversity declined in both populations (p=0.002-0.007), while for the ANC population, population genetic diversity was also lower (p=0.0004), and genetic relatedness between infections were higher (p=0.002) than control areas, indicating a recent reduction in the parasite population size. These results highlight the added value of genomic surveillance at ANC clinics to inform about changes in transmission beyond epidemiological data.

Sampling for malaria molecular surveillance

Strategic use of Plasmodium falciparum genetic variation has great potential to inform public health actions for malaria control and elimination. Malaria molecular surveillance (MMS) begins with a strategy to identify and collect parasite samples, guided by public-health priorities. In this review we discuss sampling design practices for MMS and point out epidemiological, biological, and statistical factors that need to be considered. We present examples for different use cases, including detecting emergence and spread of rare variants, establishing transmission sources and inferring changes in malaria transmission intensity. This review will potentially guide the collection of samples and data, serve as a starting point for further methodological innovation, and enhance utilization of MMS to support malaria elimination.

Testing and treatment for malaria elimination: a systematic review

BACKGROUND

Global interest in malaria elimination has prompted research on active test and treat (TaT) strategies.

METHODS

A systematic review and meta-analysis were conducted to assess the effectiveness of TaT strategies to reduce malaria transmission.

RESULTS

A total of 72 empirical research and 24 modelling studies were identified, mainly focused on proactive mass TaT (MTaT) and reactive case detection (RACD) in higher and lower transmission settings, respectively. Ten intervention studies compared MTaT to no MTaT and the evidence for impact on malaria incidence was weak. No intervention studies compared RACD to no RACD. Compared to passive case detection (PCD) alone, PCD + RACD using standard diagnostics increased infection detection 52.7% and 11.3% in low and very low transmission settings, respectively. Using molecular methods increased this detection of infections by 1.4- and 1.1-fold, respectively.

CONCLUSION

Results suggest MTaT is not effective for reducing transmission. By increasing case detection, surveillance data provided by RACD may indirectly reduce transmission by informing coordinated responses of intervention targeting.

Exploring how space, time, and sampling impact our ability to measure genetic structure across Plasmodium falciparum populations

A primary use of malaria parasite genomics is identifying highly related infections to quantify epidemiological, spatial, or temporal factors associated with patterns of transmission. For example, spatial clustering of highly related parasites can indicate foci of transmission and temporal differences in relatedness can serve as evidence for changes in transmission over time. However, for infections in settings of moderate to high endemicity, understanding patterns of relatedness is compromised by complex infections, overall high forces of infection, and a highly diverse parasite population. It is not clear how much these factors limit the utility of using genomic data to better understand transmission in these settings. In particular, further investigation is required to determine which patterns of relatedness we expect to see with high quality, densely sampled genomic data in a high transmission setting and how these observations change under different study designs, missingness, and biases in sample collection. Here we investigate two identity-by-state measures of relatedness and apply them to amplicon deep sequencing data collected as part of a longitudinal cohort in Western Kenya that has previously been analysed to identify individual-factors associated with sharing parasites with infected mosquitoes. With these data we use permutation tests, to evaluate several hypotheses about spatiotemporal patterns of relatedness compared to a null distribution. We observe evidence of temporal structure, but not of fine-scale spatial structure in the cohort data. To explore factors associated with the lack of spatial structure in these data, we construct a series of simplified simulation scenarios using an agent based model calibrated to entomological, epidemiological and genomic data from this cohort study to investigate whether the lack of spatial structure observed in the cohort could be due to inherent power limitations of this analytical method. We further investigate how our hypothesis testing behaves under different sampling schemes, levels of completely random and systematic missingness, and different transmission intensities.

Genomic approaches for monitoring transmission dynamics of malaria: A case for malaria molecular surveillance in Sub-Saharan Africa

Transmission dynamics is an important indicator for malaria control and elimination. As we move closer to eliminating malaria in Sub-Saharan Africa (sSA), transmission indices with higher resolution (genomic approaches) will complement our current measurements of transmission. Most of the present programmatic knowledge of malaria transmission patterns are derived from assessments of epidemiologic and clinical data, such as case counts, parasitological estimates of parasite prevalence, and Entomological Inoculation Rates (EIR). However, to eliminate malaria from endemic areas, we need to track changes in the parasite population and how they will impact transmission. This is made possible through the evolving field of genomics and genetics, as well as the development of tools for more in-depth studies on the diversity of parasites and the complexity of infections, among other topics. If malaria elimination is to be achieved globally, country-specific elimination activities should be supported by parasite genomic data from regularly collected blood samples for diagnosis, surveillance and possibly from other programmatic interventions. This presents a unique opportunity to track the spread of malaria parasites and shed additional light on intervention efficacy. In this review, various genetic techniques are highlighted along with their significance for an enhanced understanding of transmission patterns in distinct topological settings throughout Sub-Saharan Africa. The importance of these methods and their limitations in malaria surveillance to guide control and elimination strategies, are explored.

High genetic complexity but low relatedness in Plasmodium falciparum infections from Western Savannah Highlands and coastal equatorial Lowlands of Cameroon

To determine the diversity and connectivity of infections in Northwestern and Southwestern Cameroon, 232 Plasmodium falciparum infections, collected in 2018 from the Ndop Health District (NHD) in the western savannah highlands in the Northwest and the Limbe Health District (LHD) in the coastal lowland forests in the Southwest of Cameroon were genotyped for nine neutral microsatellite markers. Overall infection complexity and genetic diversity was significantly (p < 0.05) lower in NHD than LHD, (Mean MOI = 2.45 vs. 2.97; Fws = 0.42 vs. 0.47; Mean He = 0.84 vs. 0.89, respectively). Multi-locus linkage disequilibrium was generally low but significantly higher in the NHD than LHD population (mean ISA= 0.376 vs 0.093). Consequently, highly related pairs of isolates were observed in NHD (mean IBS = 0.086) compared to those from the LHD (mean IBS = 0.059). Infections from the two regions were mostly unrelated (mean IBS = 0.059), though the overall genetic differentiation across the geographical range was low. Indices of differentiation between the populations were however significant (overall pairwise Fst = 0.048, Jost's D = 0.133, p < 0.01). Despite the high human migration across the 270km separating the study sites, these results suggest significant restrictions to gene flow against contiguous geospatial transmission of malaria in west Cameroon. Clonal infections in the highland sites could be driven by lower levels of malaria prevalence and seasonal transmission. How these differences in genetic diversity and complexity affect responses to interventions such as drugs will require further investigations from broader community sampling.

R H: a genetic metric for measuring intrahost Plasmodium falciparum relatedness and distinguishing cotransmission from superinfection

Multiple-strain (polygenomic) infections are a ubiquitous feature of Plasmodium falciparum parasite population genetics. Under simple assumptions of superinfection, polygenomic infections are hypothesized to be the result of multiple infectious bites. As a result, polygenomic infections have been used as evidence of repeat exposure and used to derive genetic metrics associated with high transmission intensity. However, not all polygenomic infections are the result of multiple infectious bites. Some result from the transmission of multiple, genetically related strains during a single infectious bite (cotransmission). Superinfection and cotransmission represent two distinct transmission processes, and distinguishing between the two could improve inferences regarding parasite transmission intensity. Here, we describe a new metric, R H, that utilizes the correlation in allelic state (heterozygosity) within polygenomic infections to estimate the likelihood that the observed complexity resulted from either superinfection or cotransmission. R H is flexible and can be applied to any type of genetic data. As a proof of concept, we used R H to quantify polygenomic relatedness and estimate cotransmission and superinfection rates from a set of 1,758 malaria infections genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode. Contrary to expectation, we found that cotransmission was responsible for a significant fraction of 43% to 53% of the polygenomic infections collected in three distinct epidemiological regions in Senegal. The prediction that polygenomic infections frequently result from cotransmission stresses the need to incorporate estimates of relatedness within polygenomic infections to ensure the accuracy of genomic epidemiology surveillance data for informing public health activities.

Potential Opportunities and Challenges of Deploying Next Generation Sequencing and CRISPR-Cas Systems to Support Diagnostics and Surveillance Towards Malaria Control and Elimination in Africa

Recent developments in molecular biology and genomics have revolutionized biology and medicine mainly in the developed world. The application of next generation sequencing (NGS) and CRISPR-Cas tools is now poised to support endemic countries in the detection, monitoring and control of endemic diseases and future epidemics, as well as with emerging and re-emerging pathogens. Most low and middle income countries (LMICs) with the highest burden of infectious diseases still largely lack the capacity to generate and perform bioinformatic analysis of genomic data. These countries have also not deployed tools based on CRISPR-Cas technologies. For LMICs including Tanzania, it is critical to focus not only on the process of generation and analysis of data generated using such tools, but also on the utilization of the findings for policy and decision making. Here we discuss the promise and challenges of NGS and CRISPR-Cas in the context of malaria as Africa moves towards malaria elimination. These innovative tools are urgently needed to strengthen the current diagnostic and surveillance systems. We discuss ongoing efforts to deploy these tools for malaria detection and molecular surveillance highlighting potential opportunities presented by these innovative technologies as well as challenges in adopting them. Their deployment will also offer an opportunity to broadly build in-country capacity in pathogen genomics and bioinformatics, and to effectively engage with multiple stakeholders as well as policy makers, overcoming current workforce and infrastructure challenges. Overall, these ongoing initiatives will build the malaria molecular surveillance capacity of African researchers and their institutions, and allow them to generate genomics data and perform bioinformatics analysis in-country in order to provide critical information that will be used for real-time policy and decision-making to support malaria elimination on the continent.

Prospective surveillance study to detect antimalarial drug resistance, gene deletions of diagnostic relevance and genetic diversity of Plasmodium falciparum in Mozambique: protocol

INTRODUCTION

Genomic data constitute a valuable adjunct to routine surveillance that can guide programmatic decisions to reduce the burden of infectious diseases. However, genomic capacities remain low in Africa. This study aims to operationalise a functional malaria molecular surveillance system in Mozambique for guiding malaria control and elimination.

METHODS AND ANALYSES

This prospective surveillance study seeks to generate Plasmodium falciparum genetic data to (1) monitor molecular markers of drug resistance and deletions in rapid diagnostic test targets; (2) characterise transmission sources in low transmission settings and (3) quantify transmission levels and the effectiveness of antimalarial interventions. The study will take place across 19 districts in nine provinces (Maputo city, Maputo, Gaza, Inhambane, Niassa, Manica, Nampula, Zambézia and Sofala) which span a range of transmission strata, geographies and malaria intervention types. Dried blood spot samples and rapid diagnostic tests will be collected across the study districts in 2022 and 2023 through a combination of dense (all malaria clinical cases) and targeted (a selection of malaria clinical cases) sampling. Pregnant women attending their first antenatal care visit will also be included to assess their value for molecular surveillance. We will use a multiplex amplicon-based next-generation sequencing approach targeting informative single nucleotide polymorphisms, gene deletions and microhaplotypes. Genetic data will be incorporated into epidemiological and transmission models to identify the most informative relationship between genetic features, sources of malaria transmission and programmatic effectiveness of new malaria interventions. Strategic genomic information will be ultimately integrated into the national malaria information and surveillance system to improve the use of the genetic information for programmatic decision-making.

ETHICS AND DISSEMINATION

The protocol was reviewed and approved by the institutional (CISM) and national ethics committees of Mozambique (Comité Nacional de Bioética para Saúde) and Spain (Hospital Clinic of Barcelona). Project results will be presented to all stakeholders and published in open-access journals.

TRIAL REGISTRATION NUMBER

NCT05306067.

Making data map-worthy-enhancing routine malaria data to support surveillance and mapping of Plasmodium falciparum anti-malarial resistance in a pre-elimination sub-Saharan African setting: a molecular and spatiotemporal epidemiology study

Background

Independent emergence and spread of artemisinin-resistant Plasmodium falciparum malaria have recently been confirmed in Africa, with molecular markers associated with artemisinin resistance increasingly detected. Surveillance to promptly detect and effectively respond to anti-malarial resistance is generally suboptimal in Africa, especially in low transmission settings where therapeutic efficacy studies are often not feasible due to recruitment challenges. However, these communities may be at higher risk of anti-malarial resistance.

Methods

From March 2018 to February 2020, a sequential mixed-methods study was conducted to evaluate the feasibility of the near-real-time linkage of individual patient anti-malarial resistance profiles with their case notifications and treatment response reports, and map these to fine scales in Nkomazi sub-district, Mpumalanga, a pre-elimination area in South Africa.

Results

Plasmodium falciparum molecular marker resistance profiles were linked to 55.1% (2636/4787) of notified malaria cases, 85% (2240/2636) of which were mapped to healthcare facility, ward and locality levels. Over time, linkage of individual malaria case demographic and molecular data increased to 75.1%. No artemisinin resistant validated/associated  Kelch-13 mutations were detected in the 2385 PCR positive samples. Almost all 2812 samples assessed for lumefantrine susceptibility carried the wildtype mdr86ASN and crt76LYS alleles, potentially associated with decreased lumefantrine susceptibility.

Conclusion

Routine near-real-time mapping of molecular markers associated with anti-malarial drug resistance on a fine spatial scale provides a rapid and efficient early warning system for emerging resistance. The lessons learnt here could inform scale-up to provincial, national and regional malaria elimination programmes, and may be relevant for other antimicrobial resistance surveillance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-022-04224-4.

Whole Genome Sequencing Contributions and Challenges in Disease Reduction Focused on Malaria

Malaria elimination remains an important goal that requires the adoption of sophisticated science and management strategies in the era of the COVID-19 pandemic. The advent of next generation sequencing (NGS) is making whole genome sequencing (WGS) a standard today in the field of life sciences, as PCR genotyping and targeted sequencing provide insufficient information compared to the whole genome. Thus, adapting WGS approaches to malaria parasites is pertinent to studying the epidemiology of the disease, as different regions are at different phases in their malaria elimination agenda. Therefore, this review highlights the applications of WGS in disease management, challenges of WGS in controlling malaria parasites, and in furtherance, provides the roles of WGS in pursuit of malaria reduction and elimination. WGS has invaluable impacts in malaria research and has helped countries to reach elimination phase rapidly by providing required information needed to thwart transmission, pathology, and drug resistance. However, to eliminate malaria in sub-Saharan Africa (SSA), with high malaria transmission, we recommend that WGS machines should be readily available and affordable in the region.

Malaria diagnostic update: From conventional to advanced method

BACKGROUND

Update diagnostic methods play essential roles in dealing with the current global malaria situation and decreasing malaria incidence.

AIM

Global malaria control programs require the availability of adequate laboratory tests in the quick and convenient field.

RESULTS

There are several methods to find out the existence of parasites within the blood. The oldest one is by microscopy, which is still a gold standard, although rapid diagnostic tests (RDTs) have rapidly become a primary diagnostic test in many endemic areas. Because of microscopy and RDTs limitation, novel serological and molecular methods have been developed. Many kinds of polymerase chain reaction (PCR) provide rapid results and higher specificity and sensitivity. The loop-mediated isothermal amplification (LAMP) and biosensing-based molecular techniques as point of care tests (POCT) will become a cost-effective approach to advance diagnostic testing.

CONCLUSION

Despite conventional techniques are still being used in the field, the exploration and field implementation of advanced techniques for the diagnosis of malaria are still being developed rapidly.

Plasmodium falciparum importation does not sustain malaria transmission in a semi-arid region of Kenya

Human movement impacts the spread and transmission of infectious diseases. Recently, a large reservoir of Plasmodium falciparum malaria was identified in a semi-arid region of northwestern Kenya historically considered unsuitable for malaria transmission. Understanding the sources and patterns of transmission attributable to human movement would aid in designing and targeting interventions to decrease the unexpectedly high malaria burden in the region. Toward this goal, polymorphic parasite genes (ama1, csp) in residents and passengers traveling to Central Turkana were genotyped by amplicon deep sequencing. Genotyping and epidemiological data were combined to assess parasite importation. The contribution of travel to malaria transmission was estimated by modelling case reproductive numbers inclusive and exclusive of travelers. P. falciparum was detected in 6.7% (127/1891) of inbound passengers, including new haplotypes which were later detected in locally-transmitted infections. Case reproductive numbers approximated 1 and did not change when travelers were removed from transmission networks, suggesting that transmission is not fueled by travel to the region but locally endemic. Thus, malaria is not only prevalent in Central Turkana but also sustained by local transmission. As such, interrupting importation is unlikely to be an effective malaria control strategy on its own, but targeting interventions locally has the potential to drive down transmission.

Trichinella Outbreaks on Pig Farms in Poland in 2012-2020

Trichinella nematodes continue to circulate in various hosts both in the domestic and sylvatic cycles. In the majority of countries in Europe, wild boars have been noticed as a primary source of Trichinella spp. infections in humans. However, in some regions, the meat of pigs containing Trichinella spp. larvae can still be a cause of trichinellosis. Therefore, in the present study, we aimed to determine and present actual data on the occurrence of Trichinella spp. on pig farms (Sus scrofa f. domestica) in Poland. In this study, over 194 million pigs, slaughtered for commercial and personal purposes between 2012 and 2020, were tested with a digestion method according to the official rules for Trichinella control. Positive results were noticed in 172 pigs which gives an overall prevalence of 0.000088%. On seven farms, rats (Rattus norvegicus) infected with Trichinella spp. were also discovered. The species identification showed pigs were infected with Trichinella spiralis on 26 farms, and on four farms pigs with Trichinella britovi infections were found. Therefore, it is important to constantly monitor pigs for the presence of these parasites, especially in view of the growing interest in organic meat originated from ecological farms.

Mechanism of the Passage of Angiostrongylus cantonensis across the Final Host Blood-Brain Barrier Using the Next-Generation Sequencing

Background:

Multicellular parasites Angiostrogylus cantonensis larvae develop in the final host rat brain at the fourth stage (L4) and migrate to the lungs by the adult stage. The potential mechanism of its blood-brain barrier (BBB) passage remains unclear.

Methods:

By using Illumina Hiseq/Miseq sequencing, we obtained the transcriptomes of 3 groups of adult males and 3 groups of female of A. cantonensis to generate similarly expressed genes (SEGs) between 2 genders at the adult stage. Next 2 groups of L4 expressed genes were used to compared with SEGs to create differentially expressed genes (DEGs) between 2 life stages to unlock potential mechanism of BBB passage.

Results:

In total, we obtained 381 581 802 clean reads and 56 990 699 010 clean bases. Of these, 331 803 unigenes and 482 056 transcripts were successfully annotated. A total of 3 166 DEGs between L4 and adults SEGs were detected. Annotation of these DEGs showed 167 were down-regulated and 181 were up-regulated. Pathway analysis exhibited that calcium signaling pathway, the ECM−receptor interaction, focal adhesion, and cysteine and methionine metabolism were highly associated with DEGs. The function of these pathways might be related to BBB traversal, as well as neuro-regulation, interactions between parasite and host, environmental adaption.

Conclusion:

This study expanded the regulatory characteristics of the two important life stages of A. cantonensis. This information may provide a better appreciation of the biological features of the stages of the parasitic A. cantonensis.

Trich-tracker - a practical tool to trace Trichinella spiralis transmission based on rapid, cost-effective sampling of genome-wide genetic variation

Molecular epidemiology using traditional sequencing has been notoriously difficult in inbred parasites due to a lack of genetic variation available for discriminating among parasites. Next generation sequencing techniques offer a solution to this problem by increasing the number of loci that can be sequenced. Here, we introduce Trich-tracker, a tool that makes efficient use of diagnostic variation distributed throughout the genome of Trichinella spiralis to more rapidly, and conclusively, resolve connections and distinctions among focal outbreaks of T. spiralis. In particular, we rapidly characterised genetic variation among a sample of parasites from Polish farms and wildlife, sampling genomic variation using double digest restriction site-associated DNA sequencing (ddRADseq). Approximately 400,000 bases of sequence were generated from each sample and shown to be distributed across the genome with single nucleotide polymorphisms occurring at a frequency of approximately one base in 10,000. Both phylogenetic and Bayesian clustering analyses indicated that ddRADseq genotypes formed distinct clusters for specific outbreaks and were quite distinct from wild boar samples. Two of the investigated outbreaks were more similar to each other than to other outbreak samples, suggesting a link between these outbreaks. Hence, the Trich-tracker procedure identified informative genomic variation which afforded unprecedented epidemiological resolution. Trich-tracker is very flexible tool, quickly and inexpensively mining genomes of even highly inbred populations of T. spiralis to support outbreak investigations. The simplicity of the entire procedure, and time and cost effectiveness of Trich-tracker support its practical application in ongoing Trichinella outbreaks. The discriminating power of this tool is tunable and scalable, allowing application in a variety of epidemiological contexts, and is easily adapted to other parasite systems.

Infection, genetics, and evolution of Trichinella: Historical insights and applications to molecular epidemiology

Genetic variation in pathogen populations provides the means to answer questions in disease ecology and transmission, illuminating interactions between genetic traits, environmental exposures, and disease. Such studies elucidate the phylogeny, evolution, transmission and pathogenesis of viruses, bacteria and parasites. Here, we review how such studies have fostered understanding of the biology and epidemiology of zoonotic nematode parasites in the genus Trichinella spp., which impose considerable economic and health burdens by infecting wildlife, livestock, and people. To use such data to define ongoing chains of local transmission and source traceback, researchers first must understand the extent and distribution of genetic variation resident in regional parasite populations. Thus, genetic variability illuminates a population's past as well as its present. Here we review how such data have helped define population dynamics of Trichinella spp. in wild and domesticated hosts, creating opportunities to harness genetic variation in the quest to prevent, track, and contain future outbreaks.

Advances and opportunities in malaria population genomics

Almost 20 years have passed since the first reference genome assemblies were published for Plasmodium falciparum, the deadliest malaria parasite, and Anopheles gambiae, the most important mosquito vector of malaria in sub-Saharan Africa. Reference genomes now exist for all human malaria parasites and nearly half of the ~40 important vectors around the world. As a foundation for genetic diversity studies, these reference genomes have helped advance our understanding of basic disease biology and drug and insecticide resistance, and have informed vaccine development efforts. Population genomic data are increasingly being used to guide our understanding of malaria epidemiology, for example by assessing connectivity between populations and the efficacy of parasite and vector interventions. The potential value of these applications to malaria control strategies, together with the increasing diversity of genomic data types and contexts in which data are being generated, raise both opportunities and challenges in the field. This Review discusses advances in malaria genomics and explores how population genomic data could be harnessed to further support global disease control efforts.

Elucidating relationships between P.falciparum prevalence and measures of genetic diversity with a combined genetic-epidemiological model of malaria

There is an abundance of malaria genetic data being collected from the field, yet using these data to understand the drivers of regional epidemiology remains a challenge. A key issue is the lack of models that relate parasite genetic diversity to epidemiological parameters. Classical models in population genetics characterize changes in genetic diversity in relation to demographic parameters, but fail to account for the unique features of the malaria life cycle. In contrast, epidemiological models, such as the Ross-Macdonald model, capture malaria transmission dynamics but do not consider genetics. Here, we have developed an integrated model encompassing both parasite evolution and regional epidemiology. We achieve this by combining the Ross-Macdonald model with an intra-host continuous-time Moran model, thus explicitly representing the evolution of individual parasite genomes in a traditional epidemiological framework. Implemented as a stochastic simulation, we use the model to explore relationships between measures of parasite genetic diversity and parasite prevalence, a widely-used metric of transmission intensity. First, we explore how varying parasite prevalence influences genetic diversity at equilibrium. We find that multiple genetic diversity statistics are correlated with prevalence, but the strength of the relationships depends on whether variation in prevalence is driven by host- or vector-related factors. Next, we assess the responsiveness of a variety of statistics to malaria control interventions, finding that those related to mixed infections respond quickly (∼months) whereas other statistics, such as nucleotide diversity, may take decades to respond. These findings provide insights into the opportunities and challenges associated with using genetic data to monitor malaria epidemiology.

Malaria in the 'Omics Era'

Genomics has revolutionised the study of the biology of parasitic diseases. The first Eukaryotic parasite to have its genome sequenced was the malaria parasite Plasmodium falciparum. Since then, Plasmodium genomics has continued to lead the way in the study of the genome biology of parasites, both in breadth—the number of Plasmodium species’ genomes sequenced—and in depth—massive-scale genome re-sequencing of several key species. Here, we review some of the insights into the biology, evolution and population genetics of Plasmodium gained from genome sequencing, and look at potential new avenues in the future genome-scale study of its biology.

Co-Therapy of Albendazole and Dexamethasone Reduces Pathological Changes in the Cerebral Parenchyma of Th-1 and Th-2 Dominant Mice Heavily Infected with Angiostrongylus cantonensis: Histopathological and RNA-seq Analyses

Administration of albendazole alone was not very suitable for the treatment of cerebral angiostrongyliasis. This study was designed to evaluate the effects of the co-therapy of this drug and dexamethasone in Th-1 and Th-2 dominant mice infected with Angiostrongylus cantonensis. Each of BALB/c and C57BL/6 mice infected with 50 A. cantonensis third-stage larvae were administered albendazole (10 mg/kg/day) alone, dexamethasone (0.5 mg/kg/day) alone, or co-therapy of the two drugs from day 7 or 14 post-infection for 7 or 14 days. After sacrifice, coronal slices were prepared from five brain regions and stained with hematoxylin and eosin. Eight pathological changes were employed to determine the therapeutic effectiveness using a scoring system. RNA-seq analysis was performed to confirm the histopathological findings. The infected BALB/c and C57BL/6 mice had similar patterns in the pathological changes. Meningitis, hemorrhage, size of worms, and encephalitis in the cerebral parenchyma were slighter in the mice treated with co-therapy than the remaining groups. Mice treated from day 14 had more severe changes than those from day 7. The histopathological findings were found to be consistent to immune responses determined by RNA-seq analysis. Co-therapy was determined to reduce pathological changes after administration to mice infected with A. cantonensis.

Cross-border malaria in Northern Brazil

BACKGROUND

Cross-border malaria is a major barrier to elimination efforts. Along the Venezuela-Brazil-Guyana border, intense human mobility fueled primarily by a humanitarian crisis and illegal gold mining activities has increased the occurrence of cross-border cases in Brazil. Roraima, a Brazilian state situated between Venezuela and Guyana, bears the greatest burden. This study analyses the current cross-border malaria epidemiology in Northern Brazil between the years 2007 and 2018.

METHODS

De-identified data on reported malaria cases in Brazil were obtained from the Malaria Epidemiological Surveillance Information System for the years 2007 to 2018. Pearson's Chi-Square test of differences was utilized to assess differences between characteristics of cross-border cases originating from Venezuela and Guyana, and between border and transnational cases. A logistic regression model was used to predict imported status of cases.

RESULTS

Cross-border cases from Venezuela and Guyana made up the majority of border and transnational cases since 2012, and Roraima remained the largest receiving state for cross-border cases over this period. There were significant differences in the profiles of border and transnational cases originating from Venezuela and Guyana, including type of movement and nationality of patients. Logistic regression results demonstrated Venezuelan and Guyanese nationals, Brazilian miners, males, and individuals of working age had heightened odds of being an imported case. Furthermore, Venezuelan citizens had heightened odds of seeking care in municipalities adjacent Venezuela, rather than transnational municipalities.

CONCLUSIONS

Cross-border malaria contributes to the malaria burden at the Venezuela-Guyana-Brazil border. The identification of distinct profiles of case importation provides evidence on the need to strengthen surveillance at border areas, and to deploy tailored strategies that recognize different mobility routes, such as the movement of refuge-seeking individuals and of Brazilians working in mining.

Genomic-informed pathogen surveillance in Africa: opportunities and challenges

The ongoing COVID-19 pandemic has highlighted the need to incorporate pathogen genomics for enhanced disease surveillance and outbreak management in Africa. The genomics of SARS-CoV-2 has been instrumental to the timely development of diagnostics and vaccines and in elucidating transmission dynamics. Global disease control programmes, including those for tuberculosis, malaria, HIV, foodborne pathogens, and antimicrobial resistance, also recommend genomics-based surveillance as an integral strategy towards control and elimination of these diseases. Despite the potential benefits, capacity remains low for many public health programmes in Africa. The COVID-19 pandemic presents an opportunity to reassess and strengthen surveillance systems and potentially integrate emerging technologies for preparedness of future epidemics and control of endemic diseases. We discuss opportunities and challenges for integrating pathogen genomics into public health surveillance systems in Africa. Improving accessibility through the creation of functional continent-wide networks, building multipathogen sequencing cores, training a critical mass of local experts, development of standards and policies to facilitate best practices for data sharing, and establishing a community of practice of genomics experts are all needed to use genomics for improved disease surveillance in Africa. Coordination and leadership are also crucial, which the Africa Centres for Disease Control and Prevention seeks to provide through its institute for pathogen genomics.

Describing the current status of Plasmodium falciparum population structure and drug resistance within mainland Tanzania using molecular inversion probes

High-throughput Plasmodium genomic data is increasingly useful in assessing prevalence of clinically important mutations and malaria transmission patterns. Understanding parasite diversity is important for identification of specific human or parasite populations that can be targeted by control programmes, and to monitor the spread of mutations associated with drug resistance. An up-to-date understanding of regional parasite population dynamics is also critical to monitor the impact of control efforts. However, this data is largely absent from high-burden nations in Africa, and to date, no such analysis has been conducted for malaria parasites in Tanzania countrywide. To this end, over 1,000 P. falciparum clinical isolates were collected in 2017 from 13 sites in seven administrative regions across Tanzania, and parasites were genotyped at 1,800 variable positions genome-wide using molecular inversion probes. Population structure was detectable among Tanzanian P. falciparum parasites, approximately separating parasites from the northern and southern districts and identifying genetically admixed populations in the north. Isolates from nearby districts were more likely to be genetically related compared to parasites sampled from more distant districts. Known drug resistance mutations were seen at increased frequency in northern districts (including two infections carrying pfk13-R561H), and additional variants with undetermined significance for antimalarial resistance also varied by geography. Malaria Indicator Survey (2017) data corresponded with genetic findings, including average region-level complexity-of-infection and malaria prevalence estimates. The parasite populations identified here provide important information on extant spatial patterns of genetic diversity of Tanzanian parasites, to which future surveys of genetic relatedness can be compared.

Spatial and genetic clustering of Plasmodium falciparum and Plasmodium vivax infections in a low-transmission area of Ethiopia

The distribution of malaria infections is heterogeneous in space and time, especially in low transmission settings. Understanding this clustering may allow identification and targeting of pockets of transmission. In Adama district, Ethiopia, Plasmodium falciparum and P. vivax malaria patients and controls were examined, together with household members and immediate neighbors. Rapid diagnostic test and quantitative PCR (qPCR) were used for the detection of infections that were genetically characterized by a panel of microsatellite loci for P. falciparum (26) and P. vivax (11), respectively. Individuals living in households of clinical P. falciparum patients were more likely to have qPCR detected P. falciparum infections (22.0%, 9/41) compared to individuals in control households (8.7%, 37/426; odds ratio, 2.9; 95% confidence interval, 1.3–6.4; P = .007). Genetically related P. falciparum, but not P. vivax infections showed strong clustering within households. Genotyping revealed a marked temporal cluster of P. falciparum infections, almost exclusively comprised of clinical cases. These findings uncover previously unappreciated transmission dynamics and support a rational approach to reactive case detection strategies for P. falciparum in Ethiopia.

Molecular surveillance of antimalarial partner drug resistance in sub-Saharan Africa: a spatial-temporal evidence mapping study

Background

Molecular markers for antimalarial drug resistance can be used to rapidly monitor the emergence and spatial distribution of resistance to artemisinin-based combination therapies (ACTs). Little has been done to analyse molecular surveillance efforts or to assess surveillance coverage. This study aimed to develop an evidence map to characterise the spatial-temporal distribution and sampling methodologies of drug resistance surveillance in sub-Saharan Africa, specifically focusing on markers associated with ACT partner drugs.

Methods

By use of a systematic search, we identified studies that reported data on the following mutations associated with ACT partner drug resistance: pfmdr1 Asn86Tyr, Tyr184Phe, Asp1246Tyr, and copy number variation and pfcrt Lys76Thr, with sample collection occurring in sub-Saharan Africa between Jan 1, 2004, and Dec 31, 2018, corresponding to the uptake of ACTs. For each identified study, we extracted information on its sampling and laboratory methods, author and publication affiliations, years of sampling and of publication, geographic coordinates of the study sites, and prevalence of the partner drug resistance-associated markers. We used linear models to test whether urbanicity, population density, and endemicity were predictors of drug resistance survey sites and linear regressions to identify associations between the number of resistance surveys within a given country and the at-risk malaria population in 2010, the per-capita GDP in 2010, and the mean amount of funding directed to malaria and to determine trends in marker prevalence over time. For country case studies with three or more datapoints, we assessed global spatial autocorrelation using Moran's I.

Findings

Our search yielded 254 studies encompassing 492 year-specific and location-specific surveys from 35 malaria-endemic countries, the most complete set of molecular partner drug surveillance data to date. We observed a median time lag of 3·1 years (95% CI 1·0-7·7) from final sample acquisition to publication. 22 (49%) of the 44 countries in the study region conducted, on average, one or fewer studies every 3 years. The locations of surveillance sites were positively associated with urbanicity (p<0·0001), and the abundance of country-level data was associated with reported donor funding in 2004-18 (p=0·0011) and local government funding in 2004-09 (p=0·014). Nearly all molecular markers displayed significant regional trends over time and global spatial autocorrelation in space. For selected countries with more widespread coverage of surveillance data, some markers also displayed spatial heterogeneity.

Interpretation

In most sub-Saharan countries, molecular data on antimalarial resistance might not be representative of the temporal and geographic heterogeneity of partner drug resistance, and likely do not represent the true spatially dependent distribution of partner drug resistance. Our results highlight several inefficiencies that can be improved upon to develop more accurate data landscapes, including the expansion of sentinel surveillance systems, syndemic usage of research samples, and increased participation in reporting published and unpublished data to centralised platforms.

Sensitive, highly multiplexed sequencing of microhaplotypes from the Plasmodium falciparum heterozygome

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, whole-genome sequencing 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 expected heterozygosity = 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 dried blood spots with 100 parasites/µL). In silico analyses revealed that microhaplotypes provided much higher resolution to discriminate related from unrelated polyclonal infections than biallelic single-nucleotide polymorphism barcodes.

Conclusions

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.

Implementing parasite genotyping into national surveillance frameworks: feedback from control programmes and researchers in the Asia-Pacific region

The Asia-Pacific region faces formidable challenges in achieving malaria elimination by the proposed target in 2030. Molecular surveillance of Plasmodium parasites can provide important information on malaria transmission and adaptation, which can inform national malaria control programmes (NMCPs) in decision-making processes. In November 2019 a parasite genotyping workshop was held in Jakarta, Indonesia, to review molecular approaches for parasite surveillance and explore ways in which these tools can be integrated into public health systems and inform policy. The meeting was attended by 70 participants from 8 malaria-endemic countries and partners of the Asia Pacific Malaria Elimination Network. The participants acknowledged the utility of multiple use cases for parasite genotyping including: quantifying the prevalence of drug resistant parasites, predicting risks of treatment failure, identifying major routes and reservoirs of infection, monitoring imported malaria and its contribution to local transmission, characterizing the origins and dynamics of malaria outbreaks, and estimating the frequency of Plasmodium vivax relapses. However, the priority of each use case varies with different endemic settings. Although a one-size-fits-all approach to molecular surveillance is unlikely to be applicable across the Asia-Pacific region, consensus on the spectrum of added-value activities will help support data sharing across national boundaries. Knowledge exchange is needed to establish local expertise in different laboratory-based methodologies and bioinformatics processes. Collaborative research involving local and international teams will help maximize the impact of analytical outputs on the operational needs of NMCPs. Research is also needed to explore the cost-effectiveness of genetic epidemiology for different use cases to help to leverage funding for wide-scale implementation. Engagement between NMCPs and local researchers will be critical throughout this process.

Investigating the drivers of the spatio-temporal patterns of genetic differences between Plasmodium falciparum malaria infections in Kilifi County, Kenya

Knowledge of how malaria infections spread locally is important both for the design of targeted interventions aiming to interrupt malaria transmission and the design of trials to assess the interventions. A previous analysis of 1602 genotyped Plasmodium falciparum parasites in Kilifi, Kenya collected over 12 years found an interaction between time and geographic distance: the mean number of single nucleotide polymorphism (SNP) differences was lower for pairs of infections which were both a shorter time interval and shorter geographic distance apart. We determine whether the empiric pattern could be reproduced by a simple model, and what mean geographic distances between parent and offspring infections and hypotheses about genotype-specific immunity or a limit on the number of infections would be consistent with the data. We developed an individual-based stochastic simulation model of households, people and infections. We parameterized the model for the total number of infections, and population and household density observed in Kilifi. The acquisition of new infections, mutation, recombination, geographic location and clearance were included. We fit the model to the observed numbers of SNP differences between pairs of parasite genotypes. The patterns observed in the empiric data could be reproduced. Although we cannot rule out genotype-specific immunity or a limit on the number of infections per individual, they are not necessary to account for the observed patterns. The mean geographic distance between parent and offspring malaria infections for the base model was 0.4 km (95% CI 0.24, 1.20), for a distribution with 58% of distances shorter than the mean. Very short mean distances did not fit well, but mixtures of distributions were also consistent with the data. For a pathogen which undergoes meiosis in a setting with moderate transmission and a low coverage of infections, analytic methods are limited but an individual-based model can be used with genotyping data to estimate parameter values and investigate hypotheses about underlying processes.

Strengthening Surveillance Systems for Malaria Elimination by Integrating Molecular and Genomic Data

Unprecedented efforts in malaria control over the last 15 years have led to a substantial decrease in both morbidity and mortality in most endemic settings. However, these progresses have stalled over recent years, and resurgence may cause dramatic impact on both morbidity and mortality. Nevertheless, elimination efforts are currently going on with the objective of reducing malaria morbidity and mortality by 90% and malaria elimination in at least 35 countries by 2030. Strengthening surveillance systems is of paramount importance to reach those targets, and the integration of molecular and genomic techniques into routine surveillance could substantially improve the quality and robustness of data. Techniques such as polymerase chain reaction (PCR) and quantitative PCR (qPCR) are increasingly available in malaria endemic countries, whereas others such as sequencing are already available in a few laboratories. However, sequencing, especially next-generation sequencing (NGS), requires sophisticated infrastructure with adequate computing power and highly trained personnel for data analysis that require substantial investment. Different techniques will be required for different applications, and cost-effective planning must ensure the appropriate use of available resources. The development of national and sub-regional reference laboratories could help in minimizing the resources required in terms of equipment and trained staff. Concerted efforts from different stakeholders at national, sub-regional, and global level are needed to develop the required framework to establish and maintain these reference laboratories.