In 2019, over 200 million cases of malaria and over 400,000 deaths were recorded (World Health Organisation, 2020). Plasmodium falciparum remains the primary cause of malaria in humans. Fast and accurate diagnosis and treatment of clinical episodes are key components of malaria control. Diagnosis is commonly performed either by light microscopy, or rapid diagnostic tests (RDTs). RDTs are lateral flow devices that detect parasite proteins in human blood through immunohistochemistry. Light microscopy requires basic lab infrastructure and skilled microscopists. In contrast, RDTs require minimal infrastructure and training, and results are available within approximately 15 min at a cost of less than 1 USD per test. RDTs are the only field-deployable diagnostic tool available at peripheral health centers and for community screening to diagnose asymptomatic infections, for example through reactive case detection (RCD; Stuck et al., 2020). In 2016, over 300 million RDTs were used by malaria control programs (WHO, 2017).

The most sensitive RDTs for P. falciparum rely on the detection of Histidine-Rich Protein 2 (HRP2) (Li et al., 2017). HRP2 is a highly expressed secreted protein, and thus an ideal target for diagnosis. It is also the target for a new generation of ultra-sensitive RDTs with a limit of detection of <100 parasites/µl (Acquah et al., 2021; Hofmann et al., 2019). While alternative RDTs detecting other proteins, for example parasite lactase dehydrogenase (pLDH), or aldolase, are available, they are generally less sensitive (World Health Organisation, 2016a; World Health Organisation, 2018). HRP2-based RDTs can also detect HRP3, a structurally similar protein sharing multiple epitopes with HRP2.

In 2010, a report revealed that a large proportion of P. falciparum parasites in Peru did not carry the hrp2 gene (Gamboa et al., 2010), and thus could not be detected by HRP2-based RDTs. Since then, an increasing number of reports from Latin America (Maltha et al., 2012; Sáenz et al., 2015; Murillo Solano et al., 2015; Dorado et al., 2016; Akinyi Okoth et al., 2015), Africa (Amoah et al., 2016; Koita et al., 2012; Parr et al., 2017; Berhane et al., 2018; Menegon et al., 2017; Bharti et al., 2016; Li et al., 2015; Kumar et al., 2013), and Asia Johora et al., 2017; Pati et al., 2018 found varying proportions of parasites with hrp2 deletion, reaching up to 80% of clinical cases in certain hospitals in Eritrea (Berhane et al., 2018). In addition, hrp3 can be deleted. The deletion of either hrp2 or hrp3, or both genes, has no known impact on parasite fitness. RDTs can yield a positive result if hrp2 is deleted but hrp3 is expressed, but the sensitivity of the RDT is lower in this case (Kong et al., 2021).

Molecular surveillance to assess the frequency of hrp2 and hrp3 deletion is crucial to decide whether HRP2-based RDTs can be used (Cheng et al., 2014). The WHO recommends to use alternative diagnostics if the prevalence of hrp2 deletion is above 5% (World Health Organisation, 2016b). At this level, the number of tests that are false-negative tests because of hrp2 deletion will exceed the number of tests that are false-negative tests because alternative diagnostics offer a lower sensitivity (World Health Organisation, 2016b). The prevalence of hrp2 deletion has been found to differ substantially within countries (Murillo Solano et al., 2015; Parr et al., 2017), thus the choice of diagnostics might need to be adapted at subnational level. The feasibility of such approaches depends on the organization of the national control program, barriers to transmission within-country, and other factors. Where low levels of deletions are present, HRP2-based RDTs remain a highly useful tool for diagnosis.

Deletion screening has been classically done using nested PCR (nPCR) followed by gel electrophoresis (Cheng et al., 2014). Absence of a band is interpreted as deletion. False-negative results could occur when PCR conditions are suboptimal, or when parasite density is low and amplification is stochastic. To overcome this limitation, threefold repetition of the nested hrp2 PCR and a control PCR (e.g., msp2 or glurp) is recommended (Cheng et al., 2014). As a result, for each sample 12 PCRs need to be run. Deletion status might remain unresolved if results differ among replicates. As an additional problem, multiple clone P. falciparum infections are common in most endemic settings (Lopez and Koepfli, 2021; Grignard et al., 2020). In case of a multiple clone infection with a wild-type parasite and a parasite carrying the deletion, the wild-type parasite will result in a band on the gel when using the nPCR assay. While multiple clone infections will result in a positive RDT (if the density of the wild-type strain is sufficiently high), their presence can mask the presence of deletions, resulting in an underestimation of the frequency of deletion (Watson et al., 2019). More recently, quantitative PCR (qPCR) protocols for hrp2/hrp3 deletion typing were published (Grignard et al., 2020; Schindler et al., 2019; Kreidenweiss et al., 2019), greatly enhancing throughput. However, when parasite densities are low, considerable variation in quantification is observed between replicates (Koepfli et al., 2016). While quantification is accurate in the case of clinical samples that are high density, accurate estimates of the population frequency of deletions might require typing of asymptomatic, low-density samples. As a result of the technical challenges for accurate typing, maps of hrp2 deletion frequency remain scattered and incomplete.

We have developed a novel method for the typing of hrp2 and hrp3 deletions based on droplet digital PCR (ddPCR). ddPCR yields highly accurate quantification of parasites (Koepfli et al., 2016). In a ddPCR experiment, the reaction volume is partitioned into approximately 15,000 microdroplets, which are then subject to endpoint PCR. Each droplet function as an individual PCR reaction, with amplification occurring if the droplet contains template DNA. ddPCR offers multiple benefits over qPCR for quantification. Template DNA concentration can be derived directly from the number of positive and negative droplets using Poisson statistics. No external standards are required. Quantification is reliable as long as positive and negative droplets are separated, even if amplification is suboptimal, for example in the case of PCR inhibitors. Amplification efficiency, which is crucial for accurate quantification by qPCR, is thus not relevant in a ddPCR experiment. Using two different probes, two targets can be quantified in a single reaction well, for example a control gene and a target gene. Because the target DNA of each assay is partitioned into separate droplets (with the exception of a few droplets partitioned into the same droplet in case of high-density infections), no competition between assays occurs, thus circumventing a common problem of multiplexed qPCR assays. As each droplet with a template can be considered a ‘within-well replicate’, a single well offers the sensitivity and specificity of a large number of replicates by nPCR or qPCR. The risk of false-negative results (i.e., no amplification when the template is present) is thus minimal compared to nPCR or qPCR. A sample negative for hrp2/3 and the control gene (e.g., due to pipetting error) will not be classified as carrying a deletion and will be excluded from any calculations on deletion frequency in a population. The novel assay greatly reduces the number of reactions to be run compared to gel-based assays, showed high sensitivity and accuracy, and can detect the deletion in mixed infections. The assay was extensively validated using culture strains, and field samples from Kenya, Zanzibar/Tanzania, Ethiopia, Ghana, Brazil, and Ecuador.

Molecular surveillance of the extent of hrp2 and hrp3 deletions is a high priority task to select the optimal tools for P. falciparum diagnosis. The novel assay based on ddPCR yielded highly accurate results, and was able to detect mixed infections with wild-type parasites and parasites carrying hrp2 deletion. The good performance of the assay was shown by typing samples from six countries. The samples reflected a range of parasite densities, from low-density asymptomatic infections to high-density clinical infections, and sites represented a range in the frequency of hrp2 and/or hrp3 deletions. Across over 800 field samples screened, <10 samples needed to be repeated because of poor separation between negative and positive droplets, or failure of droplet generation.

The assay can be used to screen samples for P. falciparum positivity based on the result for tRNA, and hrp2 or hrp3 deletion in a single assay. Alternatively, it can be used to type samples prior determined P. falciparum positive by microscopy or another molecular assay. High sensitivity is required for accurate typing of low-density infections. We validated a threshold of two droplets positive for tRNA as the limit of detection. When 9 µl of DNA are used as template, this results in a theoretical limit of detection of 0.33 parasites/µl. Sensitivity can be further increased by concentrating the DNA prior to typing.

The ddPCR assay showed increased sensitivity and specificity to type low-density infections compared to nPCR. Out of 248 asymptomatic samples from western Kenya, 95% could be analyzed by ddPCR, but only 85% by nPCR. More importantly, results on deletion status differed substantially. By ddPCR, no deletions were observed. By nPCR, no band was observed for hrp2 in 8% of samples that had a positive band for the control gene (msp2) in all three replicates. Thus, the frequency of deletion was above the 5% threshold, and it would be erroneously recommended to discontinue the use of HRP2-based RDTs. The frequency of deletion by nPCR was similar to a previous study conducted in a nearby site in western Kenya that found hrp2 deletion in 8/89 samples using nPCR (Beshir et al., 2017). The direct comparison of ddPCR and nPCR in a large number of samples points to a possible overestimation of hrp2 deletion frequency by studies relying on nPCR. Further systematic comparison with qPCR-based assays (Grignard et al., 2020; Kreidenweiss et al., 2019; Schindler et al., 2019) will be required to determine the sensitivity and specificity of each assay.

In almost all transmission settings, polyclonal P. falciparum infections are frequent (Lopez and Koepfli, 2021). Using a gel-based assay for deletion typing, in a mixed infection with a wild-type parasite and a parasite carrying a deletion, the wild-type parasite will produce a band and mask the deletion. These infections can be detected by RDT, but depending on the proportion of polyclonal infections, they can result in pronounced underestimation of the true frequency of deletion (Watson et al., 2019). The highly accurate quantification by ddPCR allows detection of mixed infections. Based on experimental mixtures of 3D7 and Dd2, and field samples, mixed infections were reliably detected when at least 40% of parasites carried the deletion, and at densities above 100 parasites per reaction. Using a well-working qPCR assay with an amplification efficacy of 100%, a similar difference between hrp2 and tRNA copy numbers would result in less than half a cycle difference. This is within the normal variation of technical replicates (Koepfli et al., 2016; Hindson et al., 2013), and thus such mixed infections could not be detected by qPCR.

Twenty-nine samples from Zanzibar and 16 from Ghana had tested negative by HRP2-based RDT despite high density of 100 to >10,000 parasites/µl (Stuck et al., 2020), yet no hrp2 deletions were observed in these populations. False-negative RDT results might be caused due to incorrect handling, prozone effect (Gillet et al., 2009), or sequence variation without deletion of the hrp2 gene (Nderu et al., 2019). The finding corroborates the importance of molecular typing. Studies comparing microscopy and RDT results can give important clues for the presence of deletions (Berhane et al., 2017), but molecular typing is required for confirmation (Berhane et al., 2018).

Though not reported in the literature, deletion of hrp2 exon 1 only, but not exon 2, could result in a lack of expression of HRP2. In this scenario, the hrp2 exon 2 assay would not show any deletion, yet HRP2-based RDTs would show a false-negative result. In this study, no discrepancy was observed between deletion status for hrp2 exons 1 and 2. Thus, for future surveillance, it is recommended to only type samples for hrp2 exon 2 and hrp3. In case of negative RDTs despite no hrp2 exon 2 deletion, typing for exon 1 can be done.

No hrp2 deletions were found in Zanzibar, and Kenya, and one mixed infection in Ghana. The data from Ghana contrasts an earlier study that reported a frequency of deletion of >30% (Amoah et al., 2016). A single hrp2 deletion was found in southwestern Ethiopia. This is in stark contrast to very high levels of deletion in western Ethiopia (Alemayehu et al., 2021), Eritrea (Berhane et al., 2018), and Sudan (Prosser et al., 2021). The results corroborate the need for studies assessing hrp2 deletion and selection of diagnostic tools at subnational level.

Contrasting findings were obtained from the sample sets from South America, with very high levels of deletion in Brazil, and no deletions in Ecuador. Brazil and Ecuador share no borders, and the amount of human migration is limited. The results add to the heterogeneous pattern of hrp2/hrp3 deletion in South America, with high frequency of hrp2 deletion in the Amazon (Gamboa et al., 2010; Murillo Solano et al., 2015; Góes et al., 2020), but low levels among the Pacific coast (Sáenz et al., 2015; Murillo Solano et al., 2015). An outbreak of parasites with hrp2 deletion at the Peruvian Pacific coast was caused by infections imported from the Amazon (Baldeviano et al., 2015). Brazil is committed to P. falciparum elimination, and the samples typed originated from the main hotspot of transmission (Ferreira and Castro, 2016). RDTs remain relatively little used in Brazil. Microscopy remains the diagnostic method of choice, and RDTs are mostly used in remote areas, for example, populations from Amerindian Reserves and some traditional riverine communities with no access to conventional microscopy. The frequency of hrp2 deletion in Brazil clearly exceeds the 5% threshold, thus it is recommended that no HRP2-based RDTs are used.

To determine whether the frequency of the deletion exceeds the threshold of 5%, the WHO recommends systematic surveillance and typing of a minimum of 370 per site (World Health Organization, 2020). Limitations of the molecular assays available for typing have been a major hindrance to type that number of samples in many sites where hrp2 or hrp3 deletion is suspected. Even a low proportion of false-negative results could impact the decision to discontinue HRP2-based RDTs. As a result of the scarcity of field data, the spatiotemporal dynamics of hrp2 deletion in parasite populations, drivers of the deletion, potential fitness costs, and clinical consequences remain poorly understood. Results from simulation studies suggest that the use of hrp2-based RDTs selects for hrp2-negative parasites, in particular, if transmission levels are low and a large proportion of all infections turn clinical and result in treatment seeking (Gatton et al., 2017; Watson et al., 2017). While digital PCR is less common than nPCR or qPCR, it has been successfully established in malaria-endemic countries. The assay is run in 96-well format; thus throughput is comparable to qPCR, and assay setup is similarly straightforward. While costs of digital PCR instruments and reagents are moderately higher than for qPCR, they have declined recently.

In conclusion, the novel, high-throughput, highly sensitive and specific ddPCR assay will facilitate molecular surveillance for hrp2 and hrp3 deletion, and thus aid the selection of diagnostic tests to accelerate malaria control and elimination. Data obtained using this assay will help to understand the evolutionary processes underlying the de novo emergence and spread of the deletion.

All data are provided in supplementary file S3.

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Author details

1. Claudia A Vera-Arias

   University of Notre Dame, Notre Dame, United States

   Contribution

   Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing - review and editing

   Competing interests

   No competing interests declared

2. Aurel Holzschuh

   1. University of Notre Dame, Notre Dame, United States
   2. Swiss Tropical and Public Health Institute, Allschwil, Switzerland

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-2681-1114

3. Colins O Oduma

   1. Kenya Medical Research Institute-Centre for Global Health Research, Kisumu, Kenya
   2. Department of Biochemistry and Molecular Biology, Egerton University, Nakuru, Kenya

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

4. Kingsley Badu

   Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-7886-5528

5. Mutala Abdul-Hakim

   Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

6. Joshua Yukich

   Tulane University, New Orleans, United States

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6160-5295

7. Manuel W Hetzel

   1. Swiss Tropical and Public Health Institute, Allschwil, Switzerland
   2. University of Basel, Basel, Switzerland

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

8. Bakar S Fakih

   1. Swiss Tropical and Public Health Institute, Allschwil, Switzerland
   2. University of Basel, Basel, Switzerland
   3. Ifakara Health Institute, Dar es Salaam, United Republic of Tanzania

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

9. Abdullah Ali

   Zanzibar Malaria Elimination Programme, Zanzibar, Zanzibar, United Republic of Tanzania

   Contribution

   Investigation, Writing - review and editing

   Competing interests

   No competing interests declared

10. Marcelo U Ferreira

    University of São Paulo, São Paulo, Brazil

    Contribution

    Investigation, Writing - review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-5293-9090

11. Simone Ladeia-Andrade

    Laboratory of Parasitic Diseases, Fiocruz, Rio de Janeiro, Brazil

    Contribution

    Investigation, Writing - review and editing

    Competing interests

    No competing interests declared

12. Fabián E Sáenz

    Centro de Investigación para la Salud en América Latina, Facultad de Ciencias Exactas y Naturales, Pontificia Universidad Católica del Ecuador, Quito, Ecuador

    Contribution

    Investigation, Writing - review and editing

    Competing interests

    No competing interests declared

13. Yaw Afrane

    Department of Medical Microbiology, University of Ghana, Accra, Ghana

    Contribution

    Investigation, Writing - review and editing

    Competing interests

    No competing interests declared

14. Endalew Zemene

    Tropical and Infectious Diseases Research Center, Jimma University, Jimma, Ethiopia

    Contribution

    Investigation, Writing - review and editing

    Competing interests

    No competing interests declared

15. Delenasaw Yewhalaw

    Tropical and Infectious Diseases Research Center, Jimma University, Jimma, Ethiopia

    Contribution

    Investigation, Writing - review and editing

    Competing interests

    No competing interests declared

16. James W Kazura

    Case Western Reserve University, Cleveland, United States

    Contribution

    Investigation, Writing - review and editing

    Competing interests

    No competing interests declared

17. Guiyun Yan

    Program in Public Health, University of California, Irvine, Irvine, United States

    Contribution

    Investigation, Writing - review and editing

    Competing interests

    No competing interests declared

18. Cristian Koepfli

    University of Notre Dame, Notre Dame, United States

    Contribution

    Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, Visualization, Writing - original draft, Writing - review and editing

    For correspondence

    ckoepfli@nd.edu

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-9354-0414

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