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Background:
Systematic Review

Advances in Malaria Diagnostic Methods in Resource-Limited Settings: A Systematic Review

by
Akua K. Yalley
1,
Joyous Ocran
2,
Jacob E. Cobbinah
2,
Evangeline Obodai
3,
Isaac K. Yankson
4,
Anna A. Kafintu-Kwashie
1,
Gloria Amegatcher
1,
Isaac Anim-Baidoo
1,
Nicholas I. Nii-Trebi
1,* and
Diana A. Prah
5,6,*
1
Department of Medical Laboratory Sciences, School of Biomedical and Allied Health Sciences, University of Ghana, Korle Bu, Accra P.O. Box KB 143, Ghana
2
Department of Biomedical Sciences, School of Allied Health Sciences, University of Cape Coast, PMB, Cape Coast, Ghana
3
Department of Virology, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra P.O. Box LG 581, Ghana
4
CSIR-Building and Road Research Institute, Kumasi P.O. Box UP40, Kumasi, Ghana
5
West African Centre for Cell Biology of Infectious Pathogens, University of Ghana, Legon, Accra P.O. Box LG 54, Ghana
6
Department of Science Laboratory Technology, Faculty of Applied Sciences, Accra Technical University, Barnes Road, Accra P.O. Box GP 561, Ghana
*
Authors to whom correspondence should be addressed.
Trop. Med. Infect. Dis. 2024, 9(9), 190; https://doi.org/10.3390/tropicalmed9090190
Submission received: 27 June 2024 / Revised: 31 July 2024 / Accepted: 19 August 2024 / Published: 23 August 2024
(This article belongs to the Special Issue Epidemiology, Detection and Treatment of Malaria)
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Abstract

Malaria continues to pose a health challenge globally, and its elimination has remained a major topic of public health discussions. A key factor in eliminating malaria is the early and accurate detection of the parasite, especially in asymptomatic individuals, and so the importance of enhanced diagnostic methods cannot be overemphasized. This paper reviewed the advances in malaria diagnostic tools and detection methods over recent years. The use of these advanced diagnostics in lower and lower-middle-income countries as compared to advanced economies has been highlighted. Scientific databases such as Google Scholar, PUBMED, and Multidisciplinary Digital Publishing Institute (MDPI), among others, were reviewed. The findings suggest important advancements in malaria detection, ranging from the use of rapid diagnostic tests (RDTs) and molecular-based technologies to advanced non-invasive detection methods and computerized technologies. Molecular tests, RDTs, and computerized tests were also seen to be in use in resource-limited settings. In all, only twenty-one out of a total of eighty (26%) low and lower-middle-income countries showed evidence of the use of modern malaria diagnostic methods. It is imperative for governments and other agencies to direct efforts toward malaria research to upscale progress towards malaria elimination globally, especially in endemic regions, which usually happen to be resource-limited regions.

1. Introduction

Malaria elimination has been a focal topic of public health discussions for the past decade or more. Despite being a tropically endemic parasitic infection, the impact of malaria is far reaching and remains a global health concern. The 2023 World Health Organization (WHO) report states that malaria cases rose to an estimated 249 million in 2022, with an increase of 5 million more cases from the year 2021 [1]. Although relentless efforts are being made and strategies put in place, much more is required to free our globe of the parasitic infection, particularly in indigenous malaria-endemic countries such as a number of sub-Saharan African countries where most cases occur [2].
Central to eliminating malaria is early, accurate detection, quantification, and differentiation of the parasitic infection, especially among asymptomatic persons. Asymptomatic plasmodium-infected individuals represent a major threat to malaria elimination worldwide as they do not show signs of clinical disease yet serve as parasite reservoirs and significantly contribute to the spread of the infection [3]. Notably, the majority of these asymptomatic infections are missed by conventional diagnostic techniques. As a result, the need for reliable, sensitive, and specific diagnostic or detection methods arises, which would also be useful for monitoring any decline in malaria transmission [4].
Technologies for malaria diagnosis have advanced in recent years; however, certain factors, such as the lack of laboratory infrastructure, operational costs, electricity requirements, and special operation expertise, have impeded the implementation of these advanced techniques in the vast majority of malaria endemic areas. This is especially the case when it comes to molecular testing, as these tests can be particularly expensive in addition to other challenges not only for malaria but for other infectious diseases [5]. The WHO describes microscopy (thin and thick film) as the primary method of detection [6]. Though microscopy is extensively used, it is unable to adequately detect low parasitemia, which is essential for effective treatment and subsequent elimination of the parasitic infection [7]. In addition, it is a laborious process requiring much expertise and experience for accurate diagnosis [4,8]. Other concerns have been the invasive approach of this technique, where blood samples are collected after a painful pierce of a needle, and yet an accurate diagnosis unassuredly relies solely on the discretion of the laboratory scientist. In several developing countries, there is inadequate expertise, equipment, and supplies required for accurate detection; as such, there are greater risks of contamination and false diagnosis [9]. Furthermore, it becomes more unreliable and difficult to distinguish low level infections as transmissions decline; hence, there is a need for alternative approaches to detection as elimination is being considered [4].
Can there be a faster, more specific, and more sensitive method of detecting malaria that can easily be implemented in resource-limited areas? The question remains among scientists globally. Can malaria be eliminated and many more lives saved by the emergence of technologies that offer early detection and differentiation of very minimal malarial infections? Does mankind stand a chance of advancement towards needle-free malaria detection, point-of-care devices, and personalized malaria medicine? For lower and lower-middle-income countries, which total 26 and 54, respectively (Table 1), according to the World Bank, will there be access to such effective diagnostic tools [10]? It is worthy of note that 11 of these countries, all in sub-Saharan Africa, bear 70% of the global malaria burden, according to the 2023 WHO report [1] (Table 1). The above-mentioned questions are but a few that remain on the minds of scientists and thus drive research.
Subsequently, there are several techniques that have been developed over the years to address some of the challenges with the gold standard technique. Rapid diagnostic tests (RDTs) are fast and reliable. Malaria RDTs do not require skilled personnel or constant electricity, but relative to malaria microscopy, they are expensive, have a short shelf life, and only give qualitative results [11]. Other diagnostic techniques, such as enzyme-linked immunosorbent assay (ELISA), lateral flow immunoassay (LFIA), microarrays, aptamer-based biosensors, genomic sequencing, loop-mediated isothermal amplification (LAMP), nested PCR, real-time PCR, and quantitative nucleic sequence-based amplification, are usually reserved for research and surveillance purposes. These techniques have higher sensitivity and specificity for malaria diagnosis relative to microscopy and RDTs. Notwithstanding, some of them are more laborious and expensive to deploy in resource-limited areas.
This systematic review looks at traditional and modern techniques in light of their main advantages and disadvantages, as well as the countries where they have been used, with emphasis placed on lower and lower-middle-income countries. Also, emphasis would be placed on molecular-based techniques and how common they are in resource-limited settings, which usually happen to be endemic to malaria.

2. Materials and Methods

In conducting this systematic review, an accurate and authentic outcome was ensured by adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The review was registered in the open science framework database (https://doi.org/10.17605/OSF.IO/DV6Z3 (accessed on 28 June 2024)). Relevant details needed were obtained from articles published in journals and from databases up to 2022 since the search was done in early 2023. Key search phrases used for the search included “malaria detection methods”, “emerging technologies in malaria”, “recent advances in malaria detection or diagnosis”, “emerging methods in malaria diagnosis”, “traditional methods of malaria detection”, “Point of care devices for malaria detection”, “Non-invasive or needle-free malaria detection”, and “personalized malaria medicine”. Numerous articles were obtained from databases, journals, and other publishing sites, including Google Scholar, PUBMED, and MDPI databases.
From the databases, a total of 327 were identified. After the searches, the publications were sorted out to remove duplicates, and 20 publications were removed. The records were further screened to remove all incomplete, unpublished articles, and ineligible publications. With articles published in recent years under consideration, all accessible publications were considerable options, leaving out articles from journals that needed to be purchased, were restricted, or there was not a PDF version of the complete paper readily available.
Upon abstract screening, articles were selected based on the following general criteria: a traditional or modern method of malaria detection or diagnosis was investigated. A total of 276 articles were obtained, uploaded into Mendeley Reference Manager and Endnote, and carefully reviewed for full text eligibility and results presentation.
Of these articles, some investigated traditional methods, while most investigated various modern methods. Some articles were also found useful as they investigated or reviewed “emerging technologies in malaria detection” or “advances in malaria detection”, among others, and thus were used in the other parts of the review writing. After a comprehensive document screening, 167 were later removed as it was found that they did not suit the review criteria, leaving 109 to be reviewed. These articles were removed for reasons including the papers being published earlier than 2014 (for those to be analyzed), they did not specifically investigate diagnostic tools for malaria, the article obtained was not the published version, and the research scope and contents were not clear or did not focus on a possible malaria detection method. In several instances, multiple malaria detection methods were identified in a single publication; thus, the number of developed methods identified exceeded the number of publications used. Figure 1 below shows the sorting-out process.

3. Results

3.1. Traditional Methods Used for Malaria Detection

Table 2 below shows a summary of traditionally used methods of malaria detection, elaborating on their approach as well as the pros and cons of using these methods for diagnosis. Though there has been the development of new and innovative methods of detection over the years, microscopy, using thick and thin blood films coupled with Giemsa staining, remains the gold standard for the diagnosis of malaria parasitic infections [8,12].

3.2. Modern Methods Used for Malaria Detection

The quest to effectively treat malaria while gravitating towards its elimination has driven the development of various tools and assays for the diagnosis of malaria (4). Table 3 and Table 4 contain recently developed methods used in the diagnosis of malaria and where they have been used. These diagnostic approaches vary greatly, ranging from biosensors and molecular assays down to computerized algorithms and automated analyzers, which have been developed or used over recent years, no earlier than 2014. The advantages and limitations of each diagnostic method are considered, as well as the summarized procedure by which it is conducted.
Table 5 analyzes evidence of the use of some recently developed detection tools in lower and lower-middle-income countries where there are often resource limitations. The test types that featured most frequently in publications were PCR techniques (eleven), followed by RDT tests (nine), then LAMP techniques and computerized/digital deep machine learning approaches (six each). In all, twenty-one countries had publications featuring modern malaria diagnostic methods.
In Figure 2, the various methods of malaria detection reported from the identified studies have been represented graphically, indicating which diagnostic trends are being largely investigated, used more, or have gained much research interest. The chart represents malaria diagnostic developments investigated from 2014 until 2022. PCR-based methods and LAMP-based methods were the most prevalent methods.

4. Discussion

Critical to achieving effective control, treatment, and subsequent elimination of malaria is the timely detection of the parasitic infection. In the face of this threatening infection, continuous progress and innovative research are required, which leads to the development of new tools that will be useful in the fight against malaria [117]. This article reviewed the recent developments in malaria diagnostic methods and their potential for point-of-care and personalized malaria care, with special emphasis on the use of these methods in economically challenged countries.
The findings from this review suggest great advancement recently in malaria diagnostics. Research efforts by many scientists around the globe have progressed from developing improved malaria microscopy techniques into enhanced and more accurate molecular, immunological, computerized, digital methods of detection, automated analyzers, and point-of-care devices. Studies suggest that the influence of the old age infection on global health outcomes has urged on the design of more efficient diagnostics, with efforts directed at the development of point-of-care devices useful for resource-limited areas [7]. For an active drive towards the elimination of malaria, an early detection approach capable of revealing low levels of the parasitic infection is imperative [3].
As observed in Table 2, Table 3, Table 4 and Table 5, the outcome of this review indicates that recent malaria detection methods actively being used or investigated include traditional methods, molecular techniques with polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP)-based assays, and machine learning/computerized techniques (that exploit the physical and/or biological properties of Plasmodium-infected erythrocytes to enhance malaria diagnosis), among others. Figure 2 shows the frequencies of detection methods as identified from various articles published over the last decade. Several other technologies and chemical assays are also being designed to tackle the malaria burden. RDTs were among the commonly used or researched modern methods in resource-limited settings, as seen in Table 5 and Figure 2. This is not surprising since they are relatively low cost and easy to use.
Studies confirm PCR-based techniques as having widespread use globally as they are highly sensitive and capable of detecting very low parasitemia levels [3,22,35]. Polymerase chain reaction basically makes use of DNA extracted from whole blood or other samples. The process continues with denaturation, amplification, and elongation steps, after which the sensitivity and specificity of the assay can be assessed [35]. It is proposed that the PCR method, under equal reaction parameters, can diagnose all five species of the plasmodium parasitic infection [35]. Our findings reveal that a wide range of PCR assays have been developed or used over the past decade, which are less laborious and provide much faster and more accurate results [22]. Furthermore, PCR-based assays are widely preferred due to several reasons, including simultaneous species-specific detection and quantification, higher sensitivity, higher specificity, less time consuming, easy to use, and capable of diagnosing subclinical infections [13,18,22,23,41,42].
Though PCR is an effective approach to malaria detection, it is limited by the requirement of costly laboratory facilities and expertise and thus less beneficial to resource-limited areas and at the point of care [3]. Despite that, quite a number of studies in resource-limited settings, including some African countries, utilized PCR-based techniques, as shown in Table 5 and Figure 2 [13,16,18,23,25,29,35,36,37,38,40]. Other advanced PCR techniques, such as lab chip real-time PCR (LRP) and hair qPCR, were found to be suitable alternatives for point-of-care or resource-limited settings, though no evidence was found of the former currently being used or researched in lower or lower-middle-income countries [29,31]. Gómez-Luque et al. proposed that due to limitations observed, more research is required to affirm the use of the hair qPCR as an efficient technique for malaria detection [29]. The one advantage the hair qPCR has over other PCR types is the use of non-invasive samples. LRP, however, being highly sensitive, specific, and less expensive will be beneficial for diagnosis and control in malaria-endemic countries [31].
LAMP-based assays have also dominated research on malaria diagnostics. As seen in Table 3, studies have shown the development or use of various LAMP assays, which are effective malaria diagnostics [118]. Rei Yan et al. reviewed LAMP assays and found them easy to use in regions where there is limited access to clinical expertise and molecular biology equipment. Modified LAMP based assays such as multiplex LAMP with dipstick DNA chromatography, high throughput LAMP, 18S rRNA LAMP, mediated LAMP combined with lateral flow detection (LFD), etc., are highly sensitive, easy to use, consistent, convenient, cost effective, and useful in point-of-care situations [55,56,58,59], thus enabling an approach towards personalized healthcare. Table 5 provides evidence of the development and use of LAMP techniques in lower and lower-middle-income countries, including countries in sub-Saharan Africa where malaria is endemic [45,48,56,57,58,59].
Other molecular methods worthy of note as they double as point-of-care or easy-to-use methods include nuclear magnetic resonance (NMR)-based hemozoin detection, ultra-bright SERS nanorattles, recombinase-aided amplification with lateral flow dipstick assay, and dye-coupled aptamer-captured enzyme-catalyzed assay [86,104,105,110,111,112]. Though the latter two could be used in resource-limited settings due to their low cost, the study found only a dye-coupled aptamer-captured enzyme-catalyzed assay used in India [104]. Veiga and Peng identified nuclear magnetic resonance (NMR)-based hemozoin detection as having the potential of enabling personalized malaria medicine (that is, malaria treatment tailored to individual characteristics) with needleless diagnosis foresighted [119]. This technology may offer the detection of phenotypic variants, which are observable variations in characteristics among parasites of the same species as a result of genetic diversity, host–parasite interactions, or environmental factors, among others [120,121]. For example, there are drug-resistant variants, those with surface antigen variations, and variants with different clinical presentations, among others [121,122,123]. The ability to detect such variants would increase diagnostic accuracy and be considerably useful against parasite drug resistance. Acquiring these time- and patient-specific phenotypic identifiers is a basic step to personalized malaria medicine as variants continually rise [119]. The one advantage that phenotypic variant determination using NMR technology may have over nucleic acid amplification-based methods for genomic profiling is the extremely fast turnaround time for some of the devices [110]. Unfortunately, there was no evidence of such methods being used in lower and lower-middle-income countries as per the studied published data in the research articles reviewed.
Furthermore, a number of other technologies have emerged capable of point-of-care diagnosis. Unlike the traditional microscopy and commonly used RDTs, some of these methods were found to be highly sensitive, non-invasive as far as sample collection was concerned, and cost effective, even though there was no evidence that cost-effective ones were necessarily being used in economically challenged settings [85,95,99,100,101,102]. In addition to these, Aggarwal et al. classify omics-based diagnostics as another important category to malaria diagnosis and elimination [124]. Multi-omics combines genomics, proteomics, metabolomics, phenomics, and transcriptomics in the investigation of biomarkers optimal for disease diagnosis and treatment. Though each omics has individual limitations, collectively, multi-omics can lead to a more comprehensive understanding of malaria infections, which can lead to more effective treatments [124]. In this review, the only struggling economy we found using multi-omics was India. No African nation was indicated.

5. Conclusions

Given the literature reviewed, there is adequate evidence to suggest that malaria detection or diagnosis will progress significantly in the next decade and beyond towards needleless detection. This advancement will however require increased, detailed, and specified research into the various molecular identifiers and phenotypic variant characteristics of malaria infection while enhancing the accuracy, precision, and specificity of the modernized point-of-care diagnostic tools. With this in view, precedence is duly set for the use of personalized medicine in the treatment of malaria infections. Notwithstanding, the traditional thin and thick film microscopy and RDTs will continue to play an important role in the accurate detection of malaria infections, especially in resource-limited areas where there is less access to modernized diagnostic tools and little research into advanced malaria detection methods. It is, however, encouraging to see that PCR-based and LAMP-based tests were seen being utilized in these areas, including African countries. However, other modern molecular/point-of-care tests were not being utilized in sub-Saharan Africa. Findings of this study show that approximately a quarter (26%) of a total of eighty countries in low and lower-middle-income settings employ state-of-the-art methods for malaria diagnostics. This underscores the need for governments, non-governmental organizations, and funding bodies to intensify efforts towards malaria diagnostics and research in the fight against malaria.

Author Contributions

Conceptualization, A.K.Y.; methodology, A.K.Y., J.O. and J.E.C.; software, A.K.Y. and J.O.; validation, A.K.Y., J.O., J.E.C., N.I.N.-T., E.O., I.K.Y., A.A.K.-K., G.A., I.A.-B. and D.A.P.; formal analysis, A.K.Y. and J.O.; investigation, A.K.Y., J.O. and J.E.C.; resources, A.K.Y., J.O., J.E.C., N.I.N.-T., E.O., I.K.Y., A.A.K.-K., G.A., I.A.-B. and D.A.P.; writing—original draft preparation, A.K.Y., J.O. and J.E.C.; writing—review and editing, A.K.Y., J.O., J.E.C., N.I.N.-T., E.O., I.K.Y., A.A.K.-K., G.A., I.A.-B. and D.A.P.; funding acquisition, A.K.Y., N.I.N.-T., E.O., I.K.Y., A.A.K.-K., G.A., I.A.-B. and D.A.P. All authors have read and agreed to the published version of the manuscript.

Funding

This review work received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. WHO. World Malaria Report. 2023. Available online: https://www.who.int/publications/i/item/9789240086173 (accessed on 19 July 2024).
  2. Tetteh-Quarcoo, P.B.; Dayie, N.T.; Adutwum-Ofosu, K.K.; Ahenkorah, J.; Afutu, E.; Amponsah, S.K.; Abdul-Rahman, M.; Kretchy, J.-P.; Ocloo, J.Y.; Nii-Trebi, N.I. Unravelling the perspectives of day and night traders in selected markets within a sub-saharan african city with a malaria knowledge, attitude and practice survey. Int. J. Environ. Res. Public Health 2021, 18, 3468. [Google Scholar] [CrossRef]
  3. Zheng, Z.; Cheng, Z. Advances in molecular diagnosis of malaria. Adv. Clin. Chem. 2017, 80, 155–192. [Google Scholar]
  4. malERA Consultative Group on Diagnoses and Diagnostics. A research agenda for malaria eradication: Diagnoses and diagnostics. PLoS Med. 2011, 8, e1000396. [Google Scholar]
  5. Yalley, A.K.; Ahiatrogah, S.; Kafintu-Kwashie, A.A.; Amegatcher, G.; Prah, D.; Botwe, A.K.; Adusei-Poku, M.A.; Obodai, E.; Nii-Trebi, N.I. A systematic review on suitability of molecular techniques for diagnosis and research into infectious diseases of concern in resource-limited settings. Curr. Issues Mol. Biol. 2022, 44, 4367–4385. [Google Scholar] [CrossRef] [PubMed]
  6. WHO. Global Malaria Program. 2024. Available online: https://www.who.int/teams/global-malaria-programme/case-management/diagnosis/microscopy (accessed on 10 June 2024).
  7. Krampa, F.D.; Aniweh, Y.; Awandare, G.A.; Kanyong, P. Recent progress in the development of diagnostic tests for malaria. Diagnostics 2017, 7, 54. [Google Scholar] [CrossRef] [PubMed]
  8. Singh, K.; Bharti, P.K.; Devi, N.C.; Ahmed, N.; Sharma, A. Plasmodium malariae Detected by Microscopy in the International Bordering Area of Mizoram, a Northeastern State of India. Diagnostics 2022, 12, 2015. [Google Scholar] [CrossRef]
  9. Edwards, H. Tales from the bench: Laboratory diagnosis of malaria. Trop. Dr. 2011, 41, 106–107. [Google Scholar] [CrossRef] [PubMed]
  10. Worldbank. World Bank Country and Lending Groups. 2024. Available online: https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups (accessed on 13 May 2024).
  11. Azikiwe, C.C.; Ifezulike, C.; Siminialayi, I.; Amazu, L.U.; Enye, J.; Nwakwunite, O. A comparative laboratory diagnosis of malaria: Microscopy versus rapid diagnostic test kits. Asian Pac. J. Trop. Biomed. 2012, 2, 307–310. [Google Scholar] [CrossRef] [PubMed]
  12. Iqbal, J.; Hira, P.R.; Al-Ali, F.; Khalid, N.; Sher, A. Modified Giemsa staining for rapid diagnosis of malaria infection. Med. Princ. Pract. 2003, 12, 156–159. [Google Scholar] [CrossRef]
  13. Nadeem, M.F.; Khattak, A.A.; Yaqoob, A.; Awan, U.A.; Zeeshan, N. Assessment of Microscopic detection of Malaria with Nested Polymerase Chain Reaction in War-torn Federally Administered Tribal Areas of Pakistan. Acta Parasitol. 2021, 66, 1186–1192. [Google Scholar] [CrossRef]
  14. Awosolu, O.B.; Yahaya, Z.S.; Farah Haziqah, M.T. Efficacy of Plasmodium falciparum histidine-rich protein 2 (Pfhrp 2) rapid diagnostic test (RDT) and microscopy in the detection of falciparum malaria among symptomatic patients in Akure, Nigeria. Trop. Biomed. 2022, 39, 144–149. [Google Scholar] [CrossRef] [PubMed]
  15. Badiane, A.; Thwing, J.; Williamson, J.; Rogier, E.; Diallo, M.A.; Ndiaye, D. Sensitivity and specificity for malaria classification of febrile persons by rapid diagnostic test, microscopy, parasite DNA, histidine-rich protein 2, and IgG: Dakar, Senegal 2015. Int. J. Infect. Dis. 2022, 121, 92–97. [Google Scholar] [CrossRef]
  16. Fontecha, G.; Escobar, D.; Ortiz, B.; Pinto, A.; Serrano, D.; Valdivia, H.O. Field Evaluation of a Hemozoin-Based Malaria Diagnostic Device in Puerto Lempira, Honduras. Diagnostics 2022, 12, 1206. [Google Scholar] [CrossRef] [PubMed]
  17. Ahmad, A.; Soni, P.; Kumar, L.; Singh, M.P.; Verma, A.K.; Sharma, A.; Das, A.; Bharti, P.K. Comparison of polymerase chain reaction, microscopy, and rapid diagnostic test in malaria detection in a high burden state (Odisha) of India. Pathog. Glob. Health 2021, 115, 267–272. [Google Scholar] [CrossRef] [PubMed]
  18. Ugah, U.I.; Alo, M.N.; Owolabi, J.O.; Okata-Nwali, O.D.G.; Ekejindu, I.M.; Ibeh, N.; Elom, M.O. Evaluation of the utility value of three diagnostic methods in the detection of malaria parasites in endemic area. Malar. J. 2017, 16, 189. [Google Scholar] [CrossRef] [PubMed]
  19. Karimi, A.; Navidbakhsh, M.; Haghi, A.M.; Faghihi, S. A morphology-based method for the diagnosis of red blood cells parasitized by Plasmodium malariae and Plasmodium ovale. Scand. J. Infect. Dis. 2014, 46, 368–375. [Google Scholar] [CrossRef] [PubMed]
  20. Mohanty, S.; Sharma, R.; Deb, M. Usefulness of a centrifuged buffy coat smear examination for diagnosis of malaria. Indian J. Med. Microbiol. 2015, 33, 63–67. [Google Scholar] [CrossRef] [PubMed]
  21. Echeverry, D.F.; Deason, N.A.; Davidson, J.; Makuru, V.; Xiao, H.; Niedbalski, J.; Kern, M.; Russell, T.L.; Burkot, T.R.; Collins, F.H.; et al. Human malaria diagnosis using a single-step direct-PCR based on the Plasmodium cytochrome oxidase III gene. Malar. J. 2016, 15, 128. [Google Scholar] [CrossRef]
  22. Schneider, R.; Lamien-Meda, A.; Auer, H.; Wiedermann-Schmidt, U.; Chiodini, P.L.; Walochnik, J. Validation of a novel FRET real-time PCR assay for simultaneous quantitative detection and discrimination of human Plasmodium parasites. PLoS ONE 2021, 16, e0252887. [Google Scholar] [CrossRef] [PubMed]
  23. Ranjan, P.; Ghoshal, U. Utility of nested polymerase chain reaction over the microscopy and immuno-chromatographic test in the detection of Plasmodium species and their clinical spectrum. Parasitol. Res. 2016, 115, 3375–3385. [Google Scholar] [CrossRef] [PubMed]
  24. Freitas, D.R.C.d.; Gomes, L.T.; Fontes, C.J.F.; Tauil, P.L.; Pang, L.W.; Duarte, E.C. Sensitivity of nested-PCR for Plasmodium detection in pooled whole blood samples and its usefulness to blood donor screening in endemic areas. Transfus. Apher. Sci. 2014, 50, 242–246. [Google Scholar] [CrossRef] [PubMed]
  25. Li, P.; Zhao, Z.; Wang, Y.; Xing, H.; Parker, D.M.; Yang, Z.; Baum, E.; Li, W.; Sattabongkot, J.; Sirichaisinthop, J.; et al. Nested PCR detection of malaria directly using blood filter paper samples from epidemiological surveys. Malar. J. 2014, 13, 175. [Google Scholar] [CrossRef]
  26. Pomari, E.; Silva, R.; Moro, L.; Marca, G.L.; Perandin, F.; Verra, F.; Bisoffi, Z.; Piubelli, C. Droplet digital PCR for the detection of Plasmodium falciparum DNA in whole blood and serum: A comparative analysis with other molecular methods. Pathogens 2020, 9, 478. [Google Scholar] [CrossRef] [PubMed]
  27. Srisutham, S.; Saralamba, N.; Malleret, B.; Rénia, L.; Dondorp, A.M.; Imwong, M. Four human Plasmodium species quantification using droplet digital PCR. PLoS ONE 2017, 12, e0175771. [Google Scholar] [CrossRef] [PubMed]
  28. Xu, W.; Morris, U.; Aydin-Schmidt, B.; Msellem, M.I.; Shakely, D.; Petzold, M.; Björkman, A.; Mårtensson, A. SYBR green real-time PCR-RFLP assay targeting the Plasmodium cytochrome B gene—A highly sensitive molecular tool for malaria parasite detection and species determination. PLoS ONE 2015, 10, e0120210. [Google Scholar] [CrossRef] [PubMed]
  29. Gómez-Luque, A.; Parejo, J.C.; Clavijo-Chamorro, M.Z.; López-Espuela, F.; Munyaruguru, F.; Lorenzo, S.B.; Monroy, I.; Gómez-Nieto, L.C. Method for malaria diagnosis based on extractions of samples using non-invasive techniques: An opportunity for the nursing clinical practice. Int. J. Environ. Res. Public Health 2020, 17, 5551. [Google Scholar] [CrossRef]
  30. Chua, K.H.; Lee, P.C.; Chai, H.C. Development of insulated isothermal PCR for rapid on-site malaria detection. Malar. J. 2016, 15, 134. [Google Scholar] [CrossRef]
  31. Kim, J.; Lim, D.H.; Mihn, D.-C.; Nam, J.; Jang, W.S.; Lim, C.S. Clinical usefulness of labchip real-time PCR using lab-on-a-chip technology for diagnosing malaria. Korean J. Parasitol. 2021, 59, 77. [Google Scholar] [CrossRef]
  32. Barbosa, L.R.; da Silva, E.L.; de Almeida, A.C.; Salazar, Y.E.; Siqueira, A.M.; Alecrim, M.d.G.C.; Vieira, J.L.F.; Bassat, Q.; de Lacerda, M.V.; Monteiro, W.M. An Ultra-Sensitive Technique: Using Pv-mtCOX1 qPCR to Detect Early Recurrences of Plasmodium vivax in Patients in the Brazilian Amazon. Pathogens 2020, 10, 19. [Google Scholar] [CrossRef]
  33. Obaldía, N.; Barahona, I.; Lasso, J.; Avila, M.; Quijada, M.; Nuñez, M.; Marti, M. Comparison of PvLAP5 and Pvs25 qRT-PCR assays for the detection of Plasmodium vivax gametocytes in field samples preserved at ambient temperature from remote malaria endemic regions of Panama. PLoS Neglected Trop. Dis. 2022, 16, e0010327. [Google Scholar] [CrossRef] [PubMed]
  34. Bouzayene, A.; Zaffaroullah, R.; Bailly, J.; Ciceron, L.; Sarrasin, V.; Cojean, S.; Argy, N.; Houzé, S.; Joste, V.; Angoulvant, A.; et al. Evaluation of two commercial kits and two laboratory-developed qPCR assays compared to LAMP for molecular diagnosis of malaria. Malar. J. 2022, 21, 204. [Google Scholar] [CrossRef] [PubMed]
  35. Sazed, S.A.; Kibria, M.G.; Alam, M.S. An optimized real-time qpcr method for the effective detection of human malaria infections. Diagnostics 2021, 11, 736. [Google Scholar] [CrossRef]
  36. Grignard, L.; Nolder, D.; Sepúlveda, N.; Berhane, A.; Mihreteab, S.; Kaaya, R.; Phelan, J.; Moser, K.; van Schalkwyk, D.A.; Campino, S.; et al. A novel multiplex qPCR assay for detection of Plasmodium falciparum with histidine-rich protein 2 and 3 (pfhrp2 and pfhrp3) deletions in polyclonal infections. EBioMedicine 2020, 55, 102757. [Google Scholar] [CrossRef]
  37. Aimeé, K.K.; Lengu, T.B.; Nsibu, C.N.; Umesumbu, S.E.; Ngoyi, D.M.; Chen, T. Molecular detection and species identification of Plasmodium spp. infection in adults in the Democratic Republic of Congo: A populationbased study. PLoS ONE 2020, 15, e0242713. [Google Scholar] [CrossRef]
  38. Canier, L.; Khim, N.; Kim, S.; Eam, R.; Khean, C.; Loch, K.; Ken, M.; Pannus, P.; Bosman, P.; Stassijns, J.; et al. Malaria PCR detection in Cambodian low-transmission settings: Dried blood spots versus venous blood samples. Am. Soc. Trop. Med. Hyg. 2015, 92, 573–577. [Google Scholar] [CrossRef]
  39. Phuong, M.; Lau, R.; Ralevski, F.; Boggild, A.K. Sequence-based optimization of a quantitative real-time PCR assay for detection of Plasmodium ovale and Plasmodium malariae. J. Clin. Microbiol. 2014, 52, 1068–1073. [Google Scholar] [CrossRef]
  40. Leski, T.A.; Taitt, C.R.; Swaray, A.G.; Bangura, U.; Reynolds, N.D.; Holtz, A.; Yasuda, C.; Lahai, J.; Lamin, J.M.; Baio, V.; et al. Use of real-time multiplex PCR, malaria rapid diagnostic test and microscopy to investigate the prevalence of Plasmodium species among febrile hospital patients in Sierra Leone. Malar. J. 2020, 19, 84. [Google Scholar] [CrossRef] [PubMed]
  41. Murillo, E.; Muskus, C.; Agudelo, L.A.; Vélez, I.D.; Ruiz-Lopez, F. A new high-resolution melting analysis for the detection and identification of Plasmodium in human and Anopheles vectors of malaria. Sci. Rep. 2019, 9, 1674. [Google Scholar] [CrossRef]
  42. Amaral, L.C.; Robortella, D.R.; Guimarães, L.F.F.; Limongi, J.E.; Fontes, C.J.F.; Pereira, D.B.; De Brito, C.F.A.; Kano, F.S.; De Sousa, T.N.; Carvalho, L.H. Ribosomal and non-ribosomal PCR targets for the detection of low-density and mixed malaria infections. Malar. J. 2019, 18, 154. [Google Scholar] [CrossRef]
  43. Frickmann, H.; Wegner, C.; Ruben, S.; Behrens, C.; Kollenda, H.; Hinz, R.; Rojak, S.; Schwarz, N.G.; Hagen, R.M.; Tannich, E. Evaluation of the multiplex real-time PCR assays RealStar malaria S&T PCR kit 1.0 and FTD malaria differentiation for the differentiation of Plasmodium species in clinical samples. Travel Med. Infect. Dis. 2019, 31, 101442. [Google Scholar] [CrossRef] [PubMed]
  44. Lee, P.C.; Chong, E.T.J.; Anderios, F.; Lim, Y.A.L.; Chew, C.H.; Chua, K.H. Molecular detection of human Plasmodium species in Sabah using PlasmoNex™ multiplex PCR and hydrolysis probes real-time PCR. Malar. J. 2015, 14, 28. [Google Scholar] [CrossRef]
  45. Hayashida, K.; Kajino, K.; Simukoko, H.; Simuunza, M.; Ndebe, J.; Chota, A.; Namangala, B.; Sugimoto, C. Direct detection of falciparum and non-falciparum malaria DNA from a drop of blood with high sensitivity by the dried-LAMP system. Parasites Vectors 2017, 10, 26. [Google Scholar] [CrossRef]
  46. Colbert, A.J.; Co, K.; Lima-Cooper, G.; Lee, D.H.; Clayton, K.N.; Wereley, S.T.; John, C.C.; Linnes, J.C.; Kinzer-Ursem, T.L. Towards the use of a smartphone imaging-based tool for point-of-care detection of asymptomatic low-density malaria parasitaemia. Malar. J. 2021, 20, 380. [Google Scholar] [CrossRef] [PubMed]
  47. Imai, K.; Tarumoto, N.; Misawa, K.; Runtuwene, L.R.; Sakai, J.; Hayashida, K.; Eshita, Y.; Maeda, R.; Tuda, J.; Murakami, T.; et al. A novel diagnostic method for malaria using loop-mediated isothermal amplification (LAMP) and MinION™ nanopore sequencer. BMC Infect. Dis. 2017, 17, 621. [Google Scholar] [CrossRef] [PubMed]
  48. Azam, M.; Upmanyu, K.; Gupta, R.; Sruthy, K.S.; Matlani, M.; Savargaonkar, D.; Singh, R. Development of two-tube loop-mediated isothermal amplification assay for differential diagnosis of Plasmodium falciparum and Plasmodium vivax and its comparison with loopamp™ malaria. Diagnostics 2021, 11, 1689. [Google Scholar] [CrossRef] [PubMed]
  49. Jang, W.S.; Lim, D.H.; Choe, Y.; Jee, H.; Moon, K.C.; Kim, C.; Choi, M.; Park, I.S.; Lim, C.S. Development of a multiplex loop-mediated isothermal amplification assay for diagnosis of Plasmodium spp., Plasmodium falciparum and Plasmodium vivax. Diagnostics 2021, 11, 1950. [Google Scholar] [CrossRef]
  50. Mohon, A.N.; Getie, S.; Jahan, N.; Alam, M.S.; Pillai, D.R. Ultrasensitive loop mediated isothermal amplification (US-LAMP) to detect malaria for elimination. Malar. J. 2019, 18, 350. [Google Scholar] [CrossRef]
  51. Viana, G.M.R.; Silva-Flannery, L.; Barbosa, D.R.L.; Lucchi, N.; do Valle, S.C.N.; Farias, S.; Barbalho, N.; Marchesini, P.; Rossi, J.C.N.; Udhayakumar, V.; et al. Field evaluation of a real time loop-mediated isothermal amplification assay (RealAmp) for malaria diagnosis in Cruzeiro do Sul, Acre, Brazil. PLoS ONE 2018, 13, e0200492. [Google Scholar] [CrossRef] [PubMed]
  52. Cuadros, J.; Martin Ramírez, A.; González, I.J.; Ding, X.C.; Perez Tanoira, R.; Rojo-Marcos, G.; Gómez-Herruz, P.; Rubio, J.M. LAMP kit for diagnosis of non-falciparum malaria in Plasmodium ovale infected patients. Malar. J. 2017, 16, 20. [Google Scholar] [CrossRef] [PubMed]
  53. Lau, Y.L.; Lai, M.Y.; Fong, M.Y.; Jelip, J.; Mahmud, R. Loop-mediated isothermal amplification assay for identification of five human Plasmodium species in Malaysia. Am. J. Trop. Med. Hyg. 2016, 94, 336–339. [Google Scholar] [CrossRef]
  54. Patel, J.C.; Lucchi, N.W.; Srivastava, P.; Lin, J.T.; Sug-Aram, R.; Aruncharus, S.; Bharti, P.K.; Shukla, M.M.; Congpuong, K.; Satimai, W.; et al. Field evaluation of a real-time fluorescence loop-mediated isothermal amplification assay, realamp, for the diagnosis of Malaria in Thailand and India. J. Infect. Dis. 2014, 210, 1180–1187. [Google Scholar] [CrossRef] [PubMed]
  55. Moonga, L.C.; Hayashida, K.; Kawai, N.; Nakao, R.; Sugimoto, C.; Namangala, B.; Yamagishi, J. Development of a multiplex loop-mediated isothermal amplification (LAMP) method for simultaneous detection of spotted fever group rickettsiae and malaria parasites by dipstick DNA chromatography. Diagnostics 2020, 10, 897. [Google Scholar] [CrossRef]
  56. Aydin-Schmidt, B.; Morris, U.; Ding, X.C.; Jovel, I.; Msellem, M.I.; Bergman, D.; Islam, A.; Ali, A.S.; Polley, S.; Gonzalez, I.J.; et al. Field evaluation of a high throughput loop mediated isothermal amplification test for the detection of asymptomatic Plasmodium infections in Zanzibar. PLoS ONE 2017, 12, e0169037. [Google Scholar] [CrossRef] [PubMed]
  57. Lucchi, N.W.; Gaye, M.; Diallo, M.A.; Goldman, I.F.; Ljolje, D.; Deme, A.B.; Badiane, A.; Ndiaye, Y.D.; Barnwell, J.W.; Udhayakumar, V.; et al. Evaluation of the Illumigene Malaria LAMP: A Robust Molecular Diagnostic Tool for Malaria Parasites. Sci. Rep. 2016, 6, 36808. [Google Scholar] [CrossRef] [PubMed]
  58. Sharma, S.; Kumar, S.; Ahmed, M.Z.; Bhardwaj, N.; Singh, J.; Kumari, S.; Savargaonkar, D.; Anvikar, A.R.; Das, J. Advanced multiplex loop mediated isothermal amplification (mLAMP) combined with lateral flow detection (LFD) for rapid detection of two prevalent malaria species in india and melting curve analysis. Diagnostics 2022, 12, 32. [Google Scholar] [CrossRef]
  59. Aninagyei, E.; Boakye, A.A.; Tettey, C.O.; Ntiri, K.A.; Ofori, S.O.; Tetteh, C.D.; Aphour, T.T.; Rufai, T. Utilization of 18s ribosomal RNA LAMP for detecting Plasmodium falciparum in microscopy and rapid diagnostic test negative patients. PLoS ONE 2022, 17, e0275052. [Google Scholar] [CrossRef] [PubMed]
  60. Lai, M.Y.; Ooi, C.H.; Jaimin, J.J.; Lau, Y.L. Evaluation of WarmStart colorimetric loop-mediated isothermal amplification assay for diagnosis of Malaria. Am. J. Trop. Med. Hyg. 2020, 102, 1370–1372. [Google Scholar] [CrossRef]
  61. Barazorda, K.A.; Salas, C.J.; Braga, G.; Ricopa, L.; Ampuero, J.S.; Siles, C.; Sanchez, J.F.; Montano, S.; Lizewski, S.E.; Joya, C.A.; et al. Validation study of Boil & Spin Malachite Green Loop Mediated Isothermal Amplification (B&S MG-LAMP) versus microscopy for malaria detection in the Peruvian Amazon. PLoS ONE 2021, 16, e0258722. [Google Scholar] [CrossRef]
  62. Vincent, J.P.; Komaki-Yasuda, K.; Iwagami, M.; Kawai, S.; Kano, S. Combination of PURE-DNA extraction and LAMP-DNA amplification methods for accurate malaria diagnosis on dried blood spots 11 Medical and Health Sciences 1108 Medical Microbiology. Malar. J. 2018, 17, 373. [Google Scholar] [CrossRef]
  63. Cordray, M.S.; Richards-Kortum, R.R. A paper and plastic device for the combined isothermal amplification and lateral flow detection of Plasmodium DNA. Malar. J. 2015, 14, 472. [Google Scholar] [CrossRef] [PubMed]
  64. Aninagyei, E.; Abraham, J.; Atiiga, P.; Antwi, S.D.; Bamfo, S.; Acheampong, D.O. Evaluating the potential of using urine and saliva specimens for malaria diagnosis in suspected patients in Ghana. Malar. J. 2020, 19, 349. [Google Scholar] [CrossRef]
  65. Turnbull, L.B.; Ayodo, G.; Knight, V.; John, C.C.; McHenry, M.S.; Tran, T.M. Evaluation of an ultrasensitive HRP2–based rapid diagnostic test for detection of asymptomatic Plasmodium falciparum parasitaemia among children in western Kenya. Malar. J. 2022, 21, 337. [Google Scholar] [CrossRef]
  66. Briand, V.; Cottrell, G.; Tuike Ndam, N.; Martiáñez-Vendrell, X.; Vianou, B.; Mama, A.; Kouwaye, B.; Houzé, S.; Bailly, J.; Gbaguidi, E.; et al. Prevalence and clinical impact of malaria infections detected with a highly sensitive HRP2 rapid diagnostic test in Beninese pregnant women. Malar. J. 2020, 19, 188. [Google Scholar] [CrossRef]
  67. Wardhani, P.; Butarbutar, T.V.; Adiatmaja, C.O.; Betaubun, A.M.; Hamidah, N.; Aryati. Performance comparison of two malaria rapid diagnostic test with real time polymerase chain reaction and gold standard of microscopy detection method. Infect. Dis. Rep. 2020, 12, 8731. [Google Scholar] [CrossRef] [PubMed]
  68. Naeem, M.A.; Ahmed, S.; Khan, S.A. Detection of asymptomatic carriers of malaria in Kohat district of Pakistan. Malar. J. 2018, 17, 44. [Google Scholar] [CrossRef] [PubMed]
  69. Maltha, J.; Guiraud, I.; Lompo, P.; Kaboré, B.; Gillet, P.; Van Geet, C.; Tinto, H.; Jacobs, J. Accuracy of PfHRP2 versus Pf-pLDH antigen detection by malaria rapid diagnostic tests in hospitalized children in a seasonal hyperendemic malaria transmission area in Burkina Faso. Malar. J. 2014, 13, 20. [Google Scholar] [CrossRef] [PubMed]
  70. Fedele, P.L.; Wheeler, M.; Lemoh, C.; Chunilal, S. Immunochromatographic antigen testing alone is sufficient to identify asymptomatic refugees at risk of severe malaria presenting to a single health service in Victoria. Pathology 2014, 46, 551–554. [Google Scholar] [CrossRef] [PubMed]
  71. Kim, J.; Cao, X.E.; Finkelstein, J.L.; Cárdenas, W.B.; Erickson, D.; Mehta, S. A two-colour multiplexed lateral flow immunoassay system to differentially detect human malaria species on a single test line. Malar. J. 2019, 18, 313. [Google Scholar] [CrossRef] [PubMed]
  72. Abubakar, A.; Ajuji, M.; Yahya, I.U. Deepfmd: Computational analysis for malaria detection in blood-smear images using deep-learning features. Appl. Syst. Innov. 2021, 4, 82. [Google Scholar] [CrossRef]
  73. Kassim, Y.M.; Palaniappan, K.; Yang, F.; Poostchi, M.; Palaniappan, N.; Maude, R.J.; Antani, S.; Jaeger, S. Clustering-Based Dual Deep Learning Architecture for Detecting Red Blood Cells in Malaria Diagnostic Smears. IEEE J. Biomed. Health Inform. 2021, 25, 1735–1746. [Google Scholar] [CrossRef]
  74. Sriporn, K.; Tsai, C.F.; Tsai, C.E.; Wang, P. Analyzing malaria disease using effective deep learning approach. Diagnostics 2020, 10, 744. [Google Scholar] [CrossRef]
  75. Nakasi, R.; Mwebaze, E.; Zawedde, A. Mobile-aware deep learning algorithms for malaria parasites and white blood cells localization in thick blood smears. Algorithms 2021, 14, 17. [Google Scholar] [CrossRef]
  76. Yang, F.; Poostchi, M.; Yu, H.; Zhou, Z.; Silamut, K.; Yu, J.; Maude, R.J.; Jaeger, S.; Antani, S. Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears. IEEE J. Biomed. Health Inform. 2020, 24, 1427–1438. [Google Scholar] [CrossRef] [PubMed]
  77. Manescu, P.; Shaw, M.J.; Elmi, M.; Neary-Zajiczek, L.; Claveau, R.; Pawar, V.; Kokkinos, I.; Oyinloye, G.; Bendkowski, C.; Oladejo, O.A.; et al. Expert-level automated malaria diagnosis on routine blood films with deep neural networks. Am. J. Hematol. 2020, 95, 883–891. [Google Scholar] [CrossRef] [PubMed]
  78. Islam, M.R.; Nahiduzzaman, M.; Goni, M.O.F.; Sayeed, A.; Anower, M.S.; Ahsan, M.; Haider, J. Explainable Transformer-Based Deep Learning Model for the Detection of Malaria Parasites from Blood Cell Images. Sensors 2022, 22, 4358. [Google Scholar] [CrossRef]
  79. Abdurahman, F.; Fante, K.A.; Aliy, M. Malaria parasite detection in thick blood smear microscopic images using modified YOLOV3 and YOLOV4 models. BMC Bioinform. 2021, 22, 112. [Google Scholar] [CrossRef]
  80. Chibuta, S.; Acar, A.C. Real-time Malaria Parasite Screening in Thick Blood Smears for Low-Resource Setting. J. Digit. Imaging 2020, 33, 763–775. [Google Scholar] [CrossRef] [PubMed]
  81. Ashraf, S.; Khalid, A.; de Vos, A.L.; Feng, Y.; Rohrbach, P.; Hasan, T. Malaria Detection Accelerated: Combing a High-Throughput NanoZoomer Platform with a ParasiteMacro Algorithm. Pathogens 2022, 11, 1182. [Google Scholar] [CrossRef] [PubMed]
  82. Kongklad, G.; Chitaree, R.; Taechalertpaisarn, T.; Panvisavas, N.; Nuntawong, N. Discriminant Analysis PCA-LDA Assisted Surface-Enhanced Raman Spectroscopy for Direct Identification of Malaria-Infected Red Blood Cells. Methods Protoc. 2022, 5, 49. [Google Scholar] [CrossRef]
  83. Wang, W.; Dong, R.L.; Gu, D.; He, J.A.; Yi, P.; Kong, S.K.; Ho, H.P.; Loo, J.F.C.; Wang, W.; Wang, Q. Antibody-free rapid diagnosis of malaria in whole blood with surface-enhanced Raman Spectroscopy using Nanostructured Gold Substrate. Adv. Med. Sci. 2020, 65, 86–92. [Google Scholar] [CrossRef]
  84. Heraud, P.; Chatchawal, P.; Wongwattanakul, M.; Tippayawat, P.; Doerig, C.; Jearanaikoon, P.; Perez-Guaita, D.; Wood, B.R. Infrared spectroscopy coupled to cloud-based data management as a tool to diagnose malaria: A pilot study in a malaria-endemic country. Malar. J. 2019, 18, 348. [Google Scholar] [CrossRef] [PubMed]
  85. McBirney, S.E.; Chen, D.; Scholtz, A.; Ameri, H.; Armani, A.M. Rapid Diagnostic for Point-of-Care Malaria Screening. ACS Sens. 2018, 3, 1264–1270. [Google Scholar] [CrossRef] [PubMed]
  86. Ngo, H.T.; Gandra, N.; Fales, A.M.; Taylor, S.M.; Vo-Dinh, T. Sensitive DNA detection and SNP discrimination using ultrabright SERS nanorattles and magnetic beads for malaria diagnostics. Biosens. Bioelectron. 2016, 81, 8–14. [Google Scholar] [CrossRef] [PubMed]
  87. Yoon, J.; Jang, W.S.; Nam, J.; Mihn, D.C.; Lim, C.S. An automated microscopic Malaria parasite detection system using digital image analysis. Diagnostics 2021, 11, 527. [Google Scholar] [CrossRef] [PubMed]
  88. Kim, J.D.; Nam, K.M.; Park, C.Y.; Kim, Y.S.; Song, H.J. Automatic detection of malaria parasite in blood images using two parameters. Technol. Health Care 2015, 24, S33–S39. [Google Scholar] [CrossRef]
  89. Linder, N.; Turkki, R.; Walliander, M.; Mårtensson, A.; Diwan, V.; Rahtu, E.; Pietikäinen, M.; Lundin, M.; Lundin, J. A malaria diagnostic tool based on computer vision screening and visualization of Plasmodium falciparum candidate areas in digitized blood smears. PLoS ONE 2014, 9, e104855. [Google Scholar] [CrossRef] [PubMed]
  90. Post, A.; Kaboré, B.; Reuling, I.J.; Bognini, J.; Van Der Heijden, W.; Diallo, S.; Lompo, P.; Kam, B.; Herssens, N.; Lanke, K.; et al. The XN-30 hematology analyzer for rapid sensitive detection of malaria: A diagnostic accuracy study. BMC Med. 2019, 17, 103. [Google Scholar] [CrossRef]
  91. Dumas, C.; Bienvenu, A.L.; Girard, S.; Picot, S.; Debize, G.; Durand, B. Automated Plasmodium detection by the Sysmex XN hematology analyzer. J. Clin. Pathol. 2018, 71, 594–599. [Google Scholar] [CrossRef]
  92. Racsa, L.D.; Gander, R.M.; Southern, P.M.; McElvania TeKippe, E.; Doern, C.; Luu, H.S. Detection of intracellular parasites by use of the CellaVision DM96 analyzer during routine screening of peripheral blood smears. J. Clin. Microbiol. 2015, 53, 167–171. [Google Scholar] [CrossRef] [PubMed]
  93. Pillay, E.; Khodaiji, S.; Bezuidenhout, B.C.; Litshie, M.; Coetzer, T.L. Evaluation of automated malaria diagnosis using the Sysmex XN-30 analyser in a clinical setting. Malar. J. 2019, 18, 15. [Google Scholar] [CrossRef] [PubMed]
  94. Hashimoto, M.; Yokota, K.; Kajimoto, K.; Matsumoto, M.; Tatsumi, A.; Yamamoto, K.; Hyodo, T.; Matsushita, K.; Minakawa, N.; Mita, T.; et al. Quantitative detection of Plasmodium falciparum using, luna-fl, a fluorescent cell counter. Microorganisms 2020, 8, 1356. [Google Scholar] [CrossRef] [PubMed]
  95. Costa, M.S.; Baptista, V.; Ferreira, G.M.; Lima, D.; Minas, G.; Veiga, M.I.; Catarino, S.O. Multilayer thin-film optical filters for reflectance-based malaria diagnostics. Micromachines 2021, 12, 890. [Google Scholar] [CrossRef]
  96. Orbán, Á.; Longley, R.J.; Sripoorote, P.; Maneechai, N.; Nguitragool, W.; Butykai, Á.; Mueller, I.; Sattabongkot, J.; Karl, S.; Kézsmárki, I. Sensitive detection of Plasmodium vivax malaria by the rotating-crystal magneto-optical method in Thailand. Sci. Rep. 2021, 11, 18547. [Google Scholar] [CrossRef] [PubMed]
  97. Pukáncsik, M.; Molnár, P.; Orbán, Á.; Butykai, Á.; Marton, L.; Kézsmárki, I.; Vértessy, B.G.; Kamil, M.; Abraham, A.; Aly, A.S.I. Highly sensitive and rapid characterization of the development of synchronized blood stage malaria parasites via magneto-optical hemozoin quantification. Biomolecules 2019, 9, 579. [Google Scholar] [CrossRef] [PubMed]
  98. Orbán, Á.; Butykai, Á.; Molnár, A.; Pröhle, Z.; Fülöp, G.; Zelles, T.; Forsyth, W.; Hill, D.; Müller, I.; Schofield, L.; et al. Evaluation of a novel magneto-optical method for the detection of malaria parasites. PLoS ONE 2014, 9, e96981. [Google Scholar] [CrossRef]
  99. Lukianova-Hleb, E.Y.; Campbell, K.M.; Constantinou, P.E.; Braam, J.; Olson, J.S.; Ware, R.E.; Sullivan, D.J.; Lapotko, D.O. Hemozoin-generated vapor nanobubbles for transdermal reagent- and needle-free detection of malaria. Proc. Natl. Acad. Sci. USA 2014, 111, 900–905. [Google Scholar] [CrossRef]
  100. Gandarilla, A.M.D.; Glória, J.C.; Barcelay, Y.R.; Mariuba, L.A.M.; Brito, W.R. Electrochemical immunosensor for detection of Plasmodium vivax lactate dehydrogenase. Mem. Inst. Oswaldo Cruz 2022, 117, e220085. [Google Scholar] [CrossRef] [PubMed]
  101. de la Serna, E.; Arias-Alpízar, K.; Borgheti-Cardoso, L.N.; Sanchez-Cano, A.; Sulleiro, E.; Zarzuela, F.; Bosch-Nicolau, P.; Salvador, F.; Molina, I.; Ramírez, M.; et al. Detection of Plasmodium falciparum malaria in 1 h using a simplified enzyme-linked immunosorbent assay. Anal. Chim. Acta 2021, 1152, 338254. [Google Scholar] [CrossRef] [PubMed]
  102. Hemben, A.; Ashley, J.; Tothill, I.E. Development of an Immunosensor for Pf HRP 2 as a biomarker for malaria detection. Biosensors 2017, 7, 28. [Google Scholar] [CrossRef]
  103. Jang, I.K.; Jiménez, A.; Rashid, A.; Barney, R.; Golden, A.; Ding, X.C.; Domingo, G.J.; Mayor, A. Comparison of two malaria multiplex immunoassays that enable quantification of malaria antigens. Malar. J. 2022, 21, 176. [Google Scholar] [CrossRef]
  104. Singh, N.K.; Jain, P.; Das, S.; Goswami, P. Dye coupled aptamer-captured enzyme catalyzed reaction for detection of pan malaria and p. Falciparum species in laboratory settings and instrument-free paper-based platform. Anal. Chem. 2019, 91, 4213–4221. [Google Scholar] [CrossRef] [PubMed]
  105. Lin, H.; Zhao, S.; Liu, Y.; Shao, L.; Ye, Y.; Jiang, N.; Yang, K. Rapid Visual Detection of Plasmodium Using Recombinase-Aided Amplification With Lateral Flow Dipstick Assay. Front. Cell. Infect. Microbiol. 2022, 12, 922146. [Google Scholar] [CrossRef] [PubMed]
  106. Yang, D.; Subramanian, G.; Duan, J.; Gao, S.; Bai, L.; Chandramohanadas, R.; Ai, Y. A portable image-based cytometer for rapid malaria detection and quantification. PLoS ONE 2017, 12, e0179161. [Google Scholar] [CrossRef]
  107. Liu, Q.; Nam, J.; Kim, S.; Lim, C.T.; Park, M.K.; Shin, Y. Two-stage sample-to-answer system based on nucleic acid amplification approach for detection of malaria parasites. Biosens. Bioelectron. 2016, 82, 1–8. [Google Scholar] [CrossRef]
  108. Shah, J.; Mark, O.; Weltman, H.; Barcelo, N.; Lo, W.; Wronska, D.; Kakkilaya, S.; Rao, A.; Bhat, S.T.; Sinha, R.; et al. Fluorescence In Situ hybridization (FISH) assays for diagnosing malaria in endemic areas. PLoS ONE 2015, 10, e0136726. [Google Scholar] [CrossRef] [PubMed]
  109. Shah, J.; Poruri, A.; Mark, O.; Khadilka, U.; Mohring, F.; Moon, R.W.; Ramasamy, R. A dual colour fluorescence in situ hybridization (FISH) assay for identifying the zoonotic malaria parasite Plasmodium knowlesi with a potential application for the specific diagnosis of knowlesi malaria in peripheral-level laboratories of Southeast Asia. Parasites Vectors 2017, 10, 342. [Google Scholar] [CrossRef]
  110. Peng, W.K.; Kong, T.F.; Ng, C.S.; Chen, L.; Huang, Y.; Bhagat, A.A.S.; Nguyen, N.-T.; Preiser, P.R.; Han, J. Micromagnetic resonance relaxometry for rapid label-free malaria diagnosis. Nat. Med. 2014, 20, 1069–1073. [Google Scholar] [CrossRef]
  111. Thamarath, S.S.; Xiong, A.; Lin, P.-H.; Preiser, P.R.; Han, J. Enhancing the sensitivity of micro magnetic resonance relaxometry detection of low parasitemia Plasmodium falciparum in human blood. Sci. Rep. 2019, 9, 2555. [Google Scholar] [CrossRef]
  112. Fook Kong, T.; Ye, W.; Peng, W.K.; Wei Hou, H.; Marcos; Preiser, P.R.; Nguyen, N.-T.; Han, J. Enhancing malaria diagnosis through microfluidic cell enrichment and magnetic resonance relaxometry detection. Sci. Rep. 2015, 5, 11425. [Google Scholar] [CrossRef]
  113. Tomescu, O.A.; Mattanovich, D.; Thallinger, G.G. Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data. BMC Syst. Biol. 2014, 8, S4. [Google Scholar] [CrossRef]
  114. Awasthi, G.; Tyagi, S.; Kumar, V.; Patel, S.K.; Rojh, D.; Sakrappanavar, V.; Kochar, S.K.; Talukdar, A.; Samanta, B.; Das, A. A proteogenomic analysis of haptoglobin in malaria. PROTEOMICS–Clin. Appl. 2018, 12, 1700077. [Google Scholar] [CrossRef]
  115. Lindner, S.E.; Swearingen, K.E.; Shears, M.J.; Walker, M.P.; Vrana, E.N.; Hart, K.J.; Minns, A.M.; Sinnis, P.; Moritz, R.L.; Kappe, S.H. Transcriptomics and proteomics reveal two waves of translational repression during the maturation of malaria parasite sporozoites. Nat. Commun. 2019, 10, 4964. [Google Scholar] [CrossRef] [PubMed]
  116. Gardinassi, L.G.; Arévalo-Herrera, M.; Herrera, S.; Cordy, R.J.; Tran, V.; Smith, M.R.; Johnson, M.S.; Chacko, B.; Liu, K.H.; Darley-Usmar, V.M. Integrative metabolomics and transcriptomics signatures of clinical tolerance to Plasmodium vivax reveal activation of innate cell immunity and T cell signaling. Redox Biol. 2018, 17, 158–170. [Google Scholar] [CrossRef]
  117. Commonwealth. The Commonwealth Malaria Report. 2022. Available online: https://reliefweb.int/report/world/commonwealth-malaria-report-2022 (accessed on 15 June 2024).
  118. Yan, S.L.R.; Wakasuqui, F.; Wrenger, C. Point-of-care tests for malaria: Speeding up the diagnostics at the bedside and challenges in malaria cases detection. Diagn. Microbiol. Infect. Dis. 2020, 98, 115122. [Google Scholar]
  119. Veiga, M.I.; Peng, W.K. Rapid phenotyping towards personalized malaria medicine. Malar. J. 2020, 19, 68. [Google Scholar] [CrossRef] [PubMed]
  120. Su, X.-Z.; Zhang, C.; Joy, D.A. Host-malaria parasite interactions and impacts on mutual evolution. Front. Cell. Infect. Microbiol. 2020, 10, 587933. [Google Scholar] [CrossRef]
  121. Laishram, D.D.; Sutton, P.L.; Nanda, N.; Sharma, V.L.; Sobti, R.C.; Carlton, J.M.; Joshi, H. The complexities of malaria disease manifestations with a focus on asymptomatic malaria. Malar. J. 2012, 11, 29. [Google Scholar] [CrossRef] [PubMed]
  122. Leski, T.A.; Taitt, C.R.; Colston, S.M.; Bangura, U.; Holtz, A.; Yasuda, C.Y.; Reynolds, N.D.; Lahai, J.; Lamin, J.M.; Baio, V. Prevalence of malaria resistance-associated mutations in Plasmodium falciparum circulating in 2017–2018, Bo, Sierra Leone. Front. Microbiol. 2022, 13, 1059695. [Google Scholar] [CrossRef] [PubMed]
  123. Bull, P.C.; Berriman, M.; Kyes, S.; Quail, M.A.; Hall, N.; Kortok, M.M.; Marsh, K.; Newbold, C.I. Plasmodium falciparum variant surface antigen expression patterns during malaria. PLoS Pathog. 2005, 1, e26. [Google Scholar] [CrossRef] [PubMed]
  124. Aggarwal, S.; Peng, W.K.; Srivastava, S. Multi-omics advancements towards Plasmodium vivax malaria diagnosis. Diagnostics 2021, 11, 2222. [Google Scholar] [CrossRef] [PubMed]
Tropicalmed 09 00190 g001
Figure 1. A PRISMA flow diagram showing the method of article selection.
Figure 1. A PRISMA flow diagram showing the method of article selection.
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Tropicalmed 09 00190 g002
Figure 2. Frequencies of malaria detection/diagnosis methods in reviewed publications.
Figure 2. Frequencies of malaria detection/diagnosis methods in reviewed publications.
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Table 1. Countries classified by World Bank as low or lower-middle-income economies in 2024 [1,10]. The table lists all resource-limited countries divided into low (top portion) and lower-middle (bottom portion) income countries, with special emphasis placed on the 11 countries (right portion) that together bear 70% of the global malaria burden.
Table 1. Countries classified by World Bank as low or lower-middle-income economies in 2024 [1,10]. The table lists all resource-limited countries divided into low (top portion) and lower-middle (bottom portion) income countries, with special emphasis placed on the 11 countries (right portion) that together bear 70% of the global malaria burden.
LOW AND LOWER-MIDDLE INCOME COUNTRIES
70% GLOBAL MALARIA BURDEN
LOW-INCOME COUNTRIESAfghanistanBurundiCentral African RepublicChadEritreaEthiopiaGambiaBurkina FasoCongo, Dem. Rep
Guinea-BissauKorea, Dem. People’s RepLiberiaMadagascarMalawiRwandaSierra LeoneMaliMozambique
SomaliaSouth SudanSudanSyrian Arab RepublicTogoYemen, Rep NigerUganda
LOWER-MIDDLE INCOME COUNTRIESAngolaAlgeriaBangladeshBeninBhutanBoliviaCabo VerdeCameroonGhana
CambodiaComorosCongo, Rep.Côte d’Ivoire DjiboutiEgypt, Arab Rep.EswatiniIndiaNigeria
GuineaHaitiHondurasJordanIran, Islamic RepKenyaKiribatiTanzania
Kyrgyz RepublicLao PDRLebanonLesotho Mauritania Micronesia, Fed. Sts. Mongolia
MoroccoMyanmarNepal Nicaragua PakistanPapua New Guinea Philippines
Samoa São Tomé and Principe SenegalSolomon IslandsSri LankaTajikistanTimor-Leste
TunisiaUkraineUzbekistanVanuatuVietnamZambiaZimbabwe
Table 2. Traditional methods used for malaria detection.
Table 2. Traditional methods used for malaria detection.
Traditional MethodsSpecimen UsedSummary of ProcedureInvasive/Non-InvasiveAdvantagesDisadvantagesRefer-ences
Thin film microscopyBloodThin blood smears are prepared and stained using Giemsa stain. Thin smears are examined with a 100× oil immersion objective.InvasiveReliable in the identification of four human plasmodium species and their various stagesLimited by quality of blood smears as well as availability of skilled microscopists.
Lack of sensitivity where non-falciparum or mixed infections exist.		[8,13,14,15,16,17,18]
Thick film microscopyBloodThick blood smears are prepared and stained using Giemsa stain. Thin smears are examined with a 100× oil immersion objective.InvasiveReliable in the detection of four human plasmodium speciesLimited by quality of blood smears as well as availability of skilled microscopists.[8,13,14,15,16,17,18]
Morphology-based diagnosisBloodOptical images from Giemsa-stained infected blood are measured using Olysia and Scanning Probe Image Processor software based on morphology of red blood cells.InvasiveFaster prediction of malaria casesExpertise needed[19]
Centrifuged buffy coat smear examination (CBCS)BloodCentrifugation of buffy coat is done prior to Giemsa staining and microscopic examinationInvasiveSpecificity is similar to conventional method but sensitivity a bit better than conventional methodLimited by availability of skilled microscopists[20]
Table 3. Modern (PCR/LAMP-based) methods used for malaria detection and evidence of use in developed countries.
Table 3. Modern (PCR/LAMP-based) methods used for malaria detection and evidence of use in developed countries.
Modern MethodsSpecimen UsedDescriptionInvasive/Non-InvasivePoint of Care/Molecular/OtherAdvantagesDisadvantagesDeveloped CountriesReferences
Direct conventional PCRBloodWith plasmodium cytochrome oxidase III gene (COX-III) as target, direct conventional PCR is conducted on bloodspot samples. Results are visualized on a gel.InvasiveMolecularHigh Sensitivity; faster than nested; does not require DNA isolationRequires much expertise and expensiveUSA[21]
Nested Polymerase Chain Reaction (PCR)BloodUsing different primer pairs to run 2 sequential amplification reactions. Plasmodium genomic DNA extracted from dried blood spotsInvasiveMolecularHigh sensitivity and specificityTime consuming, expensive, requires much expertiseThailand, USA, Brazil, United Kingdom, Austria[13,16,18,21,22,23,24,25]
Droplet Digital PCR (ddPCR)Blood, SerumDNA extracted from blood and serum samples are analyzed using the ddPCR method, which is based on water–oil emulsion droplet technologyInvasiveMolecularHigh sensitivity using blood samplesLow sensitivity using serum samples; expensiveItaly,
Thailand		[26,27]
Photo- Induced Electron transfer PCR (PET-PCR)Blood Total DNA is extracted from dried blood spots and PCR performed using photo-induced electron transfer fluorogenic primersInvasiveMolecularHigh sen-sitivity for parasite identification and characterization.Requires much expertise and is expensiveUSA[15]
Fluoresen-ce reson-ance energy transfer (FRET) real time PCRBloodReal-time PCR utilizing FRET whereby fluorophores are brought in close proximity after hybridization is performed on DNA extracted from lyophilized blood samples targeting the 18S rRNA geneInvasive MolecularHigh sensit-ivity, and
allows for simultaneous quantitative and species-specific detection		This specific protocol could not differentiate between P. vivax and P. knowlesi; expensiveUnited Kingdom, Austria[22]
SYBR Green Real-Time PCR-RFLP AssayBloodReal-time PCR using sybr green dye that binds to all double-stranded DNA followed by restriction fragment polymorphism to differentiate speciesInvasiveMolecularHigh sensitivityMeltcurve required in PCR since Sybr green alone can be non-specific; expensiveSweden[28]
Hair qPCRHead hairsHairs without roots are taken from patients and qPCR assay conductedNon-invasivemolecularRequires no special trans-port/storage conditions for samplesSensitivity lower than when blood samples are usedSpain[29]
Insulated Isothermal PCR (iiPCR)BloodPCR is performed in a portable device using an assay based on the Rayleigh–Bénard convection methodInvasiveMolecular/point of carePortable, easy and fast operation; direct interpretationNot as sensitive as qPCRMalaysia[30]
Lab Chip Real Time PCR (LRP)BloodDNA is extracted from collected blood samples and a portable LRP device is used to detect malarial parasites based on lab-on-chip technologyInvasiveMolecular/point of careHigh sensitivity and specificity. Fast and cost effectiveRisk of false negatives higher than traditional real-time PCRKorea[31]
Pv-mt Cox PCRBloodDNA is extracted from collected blood samples and qPCR with mitochondrial gene target is carried outInvasiveMolecularMore sensitive in the detection of P. vivaxExpensiveBrazil[32]
PvLAP5 and Pvs25qRT-PCR assaysBloodExtracted RNA is subjected to quantitative reverse transcription PCRInvasiveMolecularSuitable assay for the determination of human transmission reservoirExpensivePanama[33]
Other Quantita-tive PCR (qPCR)BloodReal-time PCR performed using primers targeting different regions and SYBR green or probe-based technology on DNA extracted from whole bloodInvasiveMolecularHigh sensitivity and rapidExtreme caution needed to prevent contamination; expensiveFrance, Canada, USA
Columbia
Germany, Brazil, China, Malaysia		[34,35,36,37,38,39,40,41,42,43,44]
Dry LAMP system (CZC-LAMP)BloodBlood samples are analyzed directly without extraction using the assay made up of dried reagentsInvasivePoint of care/molecularHigh sensitivity and specificity; no need for prior extractionNot widely available [45]
Particle Diffusometry (PD)-LAMPBloodPD, which senses images, is combined with LAMP on a smartphone-enabled device to detect low levels of parasitemiaInvasivePoint of care/molecular Sensitivitities
higher than RDTs and similar to qPCR		Sensitivity slightly lower than nested PCRUSA[46]
LAMP and MinION™ nanopore sequencerBloodPrimers targeting the 18S–rRNA gene of all five human Plasmodium species are generated and samples subjected to LAMP. Min-ION™ nanopore sequencer is used on amplicons to identify Plasmodium spp.InvasiveMolecularHighly sensitive, and simpleExpensiveJapan[47]
Other Loop-mediated isothermal amplification (LAMP), BloodExtracted DNA is subjected to loop-mediated isothermal amplification with a variety of detection methodsInvasivePoint of care/molecularSimple, low cost; can be used in resource-limited settings and point-of-care settingsSome cannot quantify par-asite density; some are insensitive towards low parasitemia and mixed infectionsFrance, Korea, Thailand
Italy, Brazil
Spain, Mala-ysia, Japan, Peru, USA		[26,34,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63]
Table 4. Modern (non-PCR/non-LAMP-based) methods used for malaria detection and evidence of use in developed countries.
Table 4. Modern (non-PCR/non-LAMP-based) methods used for malaria detection and evidence of use in developed countries.
Modern MethodsSpecimen UsedDescriptionInvasive/Non-InvasivePoint of Care/Molecular/OtherAdvantagesDisadvantagesDeveloped CountriesReferences
Malaria SD Bioline RDT kitUrine, Saliva, BloodUsing immuno-chromatography to detect PfhRP2 and PLDH following manufacturer’s instructionsNon-invasive/InvasivePoint of careEffective for non-invasive detection of malaria; low costLow sensitivity [64]
Other (RDTs)BloodImmunochromatography/
according to manufacturer’s instructions		Invasive Point of careSuitable for point of care in hard-to-access areas; low costLow sensit-ivity for some kits; poor identification of non-falciparum infections for some brandsIndonesia
Australia,
USA		[14,15,17,18,65,66,67,68,69,70,71]
Computeri-zed/digital deep mach-ine learnin-g approach BloodMachine learning models are used to detect malaria parasites in blood smears. Some can be integrated into smartphone detection appsInvasive OtherAccurate/
reliable		For some, results are affected by quality of smearsUSA, Taiwan, China, Turkey[72,73,74,75,76,77,78,79,80,81]
Spectros-copyBloodBlood samples are analyzed using spectroscopyInvasiveOtherHighly effective for identifying infected cellOnly qualitative results obtainedThailand,
China, Australia		[82,83,84]
Portable Optical Diagnostic System
(PODS) 		BloodWorks by differential optical spectroscopy. The change in optical power before and after a magnet is applied, is monitored in order to determine β-hematin concentration in whole bloodInvasivePoint of carePortable; low cost;
useful for low resource settings; high sensitivity		Not widely availableUSA[85]
Ultra bright SERS nanorattlesBloodDNA detection method that uses sandwich hybridization of magnetic bead, target sequence, and ultrabright SERS nanorattle are employedInvasiveMolecular/point of careSensitive; can be automated and added to portable devi-ces for POC diagnosis; can identify SNPs hence, discri-minate betw-een wild-type and mutant parasitesNot widely availableUSA[86]
Automated Microscopy/Digital AnalysisBlood Comprises a fluorescent dye staining or Giemsa staining and an automated microscopy platform and digital analysisInvasiveOtherRapid diagn-osis and par-asite density monitoring. High sens- itivity, linear-ity, and precisionNot widely availableKorea, Finland, Sweden[87,88,89]
Flow cytometryBloodParasites are detected and quantified in blood by use of analyzers utilizing flow cytometry technologyInvasiveMolecularRapid and high sensiti-vity; useful for mass screeningMay not be able to distinguish plasmodium speciesNetherlands, France, USA,
South Africa,
Japan		[90,91,92,93,94]
Thin-Film Optical FiltersBloodA thin film optical device is used based on optical reflectance spectrophotometry, for the parasite detection through haemozoin quantificationInvasivePoint of careHigh sensitivityHigh transmittance regions outside target wavelengthPortugal[95]
Rotating cr- ystal magn-eto optical detection (RMOD) methodBloodRMOD works by detection of the periodic modulation of light transmission. This is induced by hemozoin crystals which co-rotates with a rotating magnetic fieldInvasiveOtherHigher sensitivity and accuracy than light microscopySensitivity is poorer than PCR methodsThailand,
Hungary		[96,97,98]
Hemozin-Based Malaria diagnostic device (GazelleTM)Blood Using magneto-optical technology, the device detects hemozoin produced by PlasmodiumInvasiveOtherSensitivities comparable to light micr-oscopy; faster than micros-copy; portab-le; can run on battery powerUnable to distinguish between species [16]
Hemozoin-generated vapor nanobubblesBlood vessel (transdermal)Hemozoin generates a transient vapor nanobubble around hemozoin in response to a short and safe laser pulse. The acoustic signals of these nanobubbles that are malaria specific enable detectionNon-invasivePoint of careNon-invasive;
rapid		Not widely availableUSA[99]
Electroche-mical immunosensorBloodEgg yolk IgY antibodies against Plasmodium vivax lactate dehydrogenase antigen are immobilized on a gold electrode surface followed by differential pulse voltammetry and contact angle measurements are made.InvasivePoint of careHigh Sensitivity for malaria caused by P. vivaxOnly malaria caused by P. vivax can be detectedBrazil[100]
Simplified ELISA)/PfHRP 2 ELISABlood Modified ElISA was performed on blood samples.InvasivePoint of careHigh sensitivity, portable and low costNot widely availableSpain
UK
Denmark		[101,102]
Multiple-xed ELISA based assayBloodMultiplexed ELISA-based (either planar-based array or magnetic bead-based platforms) technologies are used for malaria detectionInvasiveMolecularCan detect malaria spe-cies mutants; have high throughput potentialNot widely availableUSA[103]
Dye-Cou-pledApt-amer-Capt-ured Enzy-me-Cataly-zed assayBloodAptamer- and enzyme-based method is used to detect malaria infection in blood. Method can be used on instrument or instrument free platformInvasive Molecular/point of careLow cost; useful for resource-limited and point-of-care settings.Not widely available [104]
Recombinase-Aided Amplificat-ion with Lateral Flow Dip-stick Assay
(RAA-LFD)		BloodA combination of recombinase-aided amplification lasting for 15 min at 37 degrees and lateral flow dipstick is used to detect plasmodium species in blood InvasiveMolecular/point of careHighly sensitive, specific, low cost, convenient for on-site screening
and low resource settings.		Not widely available China[105]
Portable image-based CytometerBloodP. falciparum-infected blood cells are identified and counted from Giemsa-stained smears using the image based portable cytometer.InvasiveOtherSimple to operate;
low cost		Not widely availableSingapore[106]
Two-stage sample-to-answer sy-stem based on nucleic acid ampl-ification approachBloodIt combines the dimethyl adipimidate (DMA)/thin film sample processing (DTS) technique and the Mach–Zehnder interferometer isothermal solid-phase DNA amplification (MZI-IDA)
technique to detect infection in blood		Invasive MolecularHigh sensitivity, rapidNot widely availableSingapore,
Korea		[107]
Fluorescen-ce In Situ Hybridization (FISH) AssaysBloodDetects and localizes specific malaria nucleic acid sequences by hybridizing with complementary sequences that are labeled with fluorescent probesInvasive MolecularHigh sensitivity Skilled expertise required. USA[108,109]
NMR-based hemozoin detectionBloodDetection is based on the ability to recognize the paramagnetic susceptibility of malaria hemozoin crystalsInvasiveMolecular/point of careHigh sensitivity and rapidNot widely availableAustralia, Singapore, USA[110,111,112]
Multi-omicsVariesIntegrating data from different omic methodsInvasive/non-invasiveOtherComprehen-sive underst-anding of the infectionRequires skilled experitiseAustria
USA
Columbia		[113,114,115,116]
Table 5. Evidence of use of modern methods of malaria detection in low and lower-middle-income countries.
Table 5. Evidence of use of modern methods of malaria detection in low and lower-middle-income countries.
Modern MethodResource-Limited CountriesReferences
Malaria rapid test kit (SD Bioline RDT kit) using urine and saliva samplesGhana[64]
Other rapid diagnostic testsNigeria, Senegal, Kenya, Benin, Pakistan, Burkina Faso[14,15,17,18,65,66,68,69]
Nested polymerase chain reaction (PCR)Pakistan, Nigeria, Myanmar, Honduras, India[13,16,18,23,25]
Hair qPCRRwanda[29]
Other quantitative polymerase chain reaction (qPCR)Bangladesh, Eritrea, Tanzania
D.R. Congo, Sierra Leone, Cambodia		[35,36,37,38,40]
Dry LAMP system (CZC-LAMPZambia[45]
Other loop-mediated isothermal amplification (LAMP), India, Tanzania, Senegal, Ghana[48,56,57,58,59]
Computerized/digital deep machine learning approachNigeria, Uganda, Bangladesh, Ethiopia, Zambia, [59,75,77,78,79,80]
The rotating-crystal magneto-optical detection (RMOD) methodPapua New Guinea[96]
Hemozin-based malaria diagnostic device (GazelleTM)Honduras[16]
Flow cytometryBurkina Faso, India[90,93]
Dye-coupled aptamer-captured enzyme-catalyzed assayIndia[104]
Multi-omicsIndia[114]
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Yalley, A.K.; Ocran, J.; Cobbinah, J.E.; Obodai, E.; Yankson, I.K.; Kafintu-Kwashie, A.A.; Amegatcher, G.; Anim-Baidoo, I.; Nii-Trebi, N.I.; Prah, D.A. Advances in Malaria Diagnostic Methods in Resource-Limited Settings: A Systematic Review. Trop. Med. Infect. Dis. 2024, 9, 190. https://doi.org/10.3390/tropicalmed9090190

AMA Style

Yalley AK, Ocran J, Cobbinah JE, Obodai E, Yankson IK, Kafintu-Kwashie AA, Amegatcher G, Anim-Baidoo I, Nii-Trebi NI, Prah DA. Advances in Malaria Diagnostic Methods in Resource-Limited Settings: A Systematic Review. Tropical Medicine and Infectious Disease. 2024; 9(9):190. https://doi.org/10.3390/tropicalmed9090190

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Yalley, Akua K., Joyous Ocran, Jacob E. Cobbinah, Evangeline Obodai, Isaac K. Yankson, Anna A. Kafintu-Kwashie, Gloria Amegatcher, Isaac Anim-Baidoo, Nicholas I. Nii-Trebi, and Diana A. Prah. 2024. "Advances in Malaria Diagnostic Methods in Resource-Limited Settings: A Systematic Review" Tropical Medicine and Infectious Disease 9, no. 9: 190. https://doi.org/10.3390/tropicalmed9090190

APA Style

Yalley, A. K., Ocran, J., Cobbinah, J. E., Obodai, E., Yankson, I. K., Kafintu-Kwashie, A. A., Amegatcher, G., Anim-Baidoo, I., Nii-Trebi, N. I., & Prah, D. A. (2024). Advances in Malaria Diagnostic Methods in Resource-Limited Settings: A Systematic Review. Tropical Medicine and Infectious Disease, 9(9), 190. https://doi.org/10.3390/tropicalmed9090190

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