Malaria Diagnosis

Article Citation: Al-Awadhi, M. A. (2020, October 18). Malaria Diagnosis. Kuwaiti Journal of Medical Parasitology. https://q8jmp.com/malaria-diagnosis/

Malaria is a deadly parasitic infection caused predominantly by Plasmodium falciparum and Plasmodium vivax parasites. The parasite is transmitted from an infected female Anopheles mosquito to the human host during a blood meal. Therefore, the endemicity of malaria within a region depends largely on the presence of Anopheles mosquitos, stagnant bodies of freshwater (natural or man-made) where mosquitos lay eggs, and humans in the vicinity. Worldwide, malaria causes more than 400,000 deaths annually, the vast majority of which occur in tropical and sub-tropical African countries (WHO, 2020).

Malaria is suspected when a patient’s body temperature is higher than 37.5°C and is residing in or has a travel history to a malaria-endemic country. To diagnose malaria, the WHO (2018) recommends microscopy or malaria rapid diagnostic test (RDT) for all patients with suspected malaria before treatment is administered.

Light microscopy of Giemsa-stained thick and thin blood smears is the diagnostic standard for malaria and allows species-level identification of different Plasmodium spp., the parasite stage and the quantification of parasite density when monitoring the progress of treatment. Rapid diagnostic tests (RDTs) may be used at times when the services of expert microscopists are not available, as in rural health centers, or when an urgent test result is required (e.g. ports of entry, patient in critical condition). RDTs are commonly based on Plasmodium lactate dehydrogenase (pLDH) and P. falciparum histidine-rich protein 2 (PfHRP-2) antigen detection, which are useful due to their release into the peripheral blood by P. falciparum-infected erythrocytes (Desakorn et al., 1997). A previous study in the Cameroon has demonstrated that PfHRP-2 detection in the blood of pregnant women was superior to traditional microscopy, where about 20% of malaria-positive women at delivery have shown negative results in peripheral and intervillous space thick blood smears (Leke et al., 1999). However, the main drawback of RDTs is false-positivity due to antigen circulation in the blood after parasite elimination, which could persist for 7-60 days depending on the screened antigen and type of antimalarial therapy (Dalrymple et al., 2018; Iqbal et al., 2004). Moreover, recent studies have reported RDT misdiagnosis due to PfHRP-2 and PfHRP-3 gene deletions (parasite mutation) in highly endemic African countries such as Djibouti, Ghana and Uganda (Amoah et al., 2020; Bosco et al., 2020; Iriart et al., 2020).

Various molecular techniques have been developed to increase the sensitivity of malaria diagnosis which include polymerase chain reaction (PCR), nested PCR, multiplex PCR, quantitative (q)-PCR, capture and ligation probe (CLIP)-PCR, nucleic acid sequence-based amplification (NASBA), loop-mediated isothermal amplification (LAMP) and high throughput (Ht)-LAMP (Tedla, 2019). A study had recently demonstrated malachite green (MG)-LAMP as a useful tool, especially in resource-limited regions, producing less false-positives and -negatives than microscopy and RDTs (Gachugia et al., 2020). However, such techniques are usually complex to perform, require expensive instrumentation and reagents, or are more time-consuming than microscopy and RDTs. Nonetheless, molecular techniques remain important to investigate Plasmodium spp. genotypes, which are of particular importance in the parasite’s resistance mechanisms to antimalarial drugs and in monitoring the geographical distribution of drug resistant genotypes. Moreover, qPCR is more efficient in detecting and distinguishing mixed Plasmodium spp. infections than microscopy and RDTs (Wardhani et al., 2020).

Interestingly, a recent study had demonstrated fluorescent nucleic acid staining followed by flow cytometry as efficient tools in detecting Plasmodium-infected RBCs, having the capability to differentiate the parasite developmental stage in about 1 minute (Toya et al., 2020). Other studies are demonstrating new concepts which utilize machine learning (ML) and algorithms in the diagnosis of malaria and automation of blood film reporting (De Bruyne, 2020), in addition to the use of ML in predicting Plasmodium mitochondrial protein sequences for use as targets of anti-malarial drugs (Bian et al., 2020). However, cost-effectiveness remains an important issue, especially in low-income countries which suffer the highest burden of malaria-attributed morbidity and mortality. While RDTs remain the most feasible choice to diagnose malaria in highly affected countries, the continuous surveillance of ever-evolving Plasmodium genotypes and modification of RDT components accordingly are of high importance.

References

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