Advancements and Challenges in Malaria Diagnostics

Malaria is caused by parasites of the genus Plasmodium spp. and it is transmitted to humans when infected female Anopheles mosquito bite or feed for blood meal. According to World Health Organization, an estimated 249 million malaria incidences were reported in 2022. Diagnostic methods are vital for dealing with the global malaria burden and declining malaria incidence. The diagnosis by microscopy is considered a gold standard; however, rapid diagnostic tests (RDTs) have become a primary diagnostic test in many malaria endemic areas. RDT have many advantages like fast preparation and diagnosis results, easy handling, low-cost diagnosis, species identification. But this most implemented method is also not free of disadvantages. The deletion of pfHRP2/3, low sensitivity with low parasite levels, cross-reactivity and prozone effect are certain disadvantages of RDTs. In addition to microscopy and RDTs molecular methods have also been developed. The Quantitative Buffy Coat (QBC) has fast preparation and diagnosis results with high specificity, however, the requirement of fluorescent microscope and expert personnel along with the low sensitivity under field conditions are the disadvantages. Another molecular technique such as Polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP) provides results with higher specificity and sensitivity but have drawbacks in terms of requirements of specialized instrumentation and difficult implementation in endemic areas. On the other hand the mass spectrometry based diagnostic have certain drawbacks like low sensitivity and requirement of specialized costly instruments and reagents. Another molecular method based on flow cytometry has advantages like quantification of infected erythrocytes and automated parasite level calculations. However, low sensitivity, specialized instrumentation and difficult implementation in endemic areas are the dragging forces behind its large scale implications in diagnosis of malaria. Recently malaria diagnosis based on artificial intelligence system such as Artificial intelligence based object detection system (AIDMAN), Automated AI-based Microscopy (Easy Go scan) and smart phone based application for malaria diagnosis (Malaria Screener & PVF-Net) have been developed which can be implemented in the fields once the high sensitivity and specificity is achieved. Thus, there is an urgent need of the development of malaria diagnostic tools which has minimal disadvantage and show high sensitivity and specificity on the one hand and low cost on the other hand. Recently the gene deletions events have created a vacuum which can be filled with more advanced RDT. Recently we have identified a T-cell immunomodulatory protein which is secreted in the blood of infected mice and can be detected by ELISA. The RDT implying the T-cell immunomodulatory protein of P. falciparum is being developed in our lab, which may have advantages over other RDTs.