Malaria absorption peaks acquired through the skin of patients with infrared light can detect patients with varying parasitemia

• Published in: PNAS nexus Vol. 1; no. 5; p. pgac272
• Main Authors: Garcia, Gabriela A, Kariyawasam, Tharanga N, Lord, Anton R, da Costa, Cristiano Fernandes, Chaves, Lana Bitencourt, Lima-Junior, Josué da Costa, Maciel-de-Freitas, Rafael, Sikulu-Lord, Maggy T
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.11.2022
• Subjects: Absorption; Algorithms; Asymptomatic; Biological, Health, and Medical Sciences; Blood diseases; Diagnosis; Ethics; Ethylenediaminetetraacetic acid; Health aspects; Human subjects; I.R. radiation; Infections; Infrared spectra; Infrared spectrometers; Infrared spectroscopy; Machine learning; Malaria; Microscopy; Near infrared radiation; Parasitemia; Parasites; Parasitic diseases; Plasmodium falciparum; Reagents; Science; Skin; Spectrum analysis; Surveillance; Vector-borne diseases; Brazil; Australia
• ISSN: 2752-6542; 2752-6542
• DOI: 10.1093/pnasnexus/pgac272

To eliminate malaria, scalable tools that are rapid, affordable, and can detect patients with low parasitemia are required. Non-invasive diagnostic tools that are rapid, reagent-free, and affordable would also provide a justifiable platform for testing malaria in asymptomatic patients. However, non-invasive surveillance techniques for malaria remain a diagnostic gap. Here, we show near-infrared Plasmodium absorption peaks acquired non-invasively through the skin using a miniaturized hand-held near-infrared spectrometer. Using spectra from the ear, these absorption peaks and machine learning techniques enabled non-invasive detection of malaria-infected human subjects with varying parasitemia levels in less than 10 s.