Jillian Armstrong, MS (PhD Student)


GHES U.S. Fellow 2019-2020

FELLOWSHIP SITE: Epicentre and the University of Yaoundé, Cameroon

Project Title: Testing a novel device for the in vivo detection of malaria-infected red blood cells

Almost half of the world’s population is at risk for malaria, with 90 countries affected. The disease remains a leading cause of morbidity and mortality, with 219 million cases and 435,000 deaths reported in 2017, and 90% of cases affecting children under five years old in sub-Saharan Africa.  Of those individuals infected with P. falciparum, it is believed that the majority are asymptomatic, with the remaining displaying a spectrum of illness from uncomplicated malaria (fevers, chills, non-specific symptoms) to under 1% progressing to severe malaria, a form of the disease characterized by organ system failures and metabolic abnormalities. World-wide, the diagnosis of malaria is made by the current diagnostic “gold standard”, light microscopy, or rapid diagnostic tests. Both tests lack sufficient sensitivity to detect low levels of parasitemia, and require a blood specimen. Photoacoustic Flow Cytometry (PAFC) is a novel non-invasive diagnostic method that can detect hemozoin (Hz) in malaria-infected red blood cells (RBCs). In vitro and in vivo animal studies have demonstrated that this method is highly sensitive, offering a non-invasive, real-time alternative to the existing diagnostic landscape, is not limited by sample volume, and is theoretically able to detect extremely low parasitemia (0.0000001%), ~1000-fold better than current limits of detection. This work aims to assess the feasibility of using PAFC to detect Hz in malaria-infected RBCs. The enhanced sensitivity will offer significant insight into asymptomatic malaria reservoir and in vivo dynamics of infection over time and following treatment. Our proposed project will help provide the preliminary data needed to begin the implementation of PAFC for malaria detection in humans, potentially both for clinical use, as well for understanding of in vivo disease dynamics.