Point-of-Care Sample Preparation and Automated Quantitative Detection of Schistosoma haematobium Using Mobile Phone Microscopy

Maxim Armstrong; Andrew R Harris; Michael V D'Ambrosio; Jean T Coulibaly; Samuel Essien-Baidoo; Richard K D Ephraim; Jason R Andrews; Isaac I Bogoch; Daniel A Fletcher

doi:10.4269/ajtmh.21-1071

Point-of-Care Sample Preparation and Automated Quantitative Detection of Schistosoma haematobium Using Mobile Phone Microscopy

Am J Trop Med Hyg. 2022 Mar 28;106(5):1442-1449. doi: 10.4269/ajtmh.21-1071. Online ahead of print.

Authors

Maxim Armstrong^{1

2}, Andrew R Harris^{1

3}, Michael V D'Ambrosio¹, Jean T Coulibaly^{4

5}, Samuel Essien-Baidoo⁶, Richard K D Ephraim⁶, Jason R Andrews⁷, Isaac I Bogoch⁸, Daniel A Fletcher^{1

9

10}

Affiliations

¹ Department of Bioengineering, University of California, Berkeley, Berkeley, California.
² Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California.
³ Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, Ontario, Canada.
⁴ Unité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d'Ivoire.
⁵ Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Basel, Switzerland.
⁶ Department of Medical Laboratory Science, University of Cape Coast, Cape Coast, Ghana.
⁷ Department of Medicine, Stanford University, Stanford, California.
⁸ Department of Medicine, University of Toronto, Toronto, Ontario, Canada.
⁹ Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, Berkeley, California.
¹⁰ Chan Zuckerberg Biohub, San Francisco, California.

Abstract

Schistosoma haematobium continues to pose a significant public health burden despite ongoing global control efforts. One of several barriers to sustained control (and ultimately elimination) is the lack of access to highly sensitive diagnostic or screening tools that are inexpensive, rapid, and can be used at the point of sample collection. Here, we report an automated point-of-care diagnostic based on mobile phone microscopy that rapidly images and identifies S. haematobium eggs in urine samples. Parasite eggs are filtered from urine within a specialized, inexpensive cartridge that is then automatically imaged by the mobile phone microscope (the "SchistoScope"). Parasite eggs are captured at a constriction point in the tapered cartridge for easy imaging, and the automated quantification of eggs is obtained upon analysis of the images by an algorithm. We demonstrate S. haematobium egg detection with greater than 90% sensitivity and specificity using this device compared with the field gold standard of conventional filtration and microscopy. With simple sample preparation and image analysis on a mobile phone, the SchistoScope combines the diagnostic performance of conventional microscopy with the analytic performance of an expert technician. This portable device has the potential to provide rapid and quantitative diagnosis of S. haematobium to advance ongoing control efforts.