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

Maxim ArmstrongDepartment of Bioengineering, University of California, Berkeley, Berkeley, California;
Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California;

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Andrew R. HarrisDepartment of Bioengineering, University of California, Berkeley, Berkeley, California;
Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, Ontario, Canada;

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Michael V. D’AmbrosioDepartment of Bioengineering, University of California, Berkeley, Berkeley, California;

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Jean T. CoulibalyUnité de Formation et de Recherche Biosciences, Université Félix Houphouët-Boigny, Abidjan, Côte d’Ivoire;
Department of Medical Parasitology and Infection Biology, Swiss Tropical and Public Health Institute, Basel, Switzerland;

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Samuel Essien-BaidooDepartment of Medical Laboratory Science, University of Cape Coast, Cape Coast, Ghana;

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Richard K. D. EphraimDepartment of Medical Laboratory Science, University of Cape Coast, Cape Coast, Ghana;

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Jason R. AndrewsDepartment of Medicine, Stanford University, Stanford, California;

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Isaac I. BogochDepartment of Medicine, University of Toronto, Toronto, Ontario, Canada;

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Daniel A. FletcherDepartment of Bioengineering, University of California, Berkeley, Berkeley, California;
Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, University of California, Berkeley, Berkeley, California;
Chan Zuckerberg Biohub, San Francisco, California

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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.

Author Notes

Address correspondence to Daniel A. Fletcher, 608B Stanley Hall MC 1762, Berkeley, CA 94720. E-mail: fletch@berkeley.edu

Financial support: This work was supported by a generous gift from Mitsuru and Lucinda Igarashi, the Blum Center for Developing Economies at UC Berkeley through a grant from USAID, and donors to the Health Tech CoLab (DAF), as well as funding from an MSH-UHN AMO Innovation Funding grant and Ontario New Frontiers Grant (NFRFE/2020/00922).

Authors’ addresses: Maxim Armstrong, Michael V. D’Ambrosio, and Daniel A. Fletcher, University of California Berkeley, Berkeley, CA, E-mails: maxarmstrong@berkeley.edu, mdambrosio@berkeley.edu, and fletch@berkeley.edu. Andrew R. Harris and Isaac I. Bogoch, Carleteon University, Ottawa, ON, Canada, E-mails: andrewharris3@cunet.carleton.ca and isaac.bogoch@uhn.ca. Jean T. Coulibaly, Université Félix Houphouët-Boigny, Abidjan, Lagunes, Cote d’Ivoire, E-mail: jean.coulibaly@swisstph.ch. Samuel Essien-Baidoo, Richard K. D. Ephraim, University of Cape Coast, Cape Coast, Central, Ghana, E-mails: sessien-baidoo@ucc.edu.gh and rephraim@ucc.edu.gh. Jason R. Andrews, Stanford University, Stanford, CA, E-mail: jandr@stanford.edu.

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