# MEDSCAN: Mobile Enabled Diagnostics for Schistosomiasis Control Analytics

> **NIH NIH R01** · VANDERBILT UNIVERSITY · 2021 · $531,973

## Abstract

PROJECT SUMMARY
Schistosomiasis is endemic in 54 countries and infects nearly 240 million people worldwide per year. Sub-
Saharan Africa endures a disproportionate burden, accounting for over 90% of infections. In Kenya, the site of
our study, 17 million out of the nation’s 50 million citizens are at risk for schistosomiasis infection. Of the at-risk
population, school-aged children represent the primary risk group, and the many morbidities of infection are
amplified over a child’s lifespan.
After decades of mass drug administration, it is clear that more aggressive and targeted interventions are
necessary to move towards the elimination of schistosomiasis. Unfortunately, this recognition has not yet
resulted in the development of the tools that public health officials need to make this transition. To address this
unmet need, we propose the development of the MEDSCAN (mobile enabled diagnostics for schistosomiasis
control analytics) platform to improve schistosomiasis surveillance efforts. This software package builds off of
the successful history that we have had in the development of image-processing algorithms for diagnostic
purposes. MEDSCAN will consist of a mobile application that can analyze point-of-care diagnostic tests and a
web-based administrator dashboard for viewing real-time operational performance metrics and other advanced
analytics.
We have assembled an interdisciplinary consortium that consists of mobile health software and global
health expertise at Vanderbilt University, a world-leader in schistosomiasis diagnostics from Leiden University
Medical Center, and a successful history of neglected tropical disease program management and field
research at the Kenya Medical Research Institute. To meet our shared goals, our specific aims will: 1) evaluate
the cellular network in Western Kenya in preparation for mobile health research, and develop the mobile and
web platforms; 2) perform a usability analysis on the platform and make iterative refinements; 3) complete a
thorough laboratory evaluation of the MEDSCAN application and a single-site pilot systems check; 4) use the
MEDSCAN platform in a 10-month, observational surveillance study.
By transforming the already widely utilized point-of-care test into a “connected” diagnostic, MEDSCAN can
serve as the gateway to high-resolution surveillance that is necessary to shift efforts from control to elimination.

## Key facts

- **NIH application ID:** 10279946
- **Project number:** 1R01AI163472-01
- **Recipient organization:** VANDERBILT UNIVERSITY
- **Principal Investigator:** Thomas F Scherr
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $531,973
- **Award type:** 1
- **Project period:** 2021-07-09 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10279946

## Citation

> US National Institutes of Health, RePORTER application 10279946, MEDSCAN: Mobile Enabled Diagnostics for Schistosomiasis Control Analytics (1R01AI163472-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10279946. Licensed CC0.

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