# DIGITAL HEALTH SOLUTIONS FOR COVID-19: COVID-19 ONGOING MONITORING (COMMUNITY)

> **NIH NIH N01** · EVIDATION HEALTH, INC. · 2021 · $560,000

## Abstract

The goal of this proposal is to develop a COVID-19 detection algorithm based on self-report survey data and wearable sensor data. Data from 25K COVID-19 Experiences participants and 25K Large-scale Flu Surveillance (COVID-19 Questions added March 2020) will be used with an existing machine learning model to develop this new detection algorithm, which will be validated in a large-scale pilot population to identify individuals with undiagnosed COVID-19. Evidation will incorporate the model into an established web and multi-platform (Android, iOS) smartphone platform called Achieve which allows users to share person-generated health data (PGD) from their everyday lives. Data collected under this project will be deidentified and securely transmitted to an NIH data hub.

## Key facts

- **NIH application ID:** 10329864
- **Project number:** 75N91020C00034-P00002-9999-1
- **Recipient organization:** EVIDATION HEALTH, INC.
- **Principal Investigator:** LUCA FOSCHINI
- **Activity code:** N01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $560,000
- **Award type:** —
- **Project period:** 2020-09-14 → 2021-09-13

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10329864

## Citation

> US National Institutes of Health, RePORTER application 10329864, DIGITAL HEALTH SOLUTIONS FOR COVID-19: COVID-19 ONGOING MONITORING (COMMUNITY) (75N91020C00034-P00002-9999-1). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10329864. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*