About EquiHealth

Through the power of data, research, and Natural Language Processing (NLP), we transform fragmented health information into actionable insights.

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Who we are

We are a health-focused NGO dedicated to applying advanced data analytics, artificial intelligence, and scientific research to some of the most pressing healthcare challenges of our time. By combining technology with deep domain expertise in health and life sciences, we translate complex data into insights that drive meaningful action.

What guides us

Our core values

1

Impact

We prioritize solutions that create real-world health improvements

2

Equity

We design with inclusivity and underserved populations at the center.

3

Integrity

We uphold the highest standards of research ethics and transparency.

4

Collaboration

We believe progress happens through partnerships.

5

Innovation

We continuously explore new methods and technologies.

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Our Vision

A world where data-informed insights and inclusive technologies enable better health decisions for individuals, communities, and institutions.

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Our Mission

To improve health outcomes and equity through the ethical use of data, NLP, and research-driven innovation.

How we work

Our Research Framework

EquiHealth Institute's work is organized around a three-layer multilingual public health analytics framework designed to strengthen disease surveillance, health communication, and equitable access to health information for linguistically diverse communities in the United States.

1

Layer 1

Multilingual Processing Core

We apply natural language processing and multilingual machine learning to convert unstructured, non-English public health information into usable structured data. This layer draws directly on our published research in multilingual language modeling, translation quality evaluation, and cross-lingual text classification, including AfroLM, AfriMTE, AfriCOMET, and MasakhaNEWS. It addresses a documented gap in U.S. public health surveillance infrastructure, where early outbreak signals arriving in non-English text are often missed because existing systems are built primarily for English-language structured data.

2

Layer 2

Analytics Layer

We apply machine learning and statistical modeling to publicly available public health data to support early detection of disease trends, outbreak forecasting, and situational awareness for public health decision-makers. This layer is designed to be compatible with federal disease forecasting initiatives including the CDC's Center for Forecasting and Outbreak Analytics and the Insight Net national modeling network.

3

Layer 3

Accessible Delivery Layer

We convert analytical outputs into clear, accessible formats for public health agencies, community health organizations, and the communities they serve — delivered in multiple languages. This layer ensures that the insights generated by our analytics work reach the populations who need them most, regardless of their primary language.

All methods and tools developed through this framework are released openly through peer-reviewed publications and public repositories, ensuring that the benefit extends beyond any single institution or employer to the broader public health research community.

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Awoyomi Oluwabusayo Olufunke - Founder

The organization was founded by a visionary researcher and technologist with a strong background in health research, data science, and applied artificial intelligence. Motivated by the growing gap between health data availability and its effective use, the founder established this NGO to bridge research, technology, and real world health impact.

With experience spanning academic research, applied data projects, and cross-sector collaboration, the founder is deeply committed to building systems that turn data into better health decisions especially in settings where resources are limited but needs are high.

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Omidiji Peter Busayo - Program Manager

Peter is a Program Manager who enjoys taking a rough idea and shaping it into something real. Over the years he has led projects that cut across design, engineering, and operations, and what ties them together is a simple habit: getting the right people talking to each other, keeping the plan honest, and making sure the work actually lands with the people it was meant for.

He started out in digital product development and user-centered design, and that background still shapes how he manages programs today. Before a project moves forward, he asks how it will feel to the person on the other end. That perspective has guided his work on platforms in technology, healthcare, travel, and digital services, and it is what he brings to EquiHealth's mission of making health information genuinely accessible.