IDAIR Pathfinder

Privacy-preserving epidemiology App

“There is no one size that fits all. We must work country by country, region by region, community by community, to ensure the diversity of needs are addressed to support each reality.” – Amina J. Mohammed, Deputy Secretary-General, UN

Since 2020 and the COVID-19 pandemic, governments around the world have had to design, develop, and deploy disease prevention and control strategies at unprecedented scale and speed. While COVID has been (among other things) a wake-up call, it has also revealed many complexities in managing population health.

Real Time Epidemiology: IDAIR Pathfinder

Epidemiology and tracing tools are key to keeping populations safe in the face of contagious diseases. Yet the efficacy of these technology tools relies on a very human factor: trust in their security when it comes to personal data.

The challenge: Ensuring data security and community adoption of epidemiology tool

Ensuring that this security is both trustworthy and trusted requires different approaches depending on the population context and must be understood and adapted accordingly. In Sub-Saharan Africa, facing COVID and other epidemic outbreaks such as Ebola, successful implementation of epidemiological tools requires understanding of the entire context.

Pathfinder before pic V-P-ML-E-00524 IDAIR small.jpg — Managing infection outbreaks without the benefits of epidemiological clues is inefficient, resulting in unnecessary deaths

Our adapted solution: Notification App with AI to predict epidemics

The project aims to develop a digitally scalable notification solution with the long-term goal to support national health systems. Critical focuses are: data privacy, relevant regulation compliance, interoperability across borders, and for the development of epidemiological models. We will use real-time data integration and artificial intelligence (AI) to further predict pandemic spread.

We will develop:

A privacy-engineering toolset tailored to the needs of epidemiologists to enable the systematic design of digital real-time epidemiology tools respectful of human rights.
New computing architectures to support real-time epidemiology.
Secure radio protocols and low-cost devices that can implement emerging epidemiology policies in a decentralized manner at large scale.
Open implementation of all protocols to further increase the reach of low-cost hardware helping with accessibility in LMICs.