• info@vodan-totafrica.info

About VODAN Africa


VODAN Africa started as a platform to enable access to critical data needed from Africa to fight the novel COVID-19. The initiative was inspired by the experience from the Liberia Ebola Virus outbreak in 2014: early detection requires contact tracing. Inclusion of the most vulnerable is critical to the prevention and control effort, but this is also a major challenge.

These are relevant lessons from the Ebola crisis for the COVID-19 Pandemic. 

The Virus Outbreak Data Network (VODAN)-Africa is a collaboration of researchers and health practitioners across fifteen African countries to address this challenge.

The Virus Outbreak Data Network (VODAN)-Africa. It is focused on improving health data analysis, under the regulatory provisions of the country, and strengthening national capacities for health data analytics as well as the use of health data at the point of care. Data is fully owned by the country and does not leave the country. The focus of data analytics is on COVID-19. Data analytics is arranged based on the permission that is granted for access to the data in relation to a particular query. This follows governance frameworks in place in each country.

Research feeding into the VODAN Project started two years ago by a collaboration between KIU and Leiden University Medical Center of Leiden University in the Netherlands. Since that time, we have also started a collaboration with Stanford University, particularly the Centre for Expanded Data Annotation and Retrieval (CEDAR).

VODAN-Africa is a collaboration of universities in Uganda, Kenya, Tanzania, Ethiopia, Somalia, Nigeria, Liberia, and Tunisia. We are also including South Africa, Zambia, Burkina Faso, Sudan, and Ghana.

We are working with 83 health facilities, one of which is the JF Kennedy Hospital in Liberia, to get insights into the needs, and how the new technology of data-visiting can respond to such needs.

Our team asked this question: how can we develop an Afrocentric system that would ensure data ownership in residence, with data analytics available at the point in care and a smart system for data visiting - instead of moving the data? The data held in residence should be Findable, Accessible, Interoperable, and Reusable (FAIR).

This research program aims to generate continuous, real-time, high velocity clinical observational patient data with high veracity from resource-limited communities that have not been well represented in digital health data. The focus of this module is on how to include data from communities that are generally missing from the data that is currently being used to understand the determinants of health and the treatments of disease (e.g. of ethnicity, geography, socioeconomic status).

Important Links

Participating Countries

  • Ethiopia
  • Kenya
  • Liberia
  • Nigeria
  • Somalia
  • Tanzania
  • Tunisia
  • Uganda
  • Zimbabwe

Partner Institutions

  • Leiden University
  • Philips Foundation
  • Mekelle University 
  • FMO
  • Kampala International University
  • Addis Ababa University
  • Google.Org
  • Tilburg University
  • Stanford University
  • University de Sousse
  • Tangaza University
  • Data Science Nigeria
  • Cordaid
  • Great Zimbabwe University
  • Ibrahim Badamasi University Lapai
  • East African University
  • Kilimanjaro Christian Medical University
  • African Leadership University
  •  Olabisi Onabanjo University
  • Chinese Academy of Science
  • San Diego Center for SuperComputing