Hub: Cheikh Anta Diop University, Senegal

Title: AI and Hybrid modeling for Community-based early detection of zoonotic disease in the context of climate change in Senegal

Team Members

Sylvain Landry Faye
Principal Investigator

Daouda Ngom
Team Member

Ibrahima Dia
Team Member

Ibrahima SY
Team Member

Ibnou Ndiaye
Team Member

Ndiaye Dia
Team Member

Mouhamaadou Lamine
Team Member

Massamba Diouf
Team Member

Tidiane Ndoye
Team Member

Halima Diallo
Team Member

Vincent Duclos
Team Member

General Objectives

The general objective of this project is: To enhance the epidemiological surveillance system in Senegal by developing and testing a community-based, gender-sensitive early detection and warning systems for zoonotic diseases using AI, data science and a One Health approach.

Specific Objectives

1. To identify with communities and policy-makers the factors that influence infectious diseases in Senegal, particularly in relation to climate change and ecological upheaval.

2. To establish strong community-based surveillance systems for the early detection and reporting of zoonotic diseases in Senegal based on equitable partnership and community engagement.

3. To develop AI and data science applications based on local realities and contextual data that can rapidly detect, predict, and respond to zoonotic disease outbreaks in Senegal.

4. To ensure that the AI and data science applications are sensitive to local realities, including ecological, geographical, medical, economic, and sociocultural factors, to reduce the risk of exclusion and discrimination.

5. To evaluate the effectiveness of the AI and data science applications in improving the early detection and prevention of zoonotic diseases in Senegal.