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Data Science Methodologies for Environmental and Climate Surveillance and Monitoring from a One Health and Participatory Perspective
Applications:
January 19, 2026 to January 23, 2026
Offering Period:

February 2, 2026 to February 6, 2026

Target Audience

Post-Graduate students interested in the One Health approach, Data Science, and Participatory Approaches, with good comprehension in English

Course Information

General Objective: To introduce students to surveillance and monitoring methodologies in environmental, human, and animal health, grounded in the One Health approach and supported by data science and participatory research practices.

Educational / Learning Objectives:
1. To present the participatory environmental monitoring experience developed by the research team of the African Conservation Centre in Amboseli National Park, involving Maasai communities in Kenya.
2. To present experiences in environmental, animal, and human health surveillance and monitoring carried out in different international border areas in Kenya and Brazil, through the development of the MOSAIC Project (Multi-site Application of Open Science in the Creation of Healthy Environments Involving Local Communities).

Methodology: The course is divided into sessions lasting 3 to 4 hours, consisting of thematic presentations (lectures) followed by open discussions with the class. In addition to the course coordinators, invited researchers will present specific topics.

Justification: Climate change poses profound challenges to human, animal, and environmental health in the 21st century, with extreme events increasing in both frequency and intensity. Although climate change is a global phenomenon, its impacts are experienced locally, highlighting the need for territorially grounded and socially inclusive surveillance systems. The One Health approach has emerged as a promising framework to address these interconnected challenges; however, its effectiveness depends on meaningful engagement of local communities in participatory monitoring and decision-making processes.
This course responds to this need by presenting successful international experiences that combine scientific technologies—such as data science, satellite imagery, and geoprocessing—with social and participatory methodologies. The Amboseli National Park experience illustrates how scientific innovation and traditional ecological knowledge can be integrated to improve the predictability of extreme events and strengthen community resilience. For students enrolled in Graduate Programs in Tropical Medicine, Public Health, Environmental Studies, and related fields, the course offers an opportunity to engage with real-world applications of innovative methodologies that are highly relevant to socio-environmental and climate realities in different contexts (Brazil and Kenya), fostering the development of innovative solutions.

Assessment: Assessment will be based solely on verification of a minimum attendance of 75% of the classes.

Prerequisites: Enrolment in a Fiocruz (Brazil) postgraduate program and/or in postgraduate programs at institutions in countries participating in the MOSAIC Project (Kenya, Tanzania, France, Portugal, and Poland), and intermediate English certification.

Structure: The course is divided into five modules, with the final module conducted in the auditorium in a “Centro de Estudos” session.