Cecilia Siliansky de Andreazzi

Life Sciences

Biologist Cecilia Siliansky de Andreazzi graduated from the Federal University of Rio de Janeiro and earned a master’s degree in ecology. She holds a doctorate from the University of São Paulo, with a sandwich period at the Swiss Federal Institute of Aquatic Science and Technology. Her specialty is relating the microscopic world to the macro landscape. Fascinated by biodiversity, she studies changes in the landscape to find the factors that influence parasites to jump out and infect new hosts. She uses complex network tools and artificial intelligence to model likely scenarios. She is a researcher at the Oswaldo Cruz Foundation in Rio de Janeiro. Her love of nature extends beyond her work, and she enjoys hiking and exploring the wilderness in her spare time.

Open Calls

Science Call 3

Projects

Ecology of Disease Metacommunities: From dilutive effects to dilutive landscapes
Science / Life Sciences

Can we predict where the next pandemic will come from? Recent studies suggest a clear link between the emergence of infectious diseases and landscape structure changes caused by natural resource exploitation and biodiversity loss. Therefore, understanding the ecological and evolutionary mechanisms that regulate parasite-host dynamics and how they are affected by landscape changes is urgent. This study takes an interdisciplinary approach to the problem by integrating ecological, evolutionary, and epidemiological theory with artificial intelligence and complex network theory tools applied to real-world data. This will allow us to model and predict the dynamics of these interactions, identifying scenarios that favor parasite jumps to new hosts, including humans. We aim to contribute to understanding the mechanisms that have led to the increasing emergence of new diseases and epidemics in the Anthropocene.

Amount invested

1st phase: R$ 100,000.00
2nd phase: R$ 1,000,000.00 (R$ 700,000.00 + R$ 300,000.00 optional bonus for integrating and training people from underrepresented groups in science)
  • Topics
  • artificial inteligence
  • complex networks