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Home / Perfis / Ana Ceia-Hasse
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Ana Ceia-Hasse

Researcher

Grupo GHTM: GHTM former members

ProfileResearchTop 5 Publications

I am a biologist working in the areas of Ecology, Biogeography and Modelling. My main interests are in developing frameworks that integrate different models and data sources to better understand and predict biodiversity responses to environmental change and that also contribute to facilitate decision-making. I participated in several international and interdisciplinary teams in Portugal and abroad. My previous work has mainly focused on developing modelling frameworks to analyse and predict spatial and temporal phenomena (namely species distributions and population dynamics). I am also interested in analysing citizen science data and in integrating such data into predictive modelling. Recently I analysed biotic interactions to study ecosystem functioning and the impact of invasive species. I also developed user-friendly tools and methods for standardized quantitative impact assessments. I work with spatial modelling and geographic information systems and use several software and programming tools for spatial data analysis, specifically R and QGIS, C++ and Python.

I am working in project “WARDEN – An operational early WARning system for DENgue and other arboviral diseases in Madeira Island” at the IHMT – UNL (Institute of Hygiene and Tropical Medicine – NOVA University of Lisbon) and IGOT – UL (Institute of Geography and Spatial Planning- University of Lisbon). WARDEN will implement a system to predict the risk of arboviral diseases in the Madeira island. This includes collecting and iteratively harmonizing data on environmental and socio-economic variables, which will be integrated into models dealing with different components of arboviral epidemiology, including the probability of introduction of arboviruses from epidemic regions, habitat suitability for the transmitting species and the response of vector populations to observed and predicted weather conditions. I am developing statistical and machine learning based approaches for the spatiotemporal prediction of mosquito population dynamics and of disease risk.

  1. Ceia-Hasse A, Navarro LM, Borda-de-Água L, Pereira HM. (2018). Population persistence in landscapes fragmented by roads: Disentangling isolation, mortality, and the effect of dispersal. Ecological Modelling 375: 45-53.  https://doi.org/10.1016/j.ecolmodel.2018.01.0213
  2. Ceia-Hasse A, Borda-de-Água L, Pereira HM. (2018). PopIn – An R package for assessing the impact of linear infrastructures on populations.  https://github.com/anaceiahasse/PopIn
  3. Ceia-Hasse A, Borda-de-Água A, Grilo C, Pereira HM. (2017). Global exposure of carnivores to roads. Global Ecology and Biogeography 26(5): 592-600.  https://doi.org/10.1111/geb.125645 Featured in front cover ( https://doi.org/10.1111/geb.12597 )
  4. Tiago P, Ceia-Hasse A, Marques TA, Capinha C, Pereira HM. (2017). Spatial distribution of citizen science casuistic observations for different taxonomic groups. Scientific Reports 7(1): 1-9.  https://10.1038/s41598-017-13130-84
  5. Ceia-Hasse A, Sinervo B, Vicente L, Pereira HM. (2014). Integrating ecophysiological models into species distribution projections of European reptile range shifts in response to climate change. Ecography 37(7): 679-688.  https://doi.org/10.1111/j.1600-0587.2013.00600.x

About GHTM

GHTM is a R&D Center that brings together researchers from IHMT with a track record in Tropical Medicine and International/Global Health. It aims at strengthening Portugal's role as a leading partner in the development and implementation of a global health research agenda. Our evidence-based interventions contribute to the promotion of equity in health and to improve the health of populations.

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