Project funded at FCT call AI 4 COVID-19: SCOPE-Spatial Data Sciences for COVID-19 Pandemic

The project ‘SCOPE- Spatial Data Sciences for COVID-19 Pandemic’ is one of the 12 projects recommended for funding, out of 39 applications, at the FCT Call for IC&DT Projects “AI 4 COVID-19".

The project is lead by CERENA with the participation of CEG-IST, ITI Larsys and Instituto Nacional de Saúde Dr. Ricardo Jorge. The multidisciplinary team aim to answer the following five main questions:

- Where is the disease spreading to?

- How fast the disease is spreading?

- How can mobility data improve disease predictions in space?

- How to visualize maps of health variables and the associated uncertainty?

- What information can the high-resolution maps provide for faster and better decisions?

 

‘We strongly believe that SCOPE will be a functional prototype for the processing of data available in Public Administration, in order to address risk management during epidemic events’, says Maria João Pereira- project PI.

 

Spatial Data Sciences (SDS) can provide significant insights into explaining spatial patterns of infectious diseases, understanding and predicting spatio-temporal transmission dynamics, predicting and monitoring the impact of control interventions, which are driven by geographical factors, designing and evaluating optimal resources allocation strategies and cost-effectiveness analyses that incorporate a spatial component and analysing inequities in healthcare based on geography. SCOPE project aims at demonstrating that SDS can be successfully used to deliver a functional software prototype for spatial risk management during epidemic events delivering to health public administration new capabilities to prepare and respond in a short amount of time. This project will combine Machine Learning, high performance computing and information visualization (InfoViz) to manage big data.

SCOPE will produce daily updates of health indicators maps and the uncertainty associated to the spatial predictions, retrieving the history of the COVID-19 pandemic. The potential for understanding the spatial patterns, especially during the mitigation and endemic phases, is huge bringing insights on the spatial dispersion of the disease over time.

Furthermore, also based on the historical maps, functional data analysis will be used to build spatio-temporal models that in turn, will be explored and analysed by public health experts to bring meaning and utility to their use and to define a subset of health indicators to use in spatial risk management of the disease.

Measures to contain the spread of the epidemic and prevent the disruption of health systems have major impacts for individuals and companies in social and economic terms, so SCOPE can bring enormous benefits.

 

The Call for IC&DT Projects “AI 4 COVID-19: Data Science and Artificial Intelligence in Public Administration to reinforce the fight against COVID 19 and future pandemics - 2020” aims to ‘promote scientific knowledge based on the analysis of large amounts of data available in Public Administration. It is intended that the results of the ongoing investigation help to find solutions to significantly improve the provision of services to citizens and companies, as well as the decision-making processes, which will be progressively based on a knowledge of reality, technically supported by evidence and not by intuitions.’

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