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The Country, the pandemic and real-time data - a predictive risk model

How the use of predictive models can help us to understand the evolution of the pandemic in the portuguese national territory

Data you can trust


Understand the data better

This is a risk model developed with a high level of accuracy to understand Covid19's propagation dynamics at the national level. This tool provides a prototype that will allow the modeling of different Covid19 propagation scenarios against a set of pre-defined variables, as well as creating risk models. This tool can meet the needs of optimizing contingency plans and mitigation measures for the spread of the pandemic in a crisis context.

Likelihood of occurrence of a wave in a certain place, under certain circumstances, and its expected consequences, characterized by the impacts on the affected objects.

In the developed model, the probability expresses the similarity between vacancies, that is, the probability of occurring, conditioned to the probability that a previous event has occurred.

Susceptibility expresses the propensity of a given region to be affected by Covid19.

Danger is equivalent to the probability of occurrence of potentially destructive phenomena, in a given period of time and in a given area.

Potential damage
Potential harm is the product of vulnerability and economic value (number of infected people x potential number of hospitalizations) of the element at risk.

Vulnerability expresses the degree of loss to which a given person is subject to the occurrence of the phenomenon.

Source: DGS data


EU4COVID is a tool owned by Winning, a consulting company with almost 10 years of existence in the national market and dedicated to the application of scientific methods to solve complex problems at the management level.

With several certifications and international partnerships in the field of scientific management, it assumes itself as the market leader in terms of strategic scientific consultancy.



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