Engineering: leader della Digital Transformation

Biosurveillance platform

Eng-DE4Bios

An open source and cloud-native biosurveillance solution for SARS-Cov-2.

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Biosurveillance system

Eng-DE4Bios, our biosurveillance platform, enables to monitor the evolution of the epidemic, to map and geolocate infected subjects and to identify clusters requiring higher attention.

Based on Digital Enabler, our ecosystem platform developed on open source components of the FIWARE platform, it allows to integrate, harmonize, correlate and visualize scattered and multi-source data.
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How does it work

The platform, already active in Italy collects, harmonizes and correlates the data collected, thus representing an active bio-surveillance model that can:

  • define delimited user clusters (State, Regions, Cities, etc ...)
  • define subjects' health profile (positive / negative)
  • identify the network of social relationships (family, work, neighbors, school) that may have exposed the citizen to contagion
  • predict onset of clusters that require higher attention.
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Features and Benefits

Eng-DE4Bios provides:

  • general practitioners with a view of their patients, detailing who has carried out screening tests as well as a tool to appropriately approach patients
  • occupational doctors with real-time indicators of positive Covid-19 cases within the businesses they assist, a view on workers who carried out the tests, the possibility of recording the results of tests carried out by the business, a tool to apply the correct protocols and safely approach work activities
  • operators of healthcare organizations with indicators on the evolution of the epidemic, a georeferenced view of the tests carried out (their outcome and the analysis of the family, residence and work context of the examined subject), a view to evaluate, real time, the available workforce within organizations, and to monitor clusters at risk (nursing homes, housing contexts with many positive cases)
  • members of the Task Force / Regional Crisis Unit with a view to monitor real time the epidemic and carry out epidemiological simulations, identify clusters that require high attention (nursing homes, positivized families), a georeferenced view of the tests carried out on the territory, of aggregated positive cases and the operational status of all regional structures.
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Applications

  • Informs, in real time, on the status of the infected population (infected, healed, immunized, deceased, hospitalized, hospitalized in intensive care, in home isolation)
  • Monitors the spread of the virus among health workers (infected operators, isolated operators), highlighting the decrease or increase of the workforce
  • Provides a relation-based service that, if a subject is tested positive, identifies subjects who are likely to be infected among members of the same family and domiciled at the same address
  • Identifies clusters at risk (nursing homes, families, workplaces) to be screened and subject to forms of preventive isolation
  • Provides a service that, if a subject is tested positive, identifies whether the subject is a worker and / or student, the data of the employer / school, other addresses and contacts to identify clusters of likely infected people.

White Paper

Augmented City

We augment the way our cities and citizens use time and space, improving the overall quality of life for all city actors by delivering sustainable economic and financial project & service patterns.

Case Study

Biosurveillance against Covid-19

Eng-DE4Bios, our integrated biosurveillance platform, allows Veneto Region to implement a biosurveillance system that uses the power of data to fight the new Coronavirus.

Case Study

La Plata City
adopts the Digital Enabler

Our Digital Enabler is exploiting the value of big data for La Plata, a big city in Argentina, to provide insights on tourism, environment and health in one of the Argentina's largest cities.

Research Project

Digital Enabler for Smart Cities

Our solution, City Enabler, leverages new technologies to evolve the way European cities use Big Data.