May 6, 2020

A Biosurveillance System for the Protection of Citizens Against COVID-19

Integration, speed, data analysis, forecasting and protection: these are the keywords underlying the Eng-DE4Bios. The data-driven and cloud-native biosurveillance system developed by Engineering for the Veneto Region and Azienda Zero collects data from different sources, integrates and harmonizes it showing an updated view of the epidemic. Engineering is Italy’s largest systems integration group, member of the IDSA and part of the IDS Launching Coalition.
Angelo Marguglio

The coronavirus epidemic SARS-CoV-2 (COVID-19) is characterized by a high index of infection and rapid spreading. To ensure that those who are infected by the virus can be isolated, automatic and real-time monitoring is indispensable. The solution to this challenge is the biosurveillance system DE4Bios by Engineering. Based on Digital Enabler, it combines heterogeneous data sources to create databases on which to perform advanced data analytics. This way, public administrations and health institutions can define and apply epidemiological models, real-time geolocation of some clinical-health phenomena and predictive maps of contagion.

Biosurveillance as a basis for decision making

Biosurveillance is a medicine-related field in which the detection of pathogens and their resistance are regularly monitored, and the information is routed to a central system for the analysis and understanding of the epidemiological phenomenon. It is the process of collecting, combining, interpreting and communicating essential information concerning disease-related threats to obtain early observations and warnings. Biosurveillance promotes and contributes to an awareness of the overall health/clinical situation and provides information for a better decision-making process at all levels. The process is not cyclical, but is dynamic and interacts at various levels, for an ongoing contribution and a prolonged effect.

The Eng-DE4Bios service developed for the Veneto region: a detailed description

The Digital Enabler is Engineering’s ecosystem platform based on open source components of the FIWARE platform. It is considered the global standard for developing digital applications as a basis for new business and service management models. The Digital EnablerTM allows the integration, harmonization, and synchronization of data from different sources and in different formats. In this way, they can be associated, quickly and easily viewed, combined and analyzed to build value-added services.

The Eng-DE4Bios service developed for the Veneto Region and Azienda Zero helps the Regional Administration manage the epidemic by providing:

  • general practitioners with a real-time overview of their patients, detailing who have undergone COVID-19 tests, complete with the results and rapid geolocation of all cases on a map
  • members of the Task Force / Regional Crisis Unitwith 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.
  • operators of healthcare organizationswith 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)
  • occupational doctorswith 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

The systematic collection of all this information makes it possible to create a database for the implementation of different types of epidemiological models that can be used to illustrate possible trends of the epidemic. These models have been implemented using the Anylogic modeling software, an application that allows the epidemic to be automatically calibrated and simulated, with the possibility of forecasting the different scenarios whenever the models’ parameters are changed.

Automatic Simulation of the Epidemic

In limiting the contagion, the possibility of immediately seeing the positive cases and their relationships has proven to be extremely valuable and is not offered by any other control system used in other regions. The possibility of acting upon integrated data has also allowed the Veneto Region to implement several known epidemiological models. This has improved the management of the crisis thanks to the possibility of making reliable forecasts in terms of the trend of the hypothetical curve (and therefore of the peak) and the management of the intensive care treatments for each individual hospital.

The biosurveillance system is more fundamental than ever for the post-lockdown phase 2; the real time monitoring of the molecular and the serological test results will make it possible to have widespread control of the territory and the onset of new clusters (both familiar and in the workplace), allowing application of the region’s protocols for the safe recovery of production activities.

Datasets Based on Assured Usage Policies

Eng-DE4Bios uses exclusively personal and clinical-health data. These data are already in the possession of the Regions and the Local Health Offices (ULSS) for treatment reasons, and the Regions and Local Health Offices are authorized to access and analyze them. Their aggregation and analysis fall within the scope of the epidemiological investigation activities for which the healthcare structures and the administrative public health protection bodies are responsible. This use of the data is even compliant with the GDPR.

Author: Angelo Marguglio
Angelo Marguglio is Research Area Manager and Head of the "Smart Industry and Agrifood" Unit at Engineering.

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