Helping the government map the spread of COVID-19; An Inspiring Story of Marek and His team.

In April 2020, they intended to hand the app to governmental authorities free of charge. Although in the end, the authorities decided not to proceed with the application in production mode, they received many well-deserved accolades on the BETA Version.

Marek Hlavacek- Java Software Developer Team Leader in EmbedIT

“I joined one group that consists of IT enthusiasts from all over the country, and as a person working in the IT industry, I feel like helping the society with the skills that we have is a real-calling. With the ideas, we were already working on in our antifraud world, so it was quite easy to adapt those ideas to the COVID task.” Marek said.

Yes, Network Diagrams! That’s what we are going to talk about today.

Network Diagrams helping to identify the virus’s social network.

In some cases, we focus on infected patients; however, such infections need an environment in which to spread: human contact, from person to person. To identify the pattern is no easy task, yet it is achievable. One of the ways is by using Network Diagrams.

Network Diagrams (also called Graphs) show interconnections between a set of entities. A node (or known as vertice) represents each entity, and each connection between nodes is represented through links (or edges).

A Network Diagram is a technique for illustrating how an impact is related to another and for identifying the consequences of the impacts. In this case, it may be possible to predict the impact of each person’s movement reasonably well. Also, this data could be used in figuring out how to limit the tendency of people to socialize. Using Spring Boot and JavaScript Library D3 for network graphs, within a week of its development, the team gave the beta version of the app for testing to the Regional Hygiene Station in Zlín.

So how did this idea start?

During the development of ATS (Antifraud Tracking System), they proceeded the implementation of this tool with Microsoft excel.

ATS is used to track the investigation of potential fraud cases. Suspicious cases are detected by the automated process or manually. Each fraud case may contain many entities of different types

- Contract
- Sales Agent
- Retail Agent
- District Manager
- Retailer

The goal of the investigation is either to

· Confirm the fraud, or
· Reject the suspicion

Throughout the investigation, investigators use a lot of techniques for checking the data about applications, SA (Sales Agent), POS (Point of Sales), and others.

Over time, the team realized that the excel solution was not enough. Thus, Marek’s team started to work on a web application to speed up the investigation process. There was the time they moved on with the network graph.

The colleague from our head-quarter presented the first version. At that time, the implementation was done by a library called Jung, and then Marek’s team adopted it by using the D3 library. The idea behind it is simple, you can have a lot of the data in a table form, but if you see the same data in the network form, it can be faster to recognize there are some relations in between. For instance, you can have one mobile number, which will be in the middle of the graph, but you will see multiple lines within the application. You can also see that one photo/fingerprints/… that has been used more than once.

Back to the story of the apps and COVID-19, As we are all aware, the information about infected people with COVID-19 was placed publicly on some websites and news. With the network graph concept on hand, it was quite easy for Marek and his team to visualize what the society was missing in that time — to identify newly affected patients and whether that patients have close contact or relationship with the patients. That was when Marek brought this idea to the table, and their team gladly accepted it.

Marek and his team!

Marek leads his Risk and Antifraud team since 2016. The team consists of developers, DevOps, analytics, product manager, and testers located in Brno and one tester in Jakarta.

Marek’s journey with EmbedIT started as a small team of five, and now they have around 25 people within the team. When we asked him, what is his favorite things working here, his first answer is the team!

“My team consists of highly professional colleagues. Even Home Office or working remotely is not a big deal for us. We are handling everything smoothly. Apart from that, EmbedIT allow me to explore my skills from app to app, and people to people. I enjoy our corporation a lot, not only with colleagues here in Prague but also with the people in other countries.” He said

Check out more of #LifeInEmbedIT here!



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