Inspiration

During the quarantine, it's important to stick to the doctors' recommendations about social distancing and avoiding crowds. To stay as much home as possible. All those measures will help to flatten "the curve" and buy the healthcare system precious time to prepare. To learn more about the disease, to experiment with the efficiency of different medical supplies and to progress on a vaccine. One bottleneck of the measures taken is overcrowded stores and lines in front of the entrances and other places such as postal offices, parks, etc. It's critical to avoid crowds of people in those places during the quarantine!

On the other hand, quarantine alone won't solve the problem with the pandemic, flattening "the curve" will buy a time for the healthcare system but will dry the financial system. Therefore the ultimate goal is not just to slow down the spread but to contain it. And as South Korean example showed in order to efficiently do it we have to isolate the cases and track the history of social interactions with the Covid-positive people. In Europe, we respect privacy and freedom. We can't simply track the people using their credit card and cellular data without their consent. The might other ways to solve this problem without violating privacy. If the system will have anonymous data who visited the store (another place) at the given time, and if one person who visited it was identified by the healthcare system as a Covid-positive we can self-isolate and test those people first.

What it does

Given all the above we came up with the following solution.

  1. The COVoIDer app that will allow citizens to book a slot during which they're willing to visit the store (another place).
  2. The COVoIDer Security app that will allow personal to validate eligibility to visit the store by a citizen at a given time based booking she made previously.
  3. Backend Scoring System for each citizen that will increase/decrease the score based on a number of factors. For example, if one citizen visited the same place during the time that the proven covid-positive visited it (during the incubation period), the score will fall. After 14 days the score will be increased again. If the score will be lower some threshold, the citizen will be required for a test (even if she is not showing the symptoms).
  4. Backoffice Web-based app for medical personnel (doctors, nurses). It will allow to update the status of their patients to one of the following: Positive, Negative, Suspected, Recovered, Dead (all with respect to Covid-19 infection). It will allow to see the citizens with low score who passed the threshold for the test or who are about to pass it. And either send a medical group to run the test or schedule an appointment for them in one of the dedicated for the test facilities.

How I built it

We've built two android apps: one for the citizen, another for security personnel. We've used Kotlin and Android Studio to build them.

Besides that, we've built the backend with scoring algorithms. The bigger the score you have the lower is the risk for you to being exposed to the covid-19. We've used Java and Spring Boot on the backend side.

Finally, we've built a Backoffice web app for the doctors to see the information regarding their patients and update the status easily. For the frontend, we've used React.js, MaterialUI.

Challenges I ran into

The main problem that we encountered was how to integrate the network of food suppliers, medical personnel and end-users of the application - citizens of the country. As a result, we managed to do this through three interfaces for each group of users of the system and a shared database, where everyone has the right to receive only a certain amount of information that corresponds to them.

Accomplishments that I'm proud of

It was an honor to participate in the event, connect with the people worldwide seeking to find solutions to fight the disease caused by Covid-19 infection. We're proud to be helpful and add our small contribution to this huge problem. We are proud that in the limited amount of time we were able to build 2 mobile apps and 1 web app with sophisticated scoring algorithms to help people avoiding the lines and predict the risks of being contaminated.

What I learned

It was our first online hackathon, and we've learned a number of different things regarding the healthcare system of different countries, missing puzzles that we can now understand how to slow down the spread and how to avoid pandemics like this in the future. From a technical standpoint, we improved our knowledge of different scoring techniques and algorithms available.

What's next for COVoIDer

First of all, we plan to develop iOS apps for citizens and security personnel to allow all the potential customers to access the product. We plan to work further on improving our scoring algorithms to detect people with more risk of being contaminated. We plan to build an API that third-party providers can access, for example, delivery services and government institutions.

Once the Covid-19 crisis will be over we plan to use the app for optimizing lines in a number of use cases, including healthcare, airports, postal offices, etc.

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