We are trying to tackle the dissemination and prevention of the COVID-19. It is known that some patients do not show symptoms or show only mild symptoms even though they are also infected, they are the undetected. The undetected have a huge impact on the dissemination of the virus. We are striving to detect the undetected so that authorities can focus their efforts in specific areas or have a better understanding of where to put the focus.

  • The main goal of ARGUS-20 project is to determine how likely the population of a specific household is to be already carrying the virus. The information will allow authorities to plan ahead:
  • To achieve our goal, we will ask users to input data from their daily life; such as their outings, having packages delivered, etc. Users will also input information about any symptoms they could be experiencing, drugs they are taking, and so on.
  • With sufficient information, once a high number of individuals are tracked, it will be possible to extrapolate a pattern by doing Data Science on the information in the database

What it does

Our solution is based on a cloud platform that will be integrated by three different components:

  • CoWaldo app: A web/mobile application for data acquisition. People will register data using a user friendly app.
  • Data repository: A database where all data entered by our users will be stored.
  • Reporting dashboard: A web application where physicians or analysts will be able to report and exploit the data acquired.

In order to "detect" positives amongst asymptomatic population, we introduce the concept of 'Risk Factor'. We focus our solution on households and not in specific individuals.

How we built it

We split the team in different subgroups. Not before discussing the topic, gathering ideas, outlining the most relevant questions the user would need to answer. We propose to use a website combining information about the user demographic, health, habits and link them with their household.

Our Project will assess for the first time the differential vulnerability to COVID-19 as a function of the health situation, habits and environment of the user.

Some representative data of clinical evolution of the potential disease of the user are variable from one day to the other.

The CoWaldo app presents the possibility to be filled on a daily basis and a way to assure and follow-up of the users. Our findings will be of particular clinical relevance as asymptomatic patients may not have symptoms but people around them and their environment may reveal crucial information.

Challenges we ran into

TIME was a challenge since everything had to be done rather quickly. Besides the obvious, we struggled finding the right way to ask the user the relevant questions so that the application is not intrusive.

Accomplishments that we're proud of

Communication and respect among the members of the group. Everyone put a lot of effort and we manage to deliver a simple

What we learned


What's next for ARGUS-20

  • Polish the program.
  • Validate the model.
  • Expand to other platforms.

Try It out



express.js, heroku, javascript, node.js, postgresql, react

Devpost Software Identifier