Authors

Checkout the Product Page

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Inspiration

Hello, my name is Nicolas Cepeda. In the last 3 weeks almost my entire Family was in contact with the corona virus (total of 5 out of 6 members) with different severity levels (mild till hospitalisation).

The Corona threat is real (and needs to handled with respect), is up to all of us to save lives.

What does the app do?

The #LetsStayAtHome App is designed to help people:

  • Manage their quarantine
  • Based on all the data collected calculate the likelihood that the person has been exposed to the virus
  • Inform about the availability of close by hospitals
  • Spread official news and help detect fake news
  • How to act in case of Emergency

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Running the code

Clone the app repository

cd app
npm install
npm run start

Risk Modelling

Data Collection

The App collects following data at onboarding:

  • General data (age, kanton, etc)
  • Past Health Conditions relevant to Covid
  • Questions regarding the quality of the quarantine
  • Symptom check

And prompts the user everyday to do a self check containing following information:

  • Symptom check
  • Questions regarding the quality of the quarantine

Algorithm

With all this data the app calculates the likelihood that the user as been exposed to the virus and generates a recommendation (stay at home, etc).

Current Implementation

The current model is based on simple linear algebra and needs to be recalibrated.

ML-based implementation

The anonymized data from the users are being collected in a centralised fashion.

Once enough data has been collected (specially interesting are users that became COVID+ or show symptoms of infection) an ML model is going to be trained to better predict the likelihood of infection.

Resources:

Problems to Solve

The app focuses in the following problems:

  • Quarantine management Help manage self quarantine better.
  • Hospital Help triage for more efficient resources management.
  • Economic Help reduce the economic impact.
  • Information Help spread official information and protect from Fake News
  • Data Anonymized Data Collection for better projection and models

Product Roadmap

Current - v0.7-beta

Try this version on your phone

  • Onboarding
  • Symptom Checkup
  • Simple Risk Modelling
  • Daily BAG News & Recommendations
  • Help in case of Emergency
  • Fake News Detection
  • Review all text & models
  • Improved Risk Modelling
  • Anonymised Data Collection
  • Landing Page
  • I18N

Next - v0.7-alpha

App Store Release required

Contributors

Following Persons have contributed to this project:

Feedback

Feedback of any kind is highly welcome at cepeda.nicolas@gmail.com.

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Hackathons

Technologies

ionic, stenciljs, typescript

Devpost Software Identifier

255156