Authors

Inspiration

At first, many people thought of Coronavirus as a shameful thing that should be kept secret, no one would want to share or make posts on social media if they’re tested positive of Covid-19 because they’re afraid it’d bring disgrace to their family and society. But recently, we saw some people ranging from actors, soccer players, to government officials that stood up and make posts on social media about their condition as they’re tested positive of Covid-19. They also added messages to help others fight and know they’re not alone. Responses from citizens also vary but for the most part are positive and pray for healing for those who’s tested positive with the virus.

We also conducted a Sentiment Analysis based on tweets from actors, soccer players, and government officials, along with replies from the citizens; the results were that most of the responses given were positive responses with a score of almost 70%.

This has encouraged us to build a Coronavirus early detection application and provide a platform for people infected by the virus to share about their conditions and share positive moral messages to the community on social media. We believe that positive things will result in positive energy to make people remain strong to face this pandemic.

What it does

This IGotCovid19 application provides several questions to users regarding their environment and personal conditions. These series of questions are asked to user to find out whether they’re in high risk of Covid-19 or not. Then, based on the answers, the system will calculate their health level and it will provide health advice. If someone gets result of high risk infected by Covid-19, the system will help to give them the option whether they want to share positive information and messages to the community on social media Twitter using the official account of I Got Covid-19. Of course, the result of this test is not a substitute for a doctor's medical diagnosis.

The purpose of sharing to social media is to increase awareness for the surrounding community. With this shared information, we hope that the public will realize how easily Coronavirus spreads in the environment around us and to be more cautious. It can also be a place to exchange positive messages and energy to those who suffer from the virus to know that it is not shameful, it is not a disgrace. It is a disease and we can fight against it.  The app will also help further monitoring of user condition regarding COVID-19 cases. Every active participation will be a big help to slow down the spread of the n-CoV virus and COVID-19.

How we built it

The IGotCovid19 application was built based on the research we did by observing people's responses to Coronavirus. Questions to measure users’ health level and to determine users’ risk of expose to Coronavirus were obtained from random data from various sources. By using the simple machine learning algorithm, namely the decision tree, it is found that someone who made direct contact with a person who tested positive for Coronavirus or someone who has traveled to a pandemic area, along with bad living habits and a weak immune system, could be surely is in high risk of (Covid-19) infection. The decision tree we used, it is separated from the main application. To build this web-based application, we use Nuxt.js, a framework from Vue.js which we think is lightweight and powerful to be used in building applications in a short time.

Challenges we ran into

The challenges we faced when build this application came from Nuxt.js. This is the first time we use this framework for our project. We do not really understand much about the data state structure, nor how to move from one component to another. We also have a little trouble in finding data from Coronavirus patients, namely data on more specific symptoms, travel history, immunity level of a person, and so on. We need this patient data to make more accurate predictions in determining whether someone is in positive, high risk of Covid-19 or not.

Accomplishments that we're proud of

Our team consists of people with different abilities. However, we succeeded in uniting ideas, collaborating between simple machine learning and software engineering, and making this application arrive at our goal of increasing people's awareness of Coronavirus. We are proud of this application because it uses a framework that we have never used before to build applications within a very short time.

What we learned

We have learned how to discuss and collaborate online. Not necessarily always face to face and close together. With a distance apart, our team can stay solid to solve a problem together. We learned how to build an application in a short time that can work effectively and efficiently

What's next for I Got Covid-19

Our application research is still ongoing. We are still looking for more and larger Coronavirus patient data to improve the accuracy using better machine learning algorithm and make it more powerful than other detection systems. We will improve the way we generate or share the user information to the Twitter and need support from Google Map to increase the accuracy of user location. Also, we will added a useful feature to prevent the spread of the viruses among people with GPS tracking technology that aims to speed up the steps for paramedics to provide immediate help to those who are exposed to this Coronavirus.

Try It out

Hackathons

Technologies

machine-learning, nuxt, twitter

Devpost Software Identifier

255806