## Inspiration

Our team identified two intertwined health problems in developing countries:

1) Lack of easy-to-obtain medical advice due to economic, social and geographic problems, and

2) Difficulty of public health data collection in rural communities.

This weekend, we built SMS Doc, a single platform to help solve both of these problems at the same time. SMS Doc is an SMS-based healthcare information service for underserved populations around the globe.

Why text messages? Well, cell phones are extremely prevalent worldwide [1], but connection to the internet is not [2]. So, in many ways, SMS is the *perfect* platform for reaching our audience in the developing world: no data plan or smartphone necessary.

## What it does

Our product:

1) Democratizes healthcare information for people without Internet access by providing a guided diagnosis of symptoms the user is experiencing, and

2) Has a web application component for charitable NGOs and health orgs, populated with symptom data combined with time and location data.

That 2nd point in particular is what takes SMS Doc's impact from personal to global: by allowing people in developing countries access to medical diagnoses, we gain self-reported information on their condition. This information is then directly accessible by national health organizations and NGOs to help distribute aid appropriately, and importantly allows for epidemiological study.

**The big picture:** we'll have the data and the foresight to stop big epidemics much earlier on, so we'll be less likely to repeat crises like 2014's Ebola outbreak.

## Under the hood

* *Nexmo (Vonage) API* allowed us to keep our diagnosis platform exclusively on SMS, simplifying communication with the client on the frontend so we could worry more about data processing on the backend. **Sometimes the best UX comes with no UI**
* Some in-house natural language processing for making sense of user's replies
* *MongoDB* allowed us to easily store and access data about symptoms, conditions, and patient metadata
* *Infermedica API* for the symptoms and diagnosis pipeline: this API helps us figure out the right follow-up questions to ask the user, as well as the probability that the user has a certain condition.
* *Google Maps API* for locating nearby hospitals and clinics for the user to consider visiting.

All of this hosted on a Digital Ocean cloud droplet. The results are hooked-through to a node.js webapp which can be searched for relevant keywords, symptoms and conditions and then displays heatmaps over the relevant world locations.

## What's next for SMS Doc?

* Medical reports as output: we can tell the clinic that, for example, a 30-year old male exhibiting certain symptoms was recently diagnosed with a given illness and referred to them. This can allow them to prepare treatment, understand the local health needs, etc.
* Epidemiology data can be handed to national health boards as triggers for travel warnings.
* Allow medical professionals to communicate with patients through our SMS platform. The diagnosis system can be continually improved in sensitivity and breadth.
* More local language support

[1] <http://www.statista.com/statistics/274774/forecast-of-mobile-phone-users-worldwide/>

[2] <http://www.internetlivestats.com/internet-users/>
## Inspiration

Most of us have had to visit loved ones in the hospital before, and we know that it is often not a great experience. The process can be overwhelming between knowing where they are, which doctor is treating them, what medications they need to take, and worrying about their status overall. We decided that there had to be a better way and that we would create that better way, which brings us to EZ-Med!

## What it does

This web app changes the logistics involved when visiting people in the hospital. Some of our primary features include a home page with a variety of patient updates that give the patient's current status based on recent logs from the doctors and nurses. The next page is the resources page, which is meant to connect the family with the medical team assigned to your loved one and provide resources for any grief or hardships associated with having a loved one in the hospital. The map page shows the user how to navigate to the patient they are trying to visit and then back to the parking lot after their visit since we know that these small details can be frustrating during a hospital visit. Lastly, we have a patient update and login screen, where they both run on a database we set and populate the information to the patient updates screen and validate the login data.

## How we built it

We built this web app using a variety of technologies. We used React to create the web app and MongoDB for the backend/database component of the app. We then decided to utilize the MappedIn SDK to integrate our map service seamlessly into the project.

## Challenges we ran into

We ran into many challenges during this hackathon, but we learned a lot through the struggle. Our first challenge was trying to use React Native. We tried this for hours, but after much confusion among redirect challenges, we had to completely change course around halfway in :( In the end, we learnt a lot about the React development process, came out of this event much more experienced, and built the best product possible in the time we had left.

## Accomplishments that we're proud of

We're proud that we could pivot after much struggle with React. We are also proud that we decided to explore the area of healthcare, which none of us had ever interacted with in a programming setting.

## What we learned

We learned a lot about React and MongoDB, two frameworks we had minimal experience with before this hackathon. We also learned about the value of playing around with different frameworks before committing to using them for an entire hackathon, haha!

## What's next for EZ-Med

The next step for EZ-Med is to iron out all the bugs and have it fully functioning.
## Inspiration

When the first experimental COVID-19 vaccine became available in China, hundreds of people started queuing outside hospitals, waiting to get that vaccine. Imagine this on a planetary scale when the whole everybody has to be vaccinated all around the world. There's a big chance while queuing they can spread the virus to people around them or maybe get infected because they cannot perform social distancing at all. We sure don't want that to happen.

The other big issue is that there are lots of conspiracy theories, rumors, stigma, and other forms of disinformation simultaneously spread across our social media about COVID-19 and it's vaccine. This misinformation creates frustrations for users many asking, we really don't know which one is right? Which one is wrong?

## What it does

Immunize is a mobile app that can save your life and save your time. The goal is to make the distribution of mass-vaccination become more effective, faster, and less crowded. With this app, you can book your vaccine appointment based on your own preference. So the user can easily choose the hospital based on the nearest location and easily schedule an appointment based on their availability.

In addition, based on the research we found that most of Covid-19 vaccines requires 2 doses given in 3 weeks apart to achieve that high effectiveness. And there's a big probability that people can forget to return for a follow-up shot. We can minimize that probability. This app will automatically schedule the patient for the 2nd vaccination so there is a less likelihood of user error. The reminder system (as notification feature) that will remind them in their phone when they have appointment that day.

## How we built it

We built the prototype using flutter as our client to support mobile. We integrated radar.io for hospital search. For facial recognition we used GCP and SMS reminders we used twilio. The mobile client connected to firebase: using firebase for auth, firebase storage for avatars and firestore for user metadata storage. The second backend host used datastax.

## Challenges we ran into

Working with an international team was very challenging with team members 12+ hours apart. All of us were learning something new whether it was flutter, facial recognition or experimenting with new APIs. Flutter APIs were very experimental, the camera API had to be rolled back two major version which occurred in less than 2 months to find a viable working version compatible with online tutorials

## Accomplishments that we're proud of

The features:

1. **QR Code Feature** for storing all personal data + health condition, so user don't need to wait for a long queue of administrative things.
2. **Digital Registration Form** checking if user is qualified of COVID-19 vaccine and which vaccine suits best.
3. **Facial Recognition** due to potential fraud in people who are not eligible for vaccination attempting to get limited supplies of vaccine, we implemented facial recognition to confirm the user for the appointment is the same one that showed up.
4. **Scheduling Feature** based on date, vaccine availability, and the nearby hospital.
5. **Appointment History** to track all data of patients, this data can be used for better efficiency of mass-vaccination in the future.
6. **Immunize Passport** for vaccine & get access to public spaces. This will create domino effect for people to get vaccine as soon as possible so that they can get access.
7. **Notification** to remind the patients every time they have appointment/ any important news via SMS and push notifications
8. **Vaccine Articles** - to ensure the user can get the accurate information from a verified source.
9. **Emergency Button** - In case there are side effects after vaccination.
10. **Closest Hospitals/Pharmacies** - based on a user's location, users can get details about the closest hospitals through Radar.io Search API.

## What we learned

We researched and learned a lot about the facts of COVID-19 Vaccine; Some coronavirus vaccines may work better in certain populations than others. And there may be one vaccine that seems to work better in the elderly than in younger populations. Alternatively, one may work better in children than it works in the elderly. Research suggests, the coronavirus vaccine will likely require 2 shots to be effective in which taken 21 days apart for Pfizer's vaccine and 28 days apart for Moderna's remedy.

## What's next for Immunize

Final step is to propose this solution to our government. We really hope this app could be implemented in real life and be a solution for people to get COVID-19 vaccine effectively, efficiently, and safely. Polish up our mobile app and build out an informational web app and a mobile app for hospital staff to scan QR codes and verify patient faces (currently they have to use the same app as the client)