PathoMap

A weekly updated pathogen tracking platform that empowers users to monitor outbreaks, assess local risk, and stay protected through informative, data-driven insights.

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Inspiration

The spread and mortality rate of COVID-19 illustrated the devastating impact infectious diseases can have on global health. With over 704 million cases and 7 million deaths worldwide, the pandemic displayed how transparency, awareness, and timely information access are a must in preventing further disease outbreaks. Only informed individuals can make these decisions, and driven by AI-driven disease education, users can further access verified information, such as symptoms, transmission, and prevention, to better protect themselves from these pathogens.

What it does

PathoMap tracks and visualizes data on key infectious diseases — influenza, measles, and Nile — by collecting and processing information from verified public health APIs. Pulling from medical sources such as CDC, & WHO, PathoMap also generates verified information on these diseases for users to combat these transmissible viruses.

Users can:

  1. Click on a pin (e.g., California) to see current cases, risk level, and location.

  2. To the right is another pop-up that shows the specific disease information, including symptoms, spread, prevention, duration, and fatality rate.

Other features include

  1. Users can receive email notifications when a sudden increase in reported cases occurs in their area or a new disease pops up. Users must subscribe to the email newsletter to unlock this function.

How we built it

We used public health data APIs from organizations such as the CDC and WHO to collect verified disease reports. The backend was built to process this data, calculate infection intensity by location, and assign a local “infection score. The frontend integrates an interactive map interface where users can explore outbreaks visually. A notification and mailing system was implemented to alert subscribers to significant changes in disease activity. A self-report form was developed to crowdsource potential case information for enhanced accuracy.

Challenges we ran into

  1. Limited access to real-time, county-level disease data for specific illnesses.

  2. Data standardization — different APIs use varying formats and reporting intervals.

  3. Balancing data privacy with meaningful self-reporting contributions.

  4. Http Deployment Issue(EC2 Instance only is HTTP, had to use nginix, certbot)

  5. Fetching Data Not Available By Api (Used Selenium Scraper)

  6. Merge conflicts (Extensive Merge Conflicts -Due To Strange Setup On Other Machines (It kept creating branches), led to a point where entire functionality was erased)

  7. CORS Issus(Browser disallows sending certain JSON Data to be displayed, and map was not really visible)

Accomplishments that we're proud of

  1. Successfully integrated multiple public health datasets into a unified, real-time visualization tool.

  2. Created an interactive and intuitive map interface that displays outbreak severity at a glance.

  3. Developed a functional alert system that delivers timely notifications of potential disease surges.

  4. Designed a self-report mechanism to enhance public participation in disease surveillance.

What we learned

  1. Learned how to use AWS tools like DynamoDB, Amazon Bedrock, and EC2 Instance

  2. Thoroughly learned how to operate, navigate, and create things in a Next.js build environment

  3. Global and local disease reporting networks vary widely in update frequency and data resolution.

  4. Reliable disease tracking requires both institutional data and community input.

  5. Effective public health communication depends on presenting complex data in a clear, actionable format.

  6. Privacy and transparency can coexist through anonymous data contribution systems.

  7. Lack of proper API access can severely limit the amount of data access we have and can use

What's next for How to Rizz

  1. Expand to include additional diseases such as COVID-19, RSV, and dengue.

  2. Have a self-report feature where users can report anonymously their county, disease, and date when they experience symptoms, which can be used to power our email system, leading to a faster detection rate of pathogens.

  3. Track pathogens on an international scale.

  4. Provide faster real-time updates by increasing customer size.

  5. Separating cases based on hospitalization vs mortality vs infection.

  6. Incorporate other surveillance measures a. Wastewater and pollution management

  7. Time Visualization a. See the percentage difference in each week over a year

  8. Develop a mobile app version for easier access and real-time notifications.

  9. Add an explanation of the score and disease prevention methods

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