New surveillance solution to put COVID-19 on lockdown
How code can stop the spread
Monitoring the spread of COVID-19 has been an all-hands-on-deck global challenge. The virus blindsided the world and continues to proliferate via very sinister tactics — asymptomatic and pre-symptomatic spread. Professionals everywhere are grappling with how to prevent people from spreading a disease they don’t even know they have.
The Infosys team developed a new way to keep a watchful eye on the virus. Their solution, Infosys Epidemic Surveillance Suite, was a regional finalist in the 2020 Call for Code Global Challenge. It’s a robust system that elevates contact tracing with data-driven insights, a platform for collaboration and the means to engage with COVID patients and their contacts. Call for Code Digest was able to catch up with the team to learn more about their Call for Code experience:
What inspired you to enter into Call for Code?
Just a couple of weeks before the announcement of Call for Code 2020, we were brainstorming a solution to make COVID-19 data discovery, elicitation, presentation and dissemination more efficient. We wanted to develop an extensive solution to manage COVID and any epidemic in the future. We saw the category Crisis Communication, which was a perfect fit, and we did not have to think twice about participating in the Global Challenge.The COVID-19 domain was new to us, so it was continuous learning from both domain and technical perspectives.
What problem does your solution solve in a unique way?
We focused on a set of critical challenges of monitoring and managing the spread of COVID-19 — timely identification of positive patients, generating real-time insights, data collaboration between stakeholders and engaging patients and their contacts. These challenges inspired us to develop the solution as a system of systems that solve each challenge and together provide comprehensive surveillance of the epidemic.
What is one interesting fact you have learned through this project?
We have learned that the compartmental models in epidemiology have not been efficient for COVID-19. We are continuing our research to find the right machine learning model to predict COVID-19-related information.
Accessing the right data at the right time can change the world for the better. Call for Code continues to find ways to leverage technology and human ingenuity to build solutions that fight back. Feeling inspired to get involved? Check out various Call for Code open source projects that you can contribute to today.
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