What it does
Determining the barriers to HIV screening and explaining HIV incident rates.
How we built it
We used a generalized linear model (linear regression) to identify predictors of HIV incident rates in Charlotte by zip codes.
Challenges we ran into
Data connection was an issue. Data mapping was also another obstacle.
Accomplishments that we're proud of
We were able to retrieve data from the different clinics and join them accordingly for our analysis.
What we learned
Throughout this exercise, we were able to understand that health care access is not only driven by policies, but also by the structure of the patient data and how that data is collected and stored for analytic purposes.
What's next for DataHolics
We will use the predictors from our linear regression analysis and train a model to predict HIV rates in Charlotte for the next 5 years.