Covid 19 has greatly impacted the world. With the implementation of vaccines, the impact of covid on the world has been greatly reduced, but there are many people who refuse to get vaccinated which allows covid to have a larger impact on the world than it would if those people who refuse to get vaccinated get vaccinated. My research project looks at the sociodemographic factors that impact vaccine uptake across the US. We recently ran a multivariate geographically weighted regression which creates a regression model that takes geographical location and distance into account when making the model. The geographical component causes the model to be more accurate than a simple linear regression. We are planning on using this regression model to predict vaccine uptake on the census block group level and then use a “local indicators of spatial association” analyses to find census block groups that are local outliers in vaccine uptake. We can then look at these local outliers and determine which census block groups are more at risk which should be able to help counties decide where they need to focus their efforts on increasing vaccine uptake.
There were many techniques, such as multivariate geographically weighted regression, that we used to analyze data that I had never heard about before starting this research project. I had a very good time learning about these techniques and implementing them because I have an interest in data analyses and playing with data. This research project has helped me learn more about data analyses in an out of classroom setting which should help me a lot in the future.
An average research day starts off with a meeting in the morning where the members in my group update each other on what has been done and what we want to do next. After this meeting, we separate to work on whatever we need to get done that day by ourselves. Sometimes we will have a meeting towards the end of the day to update the group on our progress.