In this section I briefly present comments and in some cases the code about the implementation of specific tasks that aid my research projects,
together with their respective link to their GitHub space in my repository. If you are interested and want to know more send me an email at firstname.lastname@example.org.
In this project, we redesigned the discharge worksheets that physicians provide patients after surgery. The desing principal objective is to
increase the saliency of opioid addiction risks. Given a prescription on number of pills and days, the D3.js implementation would query the data and produce a calendar
with the marked final day of the prescription, but also, signaling with colors points of the distribution of prescriptions for that given surgical procedure.
This was the final project for Data Visualization (ENGR-E583). Several of its features are being implemented by Dr. Gabriel Brat, at the Harvard Medical School Teaching Hospital institutions. The repository presents a Readme file with the main proposal and how to use it, with links to the dynamic tool and a already completed worksheet. The project was joint work with Tim Whitson, Melisa Machuret, Neha Rawat and Himani Bhat. [GitHub Repository] [Live Example]
During 2020, the Health Policy team led by Prof. Kosali Simon, of which I was part, started a series of projects that attempted to estimates the effects COVID and the response policies was having in different aspects of our normal lives (i.e. mobility, employment, internet queries behavior, among others). In this repository I documented, the cleaning and processing of school closures using information collected by EdWeek, and linked to DoE information on school and school district characteristics. The final output showcased how closures were related to the population beeing affected, by school, then by school district, local government, and finally, state level interventions. This exercise provided detailed variation on the extent to which Americans were being affected by these decisions. [GitHub Repository]
I implement a routine for map creation using stata and posterior animation in a .gif file. The files on the right were produced following the routine.
The exercise is part of a wider project joint with Sumedha Gupta and Kosali Simon and benefited from the research assistance of Siddartha Rao.
The repository presents a Readme file to implement the python code as well as the Stata code that generate the individual maps.
Must Access PDMPs
Daily Limit PDMPs
This is a very simple program that leverages the ability of stata to import data from the Federal Reserve. It transforms the nominal values of a time series variable, into a CPI adjusted
variable on the baseline year you decide. This version transforms annual data, but the transformation for monthly or quarterly is relatively simple.
It takes as inputs 1) the initial year from when you want to start the series, 2) the baseline year, 3) the name of the time variable in you dataset and finally 4) the
variables you want the program to transform. The output of the program is a set of variables with the same name plus the suffix '_rl'. You need to generate your own
FRED key, which you can easily obtain following these instructions.