Post by Kimberly D, PhD, MS²

Day 8, SASsy SQL? My SAS review ended up spilling over into SQL Sunday as I realized that I needed to review SAS a LOT more! So, I kinda’ cheated a bit on my SQL review and used SQL in SAS instead. Here is a snippet of how that worked codewise, with the image on this post representing the output: PROC SQL; TITLE "Count of Virally Suppressed Patients by Housing Status"; SELECT Gender, viralSupp, housingStatus FROM dataHIV3 GROUP BY housingStatus; QUIT; Housing is a serious challenge for people who are living with HIV (PLWHIV), so I decided to create a table of the relationship between patients who are virally suppressed and their housing status. As is the case in real life, HIV + people who live in temporary or unstable housing (usually homelessness), not surprisingly also have challenges being virally suppressed. If you’re interested in reading more about the impact of housing on viral load, here’s a 2018 article from PUBMED: The Influence of Housing Status on the HIV Continuum of Care: Results From a Multisite Study of Patient Navigation Models to Build a Medical Home for People Living With HIV Experiencing Homelessness, https://lnkd.in/dK4KFJw #HIV #SAS #SQL #DataScience #PhDLife