Final project for the Health Analytics course at University of New Haven. The project aims at tidying, manipulating and analyzing health data for use in several public health outcomes.
Accidental drug deaths have become a growing public health concern in recent times. The need for effective prevention and control measures necessitates comprehensive data analysis and insights. The case study presents an analysis of accidental drug deaths data in Connecticut from 2012 to 2021, utilizing R programming language and its libraries, including dplyr and ggplot2, to extract valuable insights through data manipulation techniques.
The data set Accidental Drug Related Deaths from 2012-2021 in Connecticut has been derived from Connecticut Open Data Repository (Connecticut Data, 2021). Drug overdose is one of the leading causes of injury-related deaths in the U.S (Hedegaard, Minino, & Warner, 2020). An estimated number of 100,000 people have died in between April 2020 to 2021 due to drug overdoses, which was an increase of 28.5% from the previous year according to the CDC (2021).
The data set was collected by the Office of the Chief Medical Examiner in Connecticut through an investigation process that includes a toxicity report, death certificate, and a scene investigation. It includes 48 columns with information such as the number of deaths, demographic information of those who died (such as age, race, and gender), and the location and substances detected in the overdose for 9202 individuals.
You can find the report here.
Connecticut Data (2021). Accidental Drug-Related Deaths 2012-2021. Retrieved from https://data.ct.gov/Health-and-Human-Services/Accidental-Drug-Related-Deaths-2012-2021/rybz-nyjwLinks
Centers for Disease Control and Prevention (CDC) (2021, November 17). New CDC data show drug overdose deaths increased in 2020, driven by synthetic opioids. Retrieved from https://www.cdc.gov/nchs/pressroom/nchs_press_releases/2021/20211117.htm
Hedegaard H, Minino AM, Warner M. (2020). Drug overdose deaths in the United States, 1999–2019. NCHS Data Brief, no 394. Hyattsville, MD: National Center for Health Statistics.
Kaiser Family Foundation. (2021). Opioid Overdose Deaths by Race/Ethnicity. Retrieved from https://www.kff.org/other/state-indicator/opioid-overdose-deaths-by-raceethnicity/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%22asc%22%7D
Nahhas, R. W. (n.d.). Inspecting and transforming data. In Introduction to R. Retrieved from https://bookdown.org/rwnahhas/IntroToR/inspect.html
University of Cincinnati Research & Development Center. (n.d.). Pipe: An introduction to the magrittr-style pipes in R. Retrieved February 23, 2023, from https://uc-r.github.io/pipe
Wickham, H. (2014). Tidy data. Journal of Statistical Software, 59(10), 1-23. Retrieved from https://vita.had.co.nz/papers/tidy-data.pdf
Wickham, H. (n.d.). tidyr: Easily Tidy Data with ‘spread()’ and ‘gather()’ Functions. The Comprehensive R Archive Network (CRAN). Retrieved January 25, 2023, from https://cran.r-project.org/web/packages/tidyr/vignettes/pivot.html
Wickham, H., Danenberg, M., Eugster, R., Goulet, L., Loman, T., Takahashi, I., & Vaughan, D. (2019). Visualizing complex data with R: lessons learned from the trenches. Journal of Big Data. https://doi.org/10.1186/s40537-019-0191-1