Dr. Semmelweis and the Importance of Handwashing

Hungarian physician Dr. Ignaz Semmelweis worked at the Vienna General Hospital with childbed fever patients. Childbed fever is a deadly disease affecting women who have just given birth, and in the early 1840s, as many as 10% of the women giving birth died from it at the Vienna General Hospital. Dr.Semmelweis discovered that it was the contaminated hands of the doctors delivering the babies, and on June 1st, 1847, he decreed that everyone should wash their hands, an unorthodox and controversial request; nobody in Vienna knew about bacteria.

You will reanalyze the data that made Semmelweis discover the importance of handwashing and its impact on the hospital.

The data is stored as two CSV files within the data folder.

yearly_deaths_by_clinic.csv contains the number of women giving birth at the two clinics at the Vienna General Hospital between the years 1841 and 1846.

Column	Description
`year`	Years (1841-1846)
`births`	Number of births
`deaths`	Number of deaths
`clinic`	Clinic 1 or clinic 2

monthly_deaths.csv contains data from 'Clinic 1' of the hospital where most deaths occurred.

Column	Description
`date`	Date (YYYY-MM-DD)
`births`	Number of births
`deaths`	Number of deaths

# Imported libraries
library(tidyverse)

# Read datasets/yearly_deaths_by_clinic.csv into yearly
yearly <- read_csv("data/yearly_deaths_by_clinic.csv")

# Print out yearly
yearly

The table above shows the number of women giving birth at the two clinics at the Vienna General Hospital for the years 1841 to 1846. You'll notice that giving birth was very dangerous; an alarming number of women died as the result of childbirth, most of them from childbed fever.

We see this more clearly if we look at the proportion of deaths out of the number of women giving birth.

# Adding a new column to yearly with proportion of deaths per no. births
yearly <- yearly %>%
    mutate(proportion_deaths = deaths/births)

# Print out yearly
yearly

# Read datasets/yearly_deaths_by_clinic.csv into yearly
monthly <- read_csv("data/monthly_deaths.csv")

# Print out monthly
monthly

# Adding a new column to montlhy with proportion of deaths per no. births
monthly <- monthly %>%
    mutate(proportion_deaths = deaths/births)

# Print out monthly
monthly

# Setting the size of plots in this notebook
options(repr.plot.width=7, repr.plot.height=4)

# Plot yearly proportion of deaths at the two clinics
ggplot(yearly, aes(x=year, y=proportion_deaths, color=clinic)) +
    geom_line()

Why is the proportion of deaths constantly so much higher in Clinic 1? Semmelweis saw the same pattern and was puzzled and distressed. The only difference between the clinics was that many medical students served at Clinic 1, while mostly midwife students served at Clinic 2. While the midwives only tended to the women giving birth, the medical students also spent time in the autopsy rooms examining corpses.

Semmelweis started to suspect that something on the corpses, spread from the hands of the medical students, caused childbed fever. So in a desperate attempt to stop the high mortality rates, he decreed: Wash your hands! This was an unorthodox and controversial request, nobody in Vienna knew about bacteria at this point in time.

# Plot monthly proportion of deaths
ggplot(monthly, aes(date, proportion_deaths)) +
    geom_line() +
    labs(x = "Year", y="Proportion of Deaths")

# From this date handwashing was made mandatory
handwashing_start = as.Date('1847-06-01')

# Add a TRUE/FALSE column to monthly called handwashing_started
monthly <- monthly %>%
    mutate(handwashing_started = date >= handwashing_start)

# Plot monthly proportion of deaths before and after handwashing
ggplot(monthly, aes(x=date, y=proportion_deaths, color=handwashing_started)) +
    geom_line() +
    labs(x = "Year", y = "Proportion of Deaths")

# Calculating the mean proportion of deaths 
# before and after handwashing.

monthly_summary <- monthly %>%
    group_by(handwashing_started) %>%
    summarise(mean_proportion_deaths = mean(proportion_deaths))

# Printing out the summary.
monthly_summary