shukkkur / Analyzing-The-Discovery-of-Handwashing

Analyzing the medical data Dr.Semmelweis collected.

Analyzing-The-Discovery-of-Handwashing

This is Dr. Ignaz Semmelweis, a Hungarian physician. He is thinking about childbed fever because in the early 1840s at the Vienna General Hospital as many as 10% of the women giving birth die from it.
He is thinking about it because he knows the cause of childbed fever: It's the contaminated hands of the doctors delivering the babies. And they won't listen to him and wash their hands!

Let's start by looking at the data that made Semmelweis realize that something was wrong with the procedures at Vienna General Hospital.

yearly = pd.read_csv('datasets/yearly_deaths_by_clinic.csv')
print(yearly)

	year	births	deaths	clinic
0	1841	3036	237	clinic 1
1	1842	3287	518	clinic 1
2	1843	3060	274	clinic 1
3	1844	3157	260	clinic 1
4	1845	3492	241	clinic 1
5	1846	4010	459	clinic 1
6	1841	2442	86	clinic 2
7	1842	2659	202	clinic 2
8	1843	2739	164	clinic 2
9	1844	2956	68	clinic 2
10	1845	3241	66	clinic 2
11	1846	3754	105	clinic 2

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.

1. The alarming number of deaths

yearly['proportion_deaths'] = yearly.deaths / yearly.births

clinic_1 = yearly[yearly.clinic == 'clinic 1']
clinic_2 = yearly[yearly.clinic == 'clinic 2']

display(clinic_2)

Let's zoom in on the proportion of deaths at Clinic 1.

	year	births	deaths	clinic	proportion_deaths
6	1841	2442	86	clinic 2	0.035217
7	1842	2659	202	clinic 2	0.075968
8	1843	2739	164	clinic 2	0.059876
9	1844	2956	68	clinic 2	0.023004
10	1845	3241	66	clinic 2	0.020364
11	1846	3754	105	clinic 2	0.027970

2. Death at the clinics

If we now plot the proportion of deaths at both Clinic 1 and Clinic 2 we'll see a curious pattern…

ax = clinic_1.plot(x='year', y='proportion_deaths', label='Clinic 1')
clinic_2.plot(x='year', y='proportion_deaths', label='Clinic 2', ax=ax)

plt.ylabel("Proportion deaths")
plt.show()

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.

monthly = pd.read_csv('datasets/monthly_deaths.csv', parse_dates=['date'])

# Calculate proportion of deaths per no. births
monthly["proportion_deaths"] = monthly.deaths/monthly.births

print(monthly.head())

	date	births	deaths	proportion_deaths
0	1841-01-01	254	37	0.145669
1	1841-02-01	239	18	0.075314
2	1841-03-01	277	12	0.043321
3	1841-04-01	255	4	0.015686
4	1841-05-01	255	2	0.007843

3. The effect of handwashing

Starting from the summer of 1847 the proportion of deaths is drastically reduced and, yes, this was when Semmelweis made handwashing obligatory.
The effect of handwashing is made even more clear if we highlight this in the graph.

Date when handwashing was made mandatory handwashing_start = pd.to_datetime('1847-06-01')

before_washing = monthly[monthly.date < handwashing_start]
after_washing = monthly[monthly.date >= handwashing_start]

ax = before_washing.plot(x='date', 
              y='proportion_deaths', label='Before Washing')
after_washing.plot(x='date',y='proportion_deaths', label='After Washing', ax=ax)

4. More handwashing, fewer deaths?

before_proportion = before_washing.proportion_deaths
after_proportion = after_washing.proportion_deaths
mean_diff =  after_proportion.mean() - before_proportion.mean()

print(mean_diff)

-0.08395660751183336
It reduced the proportion of deaths by around 8 percentage points!

5. A Bootstrap analysis of Semmelweis handwashing data

To get a feeling for the uncertainty around how much handwashing reduces mortalities we could look at a confidence interval (here calculated using the bootstrap method).

# A bootstrap analysis of the reduction of deaths due to handwashing
boot_mean_diff = []
for i in range(3000):
    boot_before = before_proportion.sample(replace=True,n=len(before_proportion))
    boot_after = after_proportion.sample(replace=True,n=len(after_proportion))
    boot_mean_diff.append(boot_after.mean()-boot_before.mean())

# Calculating a 95% confidence interval from boot_mean_diff 
confidence_interval = pd.Series(boot_mean_diff).quantile([0.025, 0.975] )
confidence_interval

0.025 -0.101156
0.975 -0.066840

Conclusion

So handwashing reduced the proportion of deaths by between 6.7 and 10 percentage points, according to a 95% confidence interval. All in all, it would seem that Semmelweis had solid evidence that handwashing was a simple but highly effective procedure that could save many lives.

# The data Semmelweis collected points to that:
doctors_should_wash_their_hands = True