Indications are starting to emerge that the answer to the question may actually be no.
Previously mentioned one analysis which found a weak statistical correlation between weaker lockdown requirements and lower infection rate. The study found no correlation between the date that states started releasing the lockdown restrictions and subsequent infection rates.
The rate of infections accelerates rapidly and then hits an inflection point where the rate of infections either plateaus or the rate slows dramatically.
The following study suggests the lockdowns have no correlation to when the infection rates hit that transition point. In fact, the inflection point normally is reached before the lockdowns could have had any impact.
10/4/20 – National Review – Stats Hold a Surprise: Lockdowns May Have Had Little Effect on Covid-19 Spread –
Authors pulled the daily infection rate for 13 states and graphed the data on a logarithmic scale. Seeing infections on a log scale makes it easier to see trends. There are visible transitions in every state from rapid acceleration to a flattened or greatly reduced infection rate.
Authors then noted the date each state implement a lockdown; two did not do so at all.
Each graph with a lockdown also notes the 10 day point after the lockdown. This is when there should be a change in the curve because of the drop in infection starting the next day, plus symptoms developing in average of six days, allowing a day or two to get to the doctor and another day or two to get testing. Authors marked on each graph where there is a clear transition from rapid acceleration to flattened infection rate.
(By the way, a person might suggest stretching the timeline when the shutdowns would be expected to affect infection rates. For example, allow another day or two for most people to develop symptoms instead of the average of 6 days. Add another day or two for getting to the doctor. Allow 4 or 6 days for test results instead of 1 or 2. Stretching the time when the lockdowns would affect infection rates would even further undercut the value of any lockdown.)
The point where the death rate hit five per million people is also noted. This is a way to provide another reference point for each state to allow for variations of fluctuations in speed or accuracy of testing results.
The results for all 13 states clearly show a point at which the rapid acceleration transitioned either to a slow acceleration or flat plateau. This happened even in two states that did not implement lockdown, namely Arkansas and Iowa.
Look at the graphs in the article and you’ll see the following results:
Infection rate transitioned from accelerating to flat or slower before the 10 day point at which the lockdowns would have any impact, thus the lockdowns did not cause the slowdown:
- New York
- New Jersey
Infection rate transitioned before lockdown was imposed, which means it is impossible the lockdown had any impact in transition of infection rate:
- District of Columbia
Infection rate transitioned about 10 days after the lockdown was imposed, which means the lockdown may have had an impact on the infection rate:
Infection rate transitioned without lockdown and had about the same time in advance of the five deaths per million point and somewhere in the same time as the other states:
My summary of those results:
- The infection rate slowed in three states in advance of the lockdown being imposed.
- Infection rate slowed in seven states before the lockdown would have had any impact on the reported infection rate.
- Infection rate slowed in two states without lockdown in roughly the same time as the infection rate slowed in the other states.
- Infection rate slowed in one state at about the time the lockdown would have been expected to show a change in infection rate.
In other words, in 10 of the 13 states the lockdown had no impact on slowing the infection rate. In 2 states, the infection curve looks somewhat similar to the other states, which suggests the lockdowns did nothing.
Only in one state, California, was there a correlation between infection rates slowing and the 10 day point after lockdown was imposed. This very well could have been coincidence. In other words a lucky coincidence of the decision to impose lockdown corresponding to 10 days or so before the infection rate would have otherwise transitioned. It is also possible that California is the only state where the lockdowns actually had any impact at all on slowing the infection rate.
So the hypothesis of the study is that the lockdowns had no effect on slowing infection rate.
The author’s conclusion, which I will quote:
“The evidence suggests, then, that the sweeping, mandated lockdowns that followed voluntary responses exacted a great cost, with little effect on transmission. We can’t change the past, but we should avoid making the same mistake again.”
Please, check out the graphs for yourself. If you can see any indication in the graphs that the lockdowns did any good, any indication at all, please let me know.
It is well past time to open the economy and restore economic, political, and religious freedom.
We ought not lock down the economy again.