133 out of 178 that is over 75% countries issued a lockdown at the cost of billions of dollars in GDP.

However, how successful has a lockdown been in reducing the rate of increase of cases?

178 countries have been taken into consideration for this study. A Lockdown Restriction Index (LRI) is defined by taking into consideration data points from Oxford’s Coronavirus Government Response Tracker.

The LRI has 4 values which can be defines as :

0 — no measures

1 — recommend not leaving house

2 — require not leaving house with exceptions for grocery shopping, daily exercise and ‘essential’ trips

3 — require not leaving house with minimal exceptions (eg allowed to leave once a week, or only one person can leave at a time, etc)

In this article,estimates are made on the ‘Effectiveness’ of Lockdowns is computed for Lockdowns with LRI greater than and equal to 2.

**Sample Selection**

The 50 countries with the highest population and the 50 countries with the highest Confirmed COVID 19 Case Count were considered for this study. The Sample set of countries was divided into 3 subsets:

1. **Most Affected Countries :**The countries that are in the list of 50 countries with the highest case count but not in 50 countries with highest population

2. **Neutrally Affected Countries** : The countries that are in the list of 50 countries with the highest case count and in 50 countries with highest population

3. **Least Affected Countries** : The countries that are not in the list of 50 countries with the highest case count but in 50 countries with highest population

**Method**

To compare the effectiveness of lockdown, first one needs to be able to compare all countries at a same scale.

Mexico’s case count of 331,298 cases with a population of 12.6 crores cannot be compared to Spain’s case count of 307,335 with a population of 4.7 crores.Even though the case count for Mexico is higher % of population infected is much lesser.

Hence the metric Cases per Million of population for different countries was calculated as follows:

The next step is to compare the changes in Lockdown Restriction Index (LRI). In the plot below depicts the cases per million on the y axis and LRI using the secondary y axis for India.

The slope of the Cases per Million curve denotes the rate at which cases are increasing.

If lockdowns were successful the slope should have decreased after the lockdown began. Since, 14 days is the incubation period for COVID 19 according to WHO, any cases that were contracted before the lockdown began would be confirmed in the first 14 days of lockdown. Hence, in order to calculate effectiveness we compare the slope of the curve on the day of the lockdown and 14 days later,

In the above picture, the slope has evidently increased, which implies that the rate of increase of cases has increased even after lockdown measures were put in place.

## Computing the Effectiveness of a Lockdown

The slope denotes the rate at which Cases per Million is increasing, therefore the % decrease in the slope is a clear indicator of how effective the lockdown has been.

The effectiveness of a lockdown is calculated as follows:

Effectiveness Index is nothing but the % decrease in slope.

‘+X’ Effectiveness Index implies, the rate of increase of cases was reduced by X% and hence the lockdown was effective

‘ –X’ Effectiveness Index value implies, the rate of increase of cases was increased by X% and hence the lockdown was ineffective

**Observations**

The highest % of countries that did not have a lockdown belong to the Least Affected subset, which implies that imposing a lockdown, does not necessarily mean that countries would be successful in curbing the spread of the virus.

Let’s take a look at the % of countries the lockdown was successful for in different sub-groups.

It can be observed that,

- In the total set of countries lockdown with LRI 3 was able to decrease the rate of increase of cases for 25% of the countries.
- In the total set of countries lockdown with LRI 2 decrease the rate of increase of cases 23.2% of the countries.

Hence, in conclusion:

It was observed that imposing a lockdown does not necessarily imply that the rate of increase of cases will go down or that the curve will flatten.

A Lockdown that require not leaving house with exceptions for grocery shopping, daily exercise and ‘essential’ trips is only likely to be able to flatten the curve 23% of the time.

A Lockdown that require not leaving house with minimal exceptions (eg allowed to leave once a week, or only one person can leave at a time, etc) is only likely to be able to flatten the curve 25% of the times

**Data Sources :**

- Oxford’s Coronavirus Government Response Tracker
- Novel Coronavirus (COVID-19) Cases, provided by John Hopkins University CSSE
- United Nations, World Population Prospects

The above conclusions are subject to interpretation and depend on the data source we have worked with.