The problem with churn in Google Analytics is, that it does not "forget" a user after a certain period (often month). So if you try to combine New Users vs. Users, you can have 100 New Users and 500 total Users in one month and another month 0 New Users but 600 total Users. Because those Users could have visited your site 2 years ago.
Another effect is, that you can have 2 months in a row 500 total Users and no New User. This would be a churn of 0 %. But 50 users in that month could have churned and 50 one-year-inactive users might have come back again. Resulting in 10 % churn. And you can not detect this.
This fact makes it an unreliable source of data. It could be useful in a way, but you will never get the real churn / churn rate out of Google Analytics in their report.
Retention in Cohort analysis only works with new users in the period you are analyzing. Therefore if you see a retention of 5 % from last month, it means that only 5 of 100 new visitors in that month came back again during that month. Is it 95 % churn? No. It does not take into account that you still have 500 loyal customers coming to your site every day.
The calculation and negative numbers
If you still want to look at GA data to come up with churn rate, there are some fixes to your calculation. The monthly change is often negative. In your calculations (3rd row), you have only absolute values. Monthly CHANGE is
current Users - last month Users.
The churn is calculated as
New Users - CHANGE. If CHANGE is negative, as in the first column, you end up with
31124 -- 2851 = 31124 + 2851 = 33975. In last column, number of churned users is -4964. This value can be negative, because of the effect I desrcibed in first paragraph, where users from previous months are not counted as New Users. They churned in previous months but now came back.
And finally the kind-of-churn rate is calculated as
current month CHURN / previous month Users and then multiply it with 100 to have nice percentages. Here you have corrected calculations:
MONTH May-19 Jun-19 Jul-19 Aug-19 Sep-19 Oct-19 Nov-19 Dec-19 Jan-20 Feb-20 Mar-20
USERS 99616 96765 97627 96141 94983 86698 78381 73789 65822 67473 103818
CHANGE NA -2851 862 -1486 -1158 -8285 -8317 -4592 -7967 1651 36345
NEW 34263 31124 33676 33381 33889 20531 14345 10840 8811 13535 31381
CHURN NA 33975 32814 34867 35047 28816 22662 15432 16778 11884 -4964
RATE NA 34,11 33,91 35,71 36,45 30,34 26,14 19,69 22,74 18,05 -7,36
To calculate real churn, follow this article but you have to use Google Analytics API to download the data and then do a nontrivial calculations in SQL database.