A vaccine’s efficacy is based on how many people who got vaccinated developed the disease compared to people who got a placebo (a dummy vaccine).
Let’s take the case of Pfizer, whose trials were conducted in the US on about 44,000 people.
22,000 were given a Pfizer vaccine (V-group), while another 22,000 were given a placebo (P-group).
These 44,000 people then continued to live their lives as normal, and after 28 days, there were 8 confirmed cases of COVID in the V-group and 162 in the P-group.
To calculate what % of V-group people got COVID, we divide 8 by 22,000 and multiply by 100 to get 0.036%.
Similarly, % of the P-group people who got COVID is 162 divided by 22,000 and multiplied by 100 = 0.74%
If you divide 0.036 by 0.74 and multiply it by 100, you get 4.86%, i.e., 5% approx.
Now 100% — 5% = 95%, and that is the efficacy of the Pfizer vaccine.
Since the circumstances of the people in the V-group and P-group may differ, this outcome can’t be said to have 100% confidence.
Vaccine effectiveness measures how well vaccines work in the real world.
While the trials are conducted on significant sample numbers (44,000 in the case of Pfizer), they can’t be a perfect representation of the whole population.
Therefore, efficacy is a less robust metric than effectiveness.
But to measure the effectiveness of a vaccine for a problem like COVID is a mammoth task and may take months/years.
This is because to measure the effectiveness, a significant part (comprising different races, age groups, locations, health conditions, etc.) of the world population will have to take the vaccine.
Only after observing these huge populations and populations of those who didn’t get the vaccine, over time, can we comment on the effectiveness of any COVID vaccine.
