Markus Eyting
@meyting.bsky.social
Discrimination, Health, Individual Information Processing & Belief Formation
meyting.com
meyting.com
Interestingly, the protective effect was much stronger in women than in men (for men, the effect is statistically insignificant).
Future studies should investigate why!
Future studies should investigate why!
April 2, 2025 at 4:41 PM
Interestingly, the protective effect was much stronger in women than in men (for men, the effect is statistically insignificant).
Future studies should investigate why!
Future studies should investigate why!
What do we find?
Increase in vaccination uptake at the cutoff:
- 0.01% vaccination for those just too old
- 47.2% vaccination for those just young enough
Receiving the vaccine reduced dementia risk by 3.5 percentage points (95% CI: 0.6 – 7.1, p=0.019), i.e. ~20%, over 7 years.
Increase in vaccination uptake at the cutoff:
- 0.01% vaccination for those just too old
- 47.2% vaccination for those just young enough
Receiving the vaccine reduced dementia risk by 3.5 percentage points (95% CI: 0.6 – 7.1, p=0.019), i.e. ~20%, over 7 years.
April 2, 2025 at 4:41 PM
What do we find?
Increase in vaccination uptake at the cutoff:
- 0.01% vaccination for those just too old
- 47.2% vaccination for those just young enough
Receiving the vaccine reduced dementia risk by 3.5 percentage points (95% CI: 0.6 – 7.1, p=0.019), i.e. ~20%, over 7 years.
Increase in vaccination uptake at the cutoff:
- 0.01% vaccination for those just too old
- 47.2% vaccination for those just young enough
Receiving the vaccine reduced dementia risk by 3.5 percentage points (95% CI: 0.6 – 7.1, p=0.019), i.e. ~20%, over 7 years.
Why do economists study this?
This was a perfect setting for combining medical data and econometric methods! Policy evaluation of large public health intervention is rarely possible, but here was a unique chance to learn something causal about a vaccine policy at a large scale.
This was a perfect setting for combining medical data and econometric methods! Policy evaluation of large public health intervention is rarely possible, but here was a unique chance to learn something causal about a vaccine policy at a large scale.
April 2, 2025 at 4:41 PM
Why do economists study this?
This was a perfect setting for combining medical data and econometric methods! Policy evaluation of large public health intervention is rarely possible, but here was a unique chance to learn something causal about a vaccine policy at a large scale.
This was a perfect setting for combining medical data and econometric methods! Policy evaluation of large public health intervention is rarely possible, but here was a unique chance to learn something causal about a vaccine policy at a large scale.
What did we do?
We used a natural experiment in Wales where shingles vaccine (Zostavax) eligibility was based on an birthdate cutoff, separating eligible and ineligible cohorts. This gave us a great RDD setting to causally estimate its effect on dementia risk.
We used a natural experiment in Wales where shingles vaccine (Zostavax) eligibility was based on an birthdate cutoff, separating eligible and ineligible cohorts. This gave us a great RDD setting to causally estimate its effect on dementia risk.
April 2, 2025 at 4:41 PM
What did we do?
We used a natural experiment in Wales where shingles vaccine (Zostavax) eligibility was based on an birthdate cutoff, separating eligible and ineligible cohorts. This gave us a great RDD setting to causally estimate its effect on dementia risk.
We used a natural experiment in Wales where shingles vaccine (Zostavax) eligibility was based on an birthdate cutoff, separating eligible and ineligible cohorts. This gave us a great RDD setting to causally estimate its effect on dementia risk.