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Shift Drug Policy from Criminal to Health Approach

Grade B β€” Moderate Evidence

Decriminalize personal drug use, redirect enforcement budget to treatment. Based on Portugal (2001).

Rank #9 of 22 policies

Welfare Score
+39
Causal Confidence
70%
Policy Impact
57%
BH Average
77%

πŸ“Š Bradford Hill Criteria Scores

Temporality100%
Plausibility100%
Strength of Association98%
Coherence95%
Analogy85%
Consistency78%
Biological Gradient66%
Specificity42%
Experiment25%

πŸ’₯ Impact Breakdown

Income Effect
+5%
Health Effect
+35%
Combined Welfare
+39

πŸ§ͺ Natural Experiments

Real-world before/after data from jurisdictions that implemented this policy.

Portugal β€” Drug Decriminalization

Intervention year: 2001 Β· Decriminalized personal possession of all drugs; shifted resources to treatment

Drug-Induced Deaths
-70.4%
p=<0.001
HIV Diagnoses Among Drug Users
-73.9%
p=<0.001
Drug-Induced Deaths(deaths per million population)
-228572001 β€” Policy enacted199520192001
HIV Diagnoses Among Drug Users(new cases per year)
-957371.6k2001 β€” Policy enacted199620152001
Sources: EMCDDA Statistical Bulletin (European drug report) Β· Hughes & Stevens (2010) British Journal of Criminology Β· Greenwald (2009) Cato Institute white paper

Switzerland β€” Supervised Drug Injection Facilities

Intervention year: 1986 Β· Opened supervised injection rooms; heroin-assisted treatment (HAT) from 1994; 4-pillar drug policy

Drug Overdose Deaths
+24.2%
p=0.912
New HIV Infections Among Drug Users
-75.9%
p=<0.001
Drug Overdose Deaths(deaths per year)
882694491986 β€” Policy enacted198520181986
New HIV Infections Among Drug Users(new cases per year)
-1328401.8k1986 β€” Policy enacted198520151986
Sources: Swiss Federal Office of Public Health Β· EMCDDA Harm Reduction reports Β· Nordt & Stohler (2006) Lancet

Uruguay β€” Cannabis Legalization and Regulation

Intervention year: 2013 Β· First country to fully legalize cannabis production, sale, and consumption under state regulation

Cannabis Use Prevalence (15-65 age)
+48.5%
p=0.002
Drug-Related Arrests
-37.3%
p=<0.001
Cannabis Use Prevalence (15-65 age)(% of population)
58112013 β€” Policy enacted200620182013
Drug-Related Arrests(arrests per year)
3.3k6.3k9.3k2013 β€” Policy enacted201020172013
Sources: Junta Nacional de Drogas (Uruguay) Β· Laqueur et al (2020) International Journal of Drug Policy Β· Global Drug Policy Observatory

🌍 Drug Policy by Country

How countries compare on this policy domain. The US row is highlighted.

CountryApproachDrug Deaths/100KIncarceration/100KTreatment Access
Singaporeprohibitionist0.118130%
Japanprohibitionist0.23835%
Portugaldecriminalization0.311175%
Czech Republicdecriminalization0.518158%
Uruguaylegalization1.232240%
Switzerlandharm-reduction1.57572%
Netherlandsharm-reduction1.85968%
New Zealandmixed1.916555%
Germanyharm-reduction2.26762%
Canadamixed5.210455%
Norwayharm-reduction5.85665%
Australiamixed6.816050%
United Kingdomprohibitionist7.612952%
Swedenprohibitionist9.35745%
United Statesprohibitionist32.453128%

πŸ“‹ Policy Details

Type
regulation
Category
health
Recommendation
implement
Current Status
US spends $40B/yr on enforcement; 1.5M arrests/yr; overdose deaths at record highs
Recommended Target
Decriminalize personal use, redirect enforcement budget to treatment
Rationale

Portugal decriminalized in 2001: drug deaths dropped 80%, HIV among users dropped 90%, treatment uptake tripled. US spends $40B/yr on drug enforcement with zero measurable reduction in drug deaths (r=0.026). Czech Republic, Switzerland, Netherlands show similar results.

Blocking Factors
political opposition

πŸ”¬ Evidence Assessment: Bradford Hill Criteria

The Bradford Hill criteria are nine principles used to establish evidence of a causal relationship between a policy intervention and its outcomes. Originally developed for epidemiology (1965), they provide a structured framework for evaluating whether an observed association is truly causal. Each criterion is scored from 0 to 1.

Strength of Association98%

How large is the association between the policy and the outcome? Larger effect sizes increase confidence in causation.

Consistency78%

Has the relationship been observed across different populations, settings, and times? Replication strengthens causal claims.

Temporality100%

Does the policy change precede the outcome change? Temporal ordering is a necessary condition for causation.

Biological Gradient66%

Is there a dose-response relationship? More of the policy leads to more of the effect? Gradients support causation.

Experiment25%

Is there evidence from randomized controlled trials or natural experiments? Experimental evidence is the gold standard.

Plausibility100%

Is there a plausible mechanism explaining how the policy causes the outcome? Mechanistic understanding increases confidence.

Coherence95%

Does the causal interpretation fit with existing knowledge? The relationship should not contradict established facts.

Analogy85%

Are there analogous policies that have produced similar effects? Similar interventions with known effects support the claim.

Specificity42%

Is the effect specific to this policy rather than a general phenomenon? Specific associations are more likely causal.

How is the Causal Confidence Score calculated?

The Causal Confidence Score (CCS) of 70% is a weighted average of the nine Bradford Hill criteria. Experiment and temporality receive higher weights since they provide the strongest evidence for causation. The CCS is then combined with the estimated effect magnitude to produce the Policy Impact Score (PIS) of 57%.

See the Optimal Policy Generator paper for full methodology.

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Analysis: Β· Optimitron OPG

Optimitron β€” The Evidence-Based Earth Optimization Game