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Related: Aligning Incentives | Investor Materials | Academic Paper
Incentive Alignment Bonds represent a new class of financial instrument, distinct from Social Impact Bonds, lobbying, or campaign finance, designed to systematically align politicians’ career incentives with measurable public goods. The three-layer architecture described here (scoring, electoral support, post-office benefits) provides a legal template that could apply to any global coordination problem: climate change, nuclear disarmament, pandemic preparedness, and beyond.
Here’s a fun puzzle: You know how to save millions of lives. You can measure exactly how many. You have the money. And governments still don’t do it.
This isn’t because politicians are evil. It’s because the system is built so that:
- Politicians maximize reelection, status, and post-office careers, not “humans continuing to exist”
- Bureaucracies maximize budget, stability, and turf, not “speed of cures”
- Lobbyists maximize client profits, not “global welfare”
You don’t fix this with awareness campaigns. You’ve been “raising awareness” for decades and everyone is still dying. You don’t fix it with white papers. Politicians use white papers to stabilize wobbly tables. You don’t fix it by hoping for philosopher-kings. Plato tried that. It didn’t work.
You fix it by changing what “self-interest” points at.
This chapter describes a mechanism to legally bribe politicians into doing the right thing:
Incentive Alignment Bonds (IABs) – a way to pay for better governance without technically paying politicians, giving money to governments, or going to prison.
The Core Problem: Good Ideas Die in Committee
You’ve seen the numbers by now:
- Redirecting 1% of global military spending into pragmatic trials could save hundreds of millions of lives and generate trillions in economic value.
The 1% Treaty isn’t constrained by physics, biology, or money. It’s constrained by politics, which is like being constrained by your dog’s opinion on quantum mechanics except your dog can veto legislation.
No politician wants to be the one who “cut the military.” Even by 1%. Even if that 1% cures cancer. The attack ads write themselves: “Senator Johnson voted to WEAKEN AMERICA. His opponent didn’t. Vote for literally anyone else.”
From a public choice perspective, the 1% Treaty is a classic public good:
- Enormous global benefit
- Concentrated local political pain
- Benefits arrive in 10 years; the attack ads arrive tomorrow
The system does exactly what it’s incentivized to do. It’s not broken. It’s working perfectly. The problem is what it’s optimizing for.
If you want different outcomes, you need different incentives. Wishing very hard doesn’t count.
What You Need: Legal Bribery That Isn’t Technically Bribery
Imagine you could say to every politician on Earth:
“If you vote for a 1%-style reform and your country actually funds it, we will:
- upgrade your international reputation (you’ll get invited to better parties),
- boost your reelection odds (independent campaigns will favor you),
- and make your post-office career prospects significantly better than your rivals’ (Goldman Sachs boards, prestigious fellowships, that sort of thing).”
No backroom deals. No suitcases of cash. No prison.
No money to you personally, and no money to government budgets. What you get is external legitimacy, electoral support, and cushy retirement gigs. The things politicians actually optimize for.
Just a standing, public, announced-in-advance rule:
“Do this objectively good thing, and the world will systematically reward you.”
This is the job of Incentive Alignment Bonds. It’s bribery, except legal, transparent, and pointed at saving lives instead of ruining them.
Definition: What Are Incentive Alignment Bonds?
Incentive Alignment Bonds (IABs) are a new class of financial instruments designed to:
- Reward investors with returns proportional to public-good funding achieved
- Reward politicians with electoral support and career benefits based on their voting record for public-good policies
- Fund the public good itself from the policy outcome (self-sustaining)
The key innovation: IABs align both investors and politicians with public-good outcomes through a single instrument. Investors provide capital to pass the policy. Politicians get career benefits for supporting it. The policy outcome funds everything.
This is mechanism design applied to governance, using the tools economists developed for auctions and markets to solve political economy problems. The insight is that politicians respond to incentives like everyone else; the question is whether those incentives point toward saving lives or toward pleasing lobbies. IABs change what the incentives point at.
They are not charity. (Charity doesn’t work at scale.) They are not lobbying. (That’s already taken.) They are not “paying politicians.” (That’s illegal, and also already taken.)
They are:
A way to make investors and politicians cooperate on public goods by appealing to the only thing they respond to: self-interest.
How IABs Differ from Social Impact Bonds
| Who’s rewarded |
Service providers (nonprofits) |
Politicians AND investors |
| What’s measured |
Service delivery outcomes |
Policy adoption and funding flows |
| Attribution |
Easy (one provider, one program) |
Based on votes and $ contributed |
| Scale |
City/program level |
National/global |
| Funding source |
External (government pays for outcomes) |
Self-funding (policy outcome funds returns) |
Think of IABs as:
- Social impact bonds, but rewarding politicians and investors instead of service providers.
- Advance Market Commitments, but aimed at policies instead of vaccines.
- Bribery, but legal, transparent, and aimed at reducing human suffering instead of increasing it.
How Incentive Alignment Bonds Work – The Simple Version
Let’s walk through the basic structure in four steps.
Step 1: Define a Measurable Outcome
You choose an outcome that:
- Is measurable with agreed methods.
- Is directly attributable to policy actions.
- Matters at scale.
Measure funding flows, not downstream health outcomes. Health benefits are global and diffuse - you can’t attribute a cure discovered via a global framework for ubiquitous pragmatic trials to any specific country’s funding. But you CAN measure:
- % of military spending redirected to the 1% Treaty Fund
- Total $ contributed by each country
- Politician votes on treaty passage/expansion
For the 1% Treaty, the measurable outcomes are:
$ flowing to the 1% Treaty Fund and % of military spending redirected - not health outcomes, which are global and unattributable.
Health improvements are the justification for the policy. Funding flows are the metric for scoring, because they’re what politicians can actually control and be held accountable for.
Step 2: Raise Capital
Foundations, impact investors, development banks, and perhaps even regular investors buy Incentive Alignment Bonds.
- The capital raised is held by an independent entity (a trust, fund, or special-purpose vehicle).
- Buyers know: “This bond pays out if and only if objectively measured public-good targets are hit.”
This is structurally similar to:
- Green bonds that pay based on environmental performance.
- Catastrophe bonds that pay based on disaster events.
- Social impact bonds that pay based on outcome metrics.
Step 3: Fund Outcomes, Reward Politicians Indirectly
When a politician:
- Votes for a 1%-style policy (e.g., reallocating 1% of the military budget to pragmatic clinical trials), and
- The policy passes and funding actually flows to the treaty fund,
the mechanism triggers indirect rewards:
- Public Good Scores rise (published by independent rating organizations)
- Electoral support increases (independent campaigns favor high-scorers)
- Post-office opportunities unlock (fellowships, advisory boards, speaking circuits)
The core principle:
No money flows to politicians or governments. What flows is reputation, electoral advantage, and career advancement.
This avoids the “that’s just bribery” problem entirely. Nobody’s getting paid. They’re just getting credit for doing their job well, in ways that happen to benefit their careers.
Step 4: Make Politicians Care (Without Paying Them)
The magic is that supporting 1%-equivalent policies translates directly into political benefits.
Because:
Citizens who see their country funding cures credit the politicians who made it happen (this is called “democracy working correctly”).
Independent rating systems give politicians a Public Good Score based on:
- whether they voted for 1%-equivalent policies, and
- whether funding actually flowed to the treaty fund.
Media, NGOs, and external coalitions:
- highlight high-score politicians,
- spend more on independent campaign support for them,
- invite them into prestigious roles after office.
No private deals. No “you personally get money.” Just a standing rule:
“If you support this kind of high-impact policy and it works, the world will systematically make your political life easier, your legacy better, and your post-office prospects brighter.”
That is public choice-compatible incentive alignment.
In mechanism design terms: the politician’s utility function is roughly:
U = P(reelection) + career advancement + post-office income + status/legacy
IABs make supporting 1%-equivalent policies strictly increase all four terms. No altruism required. The mechanism is incentive-compatible: the privately optimal action (maximize personal payoff) and the socially optimal action (support policies that reduce suffering) become identical.
4a. The Three-Layer Architecture (How to Not Go to Prison)
The previous section described the what. This section describes the how, in enough detail that a lawyer could implement it without anyone getting indicted.
You cannot legally say “support Bill #XYZ123 and get paid.” That’s bribery. People go to prison for that. It’s also inefficient because you’d have to bribe every politician individually, which doesn’t scale.
But you can create a system where politicians who support a class of pro-social policies systematically get more electoral support, better reputations, and better post-office careers. The trick is: rule-based, ex-ante, universal mechanisms. No targeting individuals. No secret deals. Just standing rules that happen to reward saving lives.
Here’s the architecture:
Layer A: Outcome and Policy Scoring (Data Only)
Create an independent scoring system that assigns each politician a Public Good Score based on their policy actions (not downstream health outcomes, which are global and unattributable to any single country):
- Votes in favor of “1%-equivalent” measures
- Sponsorship of such bills
- Public commitments and campaign positions
- Blocking harmful reversals
- Actual funding flows resulting from their votes
Critical design choice: Don’t tie scores to “The 1% Treaty” specifically. Define a policy class:
“Policies that reallocate ≥1% of national military spending into independently governed pragmatic clinical trials with open data and outcome-based evaluation.”
Any politician supporting any policy matching this pattern gets credit. This avoids the “paying for your specific bill” problem entirely.
The scoring system is:
- Public (anyone can see the methodology and data)
- Rules-based (no discretion, no case-by-case decisions)
- Non-partisan (applies equally to all parties and ideologies)
Layer B: Electoral and Reputational Benefits (Separate Actors)
Independent entities, legally separate from the scoring system, can commit ex ante to favor high-scoring politicians:
501(c)(4) organizations and PACs can:
- Spend more on independent ads and voter turnout for higher-scoring candidates
- Run comparative campaigns: “Senator Smith scored 23 on the Public Good Index. His opponent scored 78. One of them wants you to keep dying.”
NGOs and media can:
- Publish annual rankings of politicians by Public Good Score
- Feature high-scorers at conferences (politicians love conferences)
- Create awards (politicians love awards even more than conferences)
The goal is to make the Public Good Score as influential as existing trusted benchmarks:
- Freedom House scores shape how democracies are perceived globally
- Transparency International rankings affect investment and diplomatic relationships
- Credit ratings (Moody’s, S&P) directly constrain sovereign borrowing costs
Moody’s can downgrade a country’s credit rating and suddenly their borrowing costs go up. That’s power. If the Public Good Score achieves similar salience:
- High score → respect, invitations, soft power, legacy, better book deals
- Low score → reputational cost, fewer opportunities, awkward questions at dinner parties
That’s a direct self-interest lever that requires no altruism to activate. Politicians don’t need to become better people. They just need to notice which direction the incentives are pointing.
Key constraints:
- No private deals (“we promise you specifically”)
- Just standing rules (“we support any candidate with Score ≥ S”)
- All commitments made publicly and in advance
This is exactly how NRA grades, League of Conservation Voters scores, and Chamber of Commerce ratings already shape political behavior. The difference is the metric: instead of “did you vote for our narrow interest,” it’s “did you vote for policies that measurably reduced human suffering.”
Layer C: Post-Office Career Benefits (The Goldman Sachs Board Problem)
After politicians leave office, they want prestigious jobs. Board seats. Fellowships. Speaking fees. This is called “the revolving door” and it’s usually pointed at whoever paid the most lobbyists.
You can point it somewhere else.
Foundations, think tanks, and impact funds can establish:
“Eligibility for certain fellowships, advisory roles, and governance positions is restricted to former leaders who: 1. Voted for 1%-equivalent policies during their tenure, and 2. Maintained a Public Good Score above threshold X.”
Politicians know this rule in advance. Their calculation becomes:
- Support 1%-style reform → prestigious fellowships, advisory boards, speaking circuits, book deals
- Oppose it → you can still get a job, but it won’t be as good, and you’ll have to explain why you voted against curing diseases
No one is paid for a specific vote. There’s just a standing rule that systematically advantages leaders who governed well by objective metrics. It’s the revolving door, except spinning toward “saved lives” instead of “military contractor profits.”
Legal Entity Separation
The three layers must be housed in legally distinct entities:
| Scoring |
501(c)(3) or independent research org |
Fund metrics, dashboards, public data |
Support/oppose candidates |
| Electoral |
501(c)(4), PAC, or Super PAC |
Independent expenditures favoring high-scorers |
Coordinate with candidates |
| Post-office |
Private foundations, think tanks |
Set eligibility criteria for positions |
Condition grants on specific votes |
This separation is not a loophole; it’s how the system maintains legitimacy. Each layer does what it’s legally permitted to do, and the combined effect is that supporting 1%-equivalent policies becomes the utility-maximizing choice for rational politicians.
4b. A Worked Example: How Senator Smith Votes Yes on the 1% Treaty
Abstract mechanisms are great for economists and terrible for everyone else. Here’s how IABs actually work, using a US senator deciding how to vote on the 1% Treaty as the example.
The Primary Metrics We’re Maximizing
The whole point of this system is to increase two numbers:
- % of military spending reallocated (starts at 1%, goal is expansion to 2%, 5%, 10%+)
- $ flowing to 1% Treaty Fund annually (starts at $27.2B, scales with %)
Every politician’s score is tied to their impact on these numbers. Vote to increase them? Score goes up. Vote to decrease them? Score goes down. It’s that simple.
The Politician’s Utility Function
Politicians optimize for a utility function whether they admit it or not. Here’s what it looks like:
\[
U_{politician} = \alpha \cdot P(\text{reelection}) + \beta \cdot \text{PostOfficeIncome} + \gamma \cdot \text{Status/Legacy}
\]
Where:
- \(\alpha, \beta, \gamma\) are weights (varies by politician, but all are positive)
- \(P(\text{reelection})\) = probability of winning next election
- \(\text{PostOfficeIncome}\) = expected lifetime earnings after leaving office (boards, speaking fees, fellowships)
- \(\text{Status/Legacy}\) = how history remembers you (books written, buildings named, Wikipedia length)
The IAB system makes each of these terms a function of the politician’s Public Good Score.
The Public Good Score
Each politician gets a score based on their voting record :
\[
\text{Score}_i = \text{VoteRecord}_i
\]
Where:
VoteRecord (0-100) measures how a politician voted on bills that affect funding flows:
| Increase % reallocation to the 1% Treaty Fund |
+15 points |
-15 points |
| Protect existing 1% Treaty Fund funding |
+10 points |
-10 points |
| Expand treaty to more countries |
+10 points |
-10 points |
| Cut 1% Treaty Fund funding or % |
-20 points |
+5 points |
| Procedural support (cloture, etc.) |
+5 points |
-5 points |
How Score Translates to Utility
Here’s where self-interest kicks in:
Reelection Probability:
\[
P(\text{reelection}) = P_0 + \delta \cdot (\text{Score}_i - 50) + \epsilon \cdot \text{IndependentSpending}_i
\]
Independent health advocacy PACs commit to spending proportional to score:
\[
\text{IndependentSpending}_i = \begin{cases}
+\$2M & \text{if Score} \geq 70 \\
+\$500K & \text{if } 60 \leq \text{Score} < 70 \\
\$0 & \text{if } 50 \leq \text{Score} < 60 \\
-\$500K \text{ (to opponent)} & \text{if } 40 \leq \text{Score} < 50 \\
-\$2M \text{ (to opponent)} & \text{if Score} < 40
\end{cases}
\]
Post-Office Income:
\[
\text{PostOfficeEligibility} = \begin{cases}
\text{Tier 1 (WHO boards, Aspen fellowships)} & \text{if Score} \geq 75 \\
\text{Tier 2 (Think tank positions)} & \text{if } 60 \leq \text{Score} < 75 \\
\text{Tier 3 (Standard revolving door)} & \text{if Score} < 60
\end{cases}
\]
Expected post-office income by tier:
| Tier 1 |
$500K+ |
High |
WHO Advisory Board, Aspen Health Fellowship, Nobel committee |
| Tier 2 |
$200-400K |
Medium |
Brookings, RAND, university chairs |
| Tier 3 |
$150-300K |
Low |
Defense contractor boards, lobbying firms |
The Setup
VICTORY Incentive Alignment Bonds have raised $1B from investors who want 272% returns. That money has funded:
- A referendum showing 70% of Americans support reallocating 1% of military spending to pragmatic clinical trials
- A lobbying campaign that’s converted several military contractors (they did the math on their own mortality)
- The Public Good Scoring system described above, tracking every federal legislator
Senator Smith (R-Texas) is up for reelection in 2026. The 1% Treaty Implementation Act is coming to a vote.
Her current stats:
- Public Good Score: 45 (below Senate median of 52)
- Current P(reelection): 55%
- Expected post-office tier: 3
- Expected post-office income: $200K/year
The Old Calculus (Without IABs)
| Attack ads: “Smith voted to WEAKEN AMERICA” |
Safe from military lobby attacks |
| Defense contractors fund opponent |
Defense contractors fund you |
| No immediate upside |
Status quo maintained |
| Benefits arrive in 10 years |
Costs arrive never |
Expected utility of No vote: \(U = 0.55 \cdot \text{Office} + \$200K/\text{year} \cdot 20\text{yrs} + \text{Medium Legacy}\)
Result: Vote no. Obviously.
The New Calculus (With IABs)
If Smith votes YES:
- VoteRecord: +15 points (major treaty vote)
- New Score: 45 + 15 = 60 → jumps to 72 with multiplier for being early supporter
- P(reelection): 55% → 62% (score boost + $500K independent support)
- Post-office tier: 3 → 2 (with path to Tier 1 if she becomes a champion)
- Expected post-office income: $200K → $300K/year
If Smith votes NO:
- VoteRecord: -15 points
- New Score: 45 - 15 = 30
- P(reelection): 55% → 48% (score penalty + $2M goes to opponent)
- Post-office tier: Stuck at 3
- Attack ads funded: “Smith voted AGAINST the cure your family needs”
The math:
\[
\Delta U_{\text{Yes vs No}} = 0.14 \cdot \text{Office} + \$100K/\text{year} \cdot 20\text{yrs} + \text{Legacy Boost}
\]
That’s a +14 percentage point swing in reelection odds and +$2M in lifetime post-office earnings.
Result: Vote yes. The math changed.
What Actually Happens
- Pre-vote: Senator Smith’s staff pulls up her current Public Good Score (45). They model the yes vote: score jumps to 72, P(reelection) rises 7 points, post-office tier improves.
Lobbying meeting: The old military lobby shows up to threaten. But three major contractors have already announced support for the treaty (270% returns beat 8% returns). The threat is empty.
Campaign finance check: Her team sees that health advocacy Super PACs have committed $50M nationally to independent expenditures. At her projected score of 72, she qualifies for $2M in support. A no vote means that $2M goes to her opponent instead.
Constituent mail: 70% of Texans voted yes in the referendum. Voting against that is explaining to voters why you think they’re wrong about not wanting to die.
The vote: Smith votes yes. So do 67 other senators. The treaty passes.
Post-Treaty: The Numbers
For Senator Smith:
| Public Good Score |
45 |
78 |
| P(reelection) |
55% |
68% |
| Independent support received |
$0 |
$3M |
| Post-office tier |
3 |
1 |
| Expected post-office income |
$200K/yr |
$500K/yr |
She wins reelection by 12 points. After leaving the Senate in 2030, she joins the WHO Advisory Board and chairs the Aspen Health Initiative.
For the primary metrics:
| % military spending to the 1% Treaty Fund |
0% |
1% |
| Annual 1% Treaty Fund funding |
$0 |
$27.2B |
| Bondholder returns |
0% |
272%/year |
| Political incentive funding |
$0 |
$2.72B/year |
| Research funding |
$0 |
$21.8B/year |
For expansion (Years 3-5):
As cures emerge, public pressure builds. Politicians who supported 1% now support 2%. Their scores rise again. Politicians who opposed face primary challenges from candidates promising “I’ll vote for the cure your incumbent blocked.”
The flywheel spins. Each expansion increases the stakes, which increases the score differential, which makes voting yes even more dominant.
The Math for VICTORY Incentive Alignment Bond Investors
The investors who funded the $1B campaign see:
- Treaty passes → $27.2B/year flows to the 1% Treaty Fund
- 10% ($2.72B/year) flows to bondholders → 272% annual returns
- 10% ($2.72B/year) funds political incentive mechanisms → keeps politicians aligned
- 80% ($21.8B/year) funds actual cures → diseases start declining → public demands expansion → returns grow
Everyone’s self-interest aligned. No one was bribed. The system just made “vote for cures” and “advance career” point in the same direction.
This is not cynical. This is public choice theory. It’s only cynical if you think politicians should be motivated by pure altruism, in which case I have some bad news about the last 5,000 years of recorded history.
Why This Is Not Bribery (Legally Speaking)
At first glance, this sounds like fancy bribery. “Reward politicians when they do what you want” is pretty much the definition.
Except it’s not, for four reasons that matter to lawyers:
- No one is paid to break a duty.
- Bribery = paying an official to violate their legal or ethical obligations.
- IABs reward compliance with duties: improving population health using legal policy tools.
- “Please do your job better and we’ll tell everyone you did” is not a bribe. It’s a performance review.
- Rules are universal and ex-ante.
- The mechanism applies to all politicians and parties, openly and in advance.
- There are no secret deals, no targeting individuals, no envelopes in parking garages.
- It’s like saying “we’ll give a prize to whoever cures cancer.” That’s not bribery. That’s an incentive.
- No money goes to politicians or government budgets.
- Politicians benefit indirectly: better scores, electoral support, nicer career options.
- This is how representative democracy is supposed to work: leaders benefit when their constituents benefit.
- The mechanism just makes the connection visible and systematic.
- Scores are based on public voting records.
- No “impact oracle” needed - just public voting records from official government sources.
- Did the politician vote YES on treaty funding? That’s verifiable, ungameable, and directly attributable.
- The 10% political incentive fund flows automatically based on treasury inflows - pure math, no discretion.
Bribery corrupts alignment. (“Here’s money to screw the public.”) IABs create alignment. (“Support policies that save lives and your career benefits.”)
Why IABs Are Not Just Social Impact Bonds
People sometimes hear this and say, “We already have Social Impact Bonds.” This is like saying “we already have bicycles” when someone proposes building a railroad.
Here’s the difference (yes, it matters):
| Scale |
One city’s recidivism rate |
Whether entire countries live or die |
| Who’s incentivized |
Service providers who already wanted to help |
Politicians (the people who control everything) |
| Outcome measured |
Did 47 people complete job training? |
Did millions of people not die? |
| Purpose |
“Innovative financing” (consultant-speak for “grant with extra steps”) |
Governance technology (also consultant-speak, but accurate) |
Social Impact Bonds are pilot projects. Important! Valuable! Also: small.
Incentive Alignment Bonds are an attempt to change the rules of the game at the level where games actually get changed, which is to say, the level where politicians decide what gets funded and what dies in committee.
How This Plugs Into the 1% Treaty (The Part Where It All Comes Together)
So how does this connect to the bigger project of ending war and disease? (You’re still reading this far. Impressive.)
The 1% Treaty says:
“Let’s take 1% of global military spending and redirect it to ultra-efficient pragmatic trials, giving the world earlier access to cures and making us safer than any new weapons system could.”
Beautiful, right? Inspiring, even. Also: meaningless without a mechanism. Treaties are just PDFs with fancy letterheads unless you give countries a reason to actually follow them.
Incentive Alignment Bonds provide the missing political mechanism:
Scoring the transition. IABs create public metrics that track which politicians voted for 1%-equivalent policies and whether funding actually flowed. Politicians get credit (or blame) in a format that’s easy to communicate.
Rewarding early adopters. Politicians who move first get higher Public Good Scores. They get electoral support from independent campaigns and access to prestigious post-office opportunities. Suddenly “being the first to do the right thing” becomes “being the first to get the career benefits.”
Creating political pressure. High-performing countries get scores, coverage, and external support. Low-performing countries get awkward questions at international summits. Politicians hate awkward questions at international summits.
Aligning global and national interests. Global funders care about reducing disease and existential risk. National leaders care about reelection, reputation, and post-office careers. IABs connect these two in a legal, transparent way that makes everyone feel clever for participating.
The 1% Treaty describes the what. Incentive Alignment Bonds supply the how.
(This is the part of the presentation where the venture capitalist starts nodding.)
7a. The Two Engines: Financial and Political
If you’ve read the VICTORY Incentive Alignment Bonds chapter, you might wonder: “Are these two different things?”
No. VICTORY Incentive Alignment Bonds are the specific financial instrument that implements the IAB concept.
However, the instrument has two distinct “engines” inside it. One pays investors to provide the capital. The other pays politicians to provide the policy.
| Who’s incentivized |
Investors |
Politicians |
| What they get |
272% annual returns (money) |
Reputation, electoral support, post-office careers |
| Funding source |
10% of treaty revenue ($2.72B/year) |
10% of treaty revenue ($2.72B/year) |
| Role |
Solves the Capital Problem
Raises $1B to fund the campaign |
Solves the Political Problem
Makes politicians want to support the treaty |
The relationship is complementary:
| Pre-Treaty |
VICTORY Incentive Alignment Bonds |
Raise capital from investors to fund the campaign |
| Pre-Treaty |
IAB Mechanism |
Shows politicians that supporting the treaty improves their scores |
| Post-Treaty |
VICTORY Incentive Alignment Bonds |
Pay investors their 10% of treaty revenue forever |
| Post-Treaty |
IAB Mechanism |
Rewards politicians who maintained support and whose countries kept funding flowing |
VICTORY Incentive Alignment Bonds get investors to fund the war. The IAB mechanism gets politicians to fight it (and to keep fighting after victory).
The 80% of treaty revenue that doesn’t go to investors or political incentives? That is allocated from the 1% Treaty Fund to decentralized institutes of health (DIH) to actually fund the pragmatic clinical trials. The split is:
| Engine 1 (Investors) |
10% |
$2.72B |
Returns for funding the campaign |
| Engine 2 (Politicians) |
10% |
$2.72B |
Electoral support, post-office fellowships |
| The Mission (Research) |
80% |
$21.8B |
Actually curing diseases |
Objections and Failure Modes
No mechanism is magic. It is worth being explicit about what can go wrong.
Objection 1: “Won’t politicians game the metrics?”
Yes. Obviously. Politicians game everything. That’s what they do.
The question isn’t “will they try to game it?” The question is “is gaming it harder than just doing the right thing?”
The scoring is based on public voting records and verified funding flows, not health outcomes. To game these metrics, you’d need to:
- Falsify your own vote (impossible - it’s public record in every democracy)
- Claim you voted yes when you voted no (easily disproven)
- Pretend funding flowed when it didn’t (treasury records are public)
Votes and funding flows are among the hardest metrics to game because they’re already tracked by official government sources. The scoring system just aggregates public information.
Gaming is a risk with any metric. But votes and funding flows are orders of magnitude harder to fake than, say, self-reported ESG compliance.
Objection 2: “Isn’t this just rich people buying policy?”
This is the most important objection, so let’s take it seriously instead of hand-waving.
If IABs are just plutocracy with better marketing, they deserve to fail. Let’s see if they are.
First, the uncomfortable reality: Wealthy actors already buy policy. They do it via lobbying, revolving doors, campaign finance, and regulatory capture. The pharmaceutical industry alone spends over $300 million annually on lobbying in the United States. Defense contractors spend more. The question is not “should money influence policy?” but rather “given that money already influences policy, can we channel that influence toward measurable global welfare instead of narrow interests?”
Second, the structural safeguards:
No quid pro quo. The three-layer architecture explicitly separates scoring (data), electoral support (issue campaigns), and post-office benefits (standing eligibility rules). No one can say “vote for X, get Y.” There are only standing rules: “Any politician who supports this class of policies will score higher on this public metric, and entities that care about that metric may independently favor high-scorers.”
Universal and ex-ante rules. Every politician faces the same scoring system, announced publicly in advance. A left-wing politician who supports 1%-equivalent health policy gets the same credit as a right-wing one. The system is indifferent to party, ideology, and individual identity.
No money flows to politicians. IABs don’t pay anyone. They create scoring systems and eligibility criteria. Politicians get indirect benefits: better scores on public metrics, electoral support from independent campaigns, and eligibility for post-office positions. No cash changes hands. This is how lobbying is supposed to work; it just usually doesn’t.
The metric is suffering reduced, not interests served. Traditional influence-buying delivers policies that benefit narrow groups at diffuse public expense. IABs do the opposite: they reward policies that deliver diffuse public benefits even when narrow groups oppose them. The direction of distortion is reversed.
Third, the honest admission: Yes, wealthy people who fund IABs will have more influence over which public goods get prioritized than people who don’t fund IABs. That’s true of all philanthropy. The Gates Foundation has more influence over malaria policy than a random person who also cares about malaria. The question is whether that influence is being exercised transparently, toward measurable welfare improvements, through legal and auditable channels. IABs satisfy all three criteria in ways that traditional lobbying does not.
Objection 3: “What if politicians pocket the career rewards, then reverse the policy?”
They might. Politicians are humans, and humans have short attention spans and shorter terms.
Countermeasures:
- Score decay: Public Good Scores decline if you vote to reverse funding. Yesterday’s hero becomes today’s cautionary tale.
- Long-term metrics: Reward durability, not just one-off votes. “You voted yes once” is worth less than “you defended the funding for five years.”
- Political scorecards: Voting to cut funding tanks your Public Good Score. The same mechanism that rewarded you for supporting the policy punishes you for killing it.
You cannot prevent all backsliding. But you can make it expensive enough that it’s not the default move.
Objection 4: “Is this realistic at a global scale?”
It doesn’t have to start global. Global is the goal. Portugal is the pilot.
The path:
- One or two pilot countries adopt a limited 1%-style policy with IAB support. (Portugal, Costa Rica, maybe New Zealand - small, functional democracies with something to prove.)
- Funding flows are verified; the policy works; leaders get invited to better conferences and their scores rise.
- Other countries notice and copy what works, as they already do with credit ratings, trade agreements, and health system reforms. FOMO is a powerful force in international relations.
Credit ratings didn’t start as a global system. They started as one guy in the 1800s publishing opinions about railroad bonds. Now Moody’s can tank a country’s economy with a press release.
IABs can scale the same way: proof of concept → adoption by early movers → FOMO among laggards → new normal.
Why This Matters for Ending War and Disease
Ending war and disease is not primarily a scientific problem; it is a governance problem.
We already know:
- How to prevent many pandemics.
- How to reduce cardiovascular and infectious disease.
- How to run pragmatic trials at a fraction of current cost.
- That 1% of war budgets could transform the health landscape.
What’s missing is:
- a credible way for the public and global funders to reward governments for doing these things,
- using tools that are legal, transparent, and consistent with human self-interest.
Incentive Alignment Bonds give us a way to say:
“If you govern well by these objective metrics, the world will systematically make your political life easier, your legacy better, and your future brighter.”
That does not guarantee success. But it changes the game from “hope someone in power cares enough” to:
“Let’s build a system where caring enough is the best selfish move a leader can make.”
If ending war and disease is about anything, it is about that: reprogramming the incentive landscape so that the easiest and most rewarding path for powerful actors is the path that saves the most lives.
Incentive Alignment Bonds are one of the simplest, most scalable tools we have to do that.
Why 10%: The Scaling Engine
You might wonder: Why dedicate 10% of treaty revenue ($2.72B/year) to political incentives? Isn’t that money that could go to pragmatic clinical trials?
The answer requires understanding what we’re actually trying to do.
The Goal Isn’t a 1% Treaty. The Goal Is 100%.
The 1% treaty is the proof of concept. The endgame is redirecting most of global military spending to health. Ideally, 50%, 75%, eventually approaching 100%.
That doesn’t happen automatically. Once the 1% treaty passes:
- VICTORY Incentive Alignment Bond investors are satisfied. They’re getting 272% returns. They have no financial incentive to push for 2%, 5%, or 10%.
- Defense contractors adapt. They’ll accept 1% as a small loss, then lobby to prevent further cuts.
- Political attention fades. Once the “win” is declared, politicians move on to the next issue.
- Backlash builds. The military-industrial complex regroups. Attack ads return.
Without a mechanism for sustained political pressure, the treaty stalls at 1-2% forever.
IABs Are the Political Ratchet
The 10% IAB allocation creates something social impact bonds cannot: perpetual, compounding political incentives that only increase with treaty expansion.
| 1% |
$27.2B |
$2.72B/year |
$21.8B/year |
Politicians rewarded for passage |
| 2% |
$54B |
$5.4B/year |
$43.2B/year |
Politicians compete to expand |
| 5% |
$136B |
$13.6B/year |
$109B/year |
Defense industry pivots to health |
| 10% |
$272B |
$27.2B/year |
$218B/year |
War becomes economically obsolete |
| 25% |
$680B |
$68B/year |
$544B/year |
Superpowers compete on health |
| 50% |
$1.36T |
$136B/year |
$1.09T/year |
Global transformation |
| 100% |
$2.72T |
$272B/year |
$2.18T/year |
Full redirection achieved |
At 100% redirection, the IAB mechanism would fund $270 billion per year in political incentives. That’s more than all current global lobbying combined. It would make “support pragmatic clinical trial funding” the single most rewarded political position on Earth.
The Math Changes Everything
At 1%: “Is $2.72B/year for political incentives worth it?”
At 100%: “$270B/year in political incentives unlocks $2.16 trillion per year in funding for pragmatic clinical trials.”
The 10% isn’t a cost. It’s the engine that drives the entire expansion. Without it, you get a one-time win. With it, you get a self-reinforcing cycle that makes each expansion easier than the last.
Why VICTORY Incentive Alignment Bonds Alone Won’t Scale
VICTORY Incentive Alignment Bonds solve the initial alignment problem:
- Investors fund the campaign
- Treaty passes
- Investors get 272% returns forever
But after the 1% treaty passes:
- Investors are done. Their job was funding the campaign. Mission accomplished.
- They have no mechanism to push for expansion.
- Their returns are locked in. 2% treaty or 10% treaty, they still get 272%.
IABs solve the ongoing alignment problem:
- Politicians who pushed for 1% see their IAB-funded benefits
- They see colleagues getting rewarded for supporting treaty expansion
- They compete to push for 2%, then 5%, then 10%
- Each expansion increases IAB funding, which increases political pressure, which drives the next expansion
It’s a political ratchet that only moves in one direction: toward more pragmatic clinical trial funding.
The Alternative Is Stagnation
Without IABs, here’s the likely trajectory:
- Year 1-3: 1% treaty passes. Celebration.
- Year 4-7: Defense lobby regroups. Politicians lose interest. No expansion.
- Year 8-15: Treaty stalls at 1%. Defense spending slowly creeps back up.
- Year 16+: The 1% treaty becomes like the Paris Agreement: a nice symbol that everyone ignores.
With IABs:
- Year 1-3: 1% treaty passes. Politicians rewarded.
- Year 4-7: Politicians compete to expand to 2%. More rewards.
- Year 8-15: 5% treaty. Defense contractors pivot to health. More rewards.
- Year 16-30: 10%, 25%, 50%. War becomes economically obsolete.
- Year 50+: Full redirection. Disease becomes a solved problem.
The 10% allocation is the difference between a one-time policy win and a multi-generational transformation of human civilization.
Bottom Line
The question isn’t “Is 10% too much?”
The question is: “Is 10% enough to sustain political momentum through the inevitable backlash as military budgets face real cuts?”
Probably. But if anything, 10% might be conservative for what we’re trying to accomplish.
Summary
Incentive Alignment Bonds are a new class of financial instrument designed to solve a problem as old as governance: politicians optimize for reelection and post-office careers, not for humanity’s long-term welfare.
IABs don’t try to change human nature. They redirect it.
The core innovation:
Create scoring systems, electoral support mechanisms, and post-office career paths that make supporting public-good policies the personally optimal choice for politicians, without paying anyone directly.
How they differ from existing instruments:
| Social Impact Bonds |
Service providers |
Local programs |
IABs target politicians at scale |
| Lobbying |
Politicians (via access) |
Narrow interests |
IABs align with measurable public goods |
| Campaign finance |
Candidates |
Individual races |
IABs create universal, ex-ante rules |
| Treaties |
Governments |
Commitments |
IABs provide enforcement mechanism |
Why they matter:
They solve the political economy problem. Good policies die because concentrated losers lobby harder than diffuse beneficiaries. IABs concentrate benefits on politicians who support good policies.
They’re legal. The three-layer architecture (scoring, electoral, post-office) avoids bribery law by rewarding policy classes, not specific votes, through independent actors, with no money flowing to officials.
They scale. Start with one treaty, one country. Success creates FOMO. Other countries copy. The mechanism spreads.
They’re self-reinforcing. Each success (1% → 2% → 5%) increases IAB funding, which increases political incentives, which drives the next expansion.
They generalize. The same architecture works for climate, nuclear risk, pandemic preparedness, and any global coordination problem with measurable outcomes.
The bottom line:
We’ve known for decades that ending war and disease is technically feasible. The constraint is political will. IABs don’t create political will out of nothing; they make it the path of least resistance.
You’re not asking politicians to be saints. You’re just making “save millions of lives” and “advance my career” point in the same direction.
The rest is just self-interest doing what self-interest does.
1.
Fund, N. C. NIH pragmatic trials: Minimal funding despite 30x cost advantage.
NIH Common Fund: HCS Research Collaboratory https://commonfund.nih.gov/hcscollaboratory (2025)
The NIH Pragmatic Trials Collaboratory funds trials at **$500K for planning phase, $1M/year for implementation**—a tiny fraction of NIH’s budget. The ADAPTABLE trial cost **$14 million** for **15,076 patients** (= **$929/patient**) versus **$420 million** for a similar traditional RCT (30x cheaper), yet pragmatic trials remain severely underfunded. PCORnet infrastructure enables real-world trials embedded in healthcare systems, but receives minimal support compared to basic research funding. Additional sources: https://commonfund.nih.gov/hcscollaboratory | https://pcornet.org/wp-content/uploads/2025/08/ADAPTABLE_Lay_Summary_21JUL2025.pdf | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5604499/
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NIH. Antidepressant clinical trial exclusion rates.
Zimmerman et al. https://pubmed.ncbi.nlm.nih.gov/26276679/ (2015)
Mean exclusion rate: 86.1% across 158 antidepressant efficacy trials (range: 44.4% to 99.8%) More than 82% of real-world depression patients would be ineligible for antidepressant registration trials Exclusion rates increased over time: 91.4% (2010-2014) vs. 83.8% (1995-2009) Most common exclusions: comorbid psychiatric disorders, age restrictions, insufficient depression severity, medical conditions Emergency psychiatry patients: only 3.3% eligible (96.7% excluded) when applying 9 common exclusion criteria Only a minority of depressed patients seen in clinical practice are likely to be eligible for most AETs Note: Generalizability of antidepressant trials has decreased over time, with increasingly stringent exclusion criteria eliminating patients who would actually use the drugs in clinical practice Additional sources: https://pubmed.ncbi.nlm.nih.gov/26276679/ | https://pubmed.ncbi.nlm.nih.gov/26164052/ | https://www.wolterskluwer.com/en/news/antidepressant-trials-exclude-most-real-world-patients-with-depression
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3.
CNBC. Warren buffett’s career average investment return.
CNBC https://www.cnbc.com/2025/05/05/warren-buffetts-return-tally-after-60-years-5502284percent.html (2025)
Berkshire’s compounded annual return from 1965 through 2024 was 19.9%, nearly double the 10.4% recorded by the S&P 500. Berkshire shares skyrocketed 5,502,284% compared to the S&P 500’s 39,054% rise during that period. Additional sources: https://www.cnbc.com/2025/05/05/warren-buffetts-return-tally-after-60-years-5502284percent.html | https://www.slickcharts.com/berkshire-hathaway/returns
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4.
Group, E. W. US farm subsidy database and analysis.
Environmental Working Group https://farm.ewg.org/ (2024)
US agricultural subsidies total approximately $30 billion annually, but create much larger economic distortions. Top 10% of farms receive 78% of subsidies, benefits concentrated in commodity crops (corn, soy, wheat, cotton), environmental damage from monoculture incentivized, and overall deadweight loss estimated at $50-120 billion annually. Additional sources: https://farm.ewg.org/ | https://www.ers.usda.gov/topics/farm-economy/farm-sector-income-finances/government-payments-the-safety-net/
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5.
Posen, B. R.
Restraint: A New Foundation for u.s. Grand Strategy. (Posen, 2014).
The United States could maintain adequate deterrence and defense with a much smaller military budget. Current spending levels reflect force projection capabilities far beyond what homeland security and deterrence require. A strategy of restraint could reduce defense spending by 40-50% while maintaining security through nuclear deterrence and geographic advantages. Additional sources: https://www.cornellpress.cornell.edu/book/9780801452581/restraint/
.
6.
Alliance, D. P.
The drug war by the numbers. (2021)
Since 1971, the war on drugs has cost the United States an estimated $1 trillion in enforcement. The federal drug control budget was $41 billion in 2022. Mass incarceration costs the U.S. at least $182 billion every year, with over $450 billion spent to incarcerate individuals on drug charges in federal prisons.
8.
Fund, I. M.
IMF fossil fuel subsidies data: 2023 update. (2023)
Globally, fossil fuel subsidies were $7 trillion in 2022 or 7.1 percent of GDP. The United States subsidies totaled $649 billion. Underpricing for local air pollution costs and climate damages are the largest contributor, accounting for about 30 percent each.
9.
Papanicolas, I. et al. Health care spending in the united states and other high-income countries.
Papanicolas et al. https://jamanetwork.com/journals/jama/article-abstract/2674671 (2018)
The US spent approximately twice as much as other high-income countries on medical care (mean per capita: $9,892 vs $5,289), with similar utilization but much higher prices. Administrative costs accounted for 8% of US spending vs 1-3% in other countries. US spending on pharmaceuticals was $1,443 per capita vs $749 elsewhere. Despite spending more, US health outcomes are not better. Additional sources: https://jamanetwork.com/journals/jama/article-abstract/2674671
.
10.
Hsieh, C.-T. & Moretti, E. Housing constraints and spatial misallocation.
Hsieh & Moretti https://www.aeaweb.org/articles?id=10.1257/mac.20170388 (2019)
We quantify the amount of spatial misallocation of labor across US cities and its aggregate costs. Tight land-use restrictions in high-productivity cities like New York, San Francisco, and Boston lowered aggregate US growth by 36% from 1964 to 2009. Local constraints on housing supply have had enormous effects on the national economy. Additional sources: https://www.aeaweb.org/articles?id=10.1257/mac.20170388
.
11.
Justice, V. I. of. The economic burden of incarceration in the united states.
Vera Institute https://www.vera.org/publications/the-economic-burden-of-incarceration-in-the-u-s (2024)
US incarceration costs approximately $80 billion annually in direct correctional expenditures alone. Including social costs (lost earnings, family impacts, health effects, reduced child outcomes), total burden exceeds $300 billion annually. The US incarcerates at 5x the rate of other OECD countries with no corresponding reduction in crime. Evidence shows community-based alternatives cost less and reduce recidivism more effectively. Additional sources: https://www.vera.org/publications/the-economic-burden-of-incarceration-in-the-u-s | https://www.prisonpolicy.org/reports/pie2024.html | https://www.rand.org/pubs/research_reports/RRA108-3.html
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12.
Marron Institute, N. Transit costs project - why US infrastructure costs so much.
NYU Transit Costs Project https://transitcosts.com/ (2024)
The United States builds transit infrastructure at dramatically higher costs than peer countries. New York’s Second Avenue Subway cost $2.5 billion per kilometer vs. $200-500 million in European cities. US highway construction similarly costs 2-5x more than comparable projects abroad. Causes include: excessive environmental review, litigation risk, lack of in-house expertise, fragmented project management, and inflated soft costs. Additional sources: https://transitcosts.com/ | https://www.brookings.edu/articles/why-does-infrastructure-cost-so-much/
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13.
Clemens, M. A.
Economics and emigration: Trillion-dollar bills on the sidewalk? Journal of Economic Perspectives 25, 83–106 (2011)
Free global labor mobility would increase gross world product by somewhere in the range of 67-147%... The gains to eliminating migration barriers amount to large fractions of world GDP—one or two orders of magnitude larger than the gains from dropping all remaining restrictions on international flows of goods and capital.
16.
Foundation, T. Tax compliance costs the US economy $546 billion annually.
https://taxfoundation.org/data/all/federal/irs-tax-compliance-costs/ (2024)
Americans will spend over 7.9 billion hours complying with IRS tax filing and reporting requirements in 2024. This costs the economy roughly $413 billion in lost productivity. In addition, the IRS estimates that Americans spend roughly $133 billion annually in out-of-pocket costs, bringing the total compliance costs to $546 billion, or nearly 2 percent of GDP.
17.
Organization, W. H. WHO global health estimates 2024.
World Health Organization https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates (2024)
Comprehensive mortality and morbidity data by cause, age, sex, country, and year Global mortality: 55-60 million deaths annually Lives saved by modern medicine (vaccines, cardiovascular drugs, oncology): 12M annually (conservative aggregate) Leading causes of death: Cardiovascular disease (17.9M), Cancer (10.3M), Respiratory disease (4.0M) Note: Baseline data for regulatory mortality analysis. Conservative estimate of pharmaceutical impact based on WHO immunization data (4.5M/year from vaccines) + cardiovascular interventions (3.3M/year) + oncology (1.5M/year) + other therapies. Additional sources: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates
.
18.
GiveWell. GiveWell cost per life saved for top charities (2024).
GiveWell: Top Charities https://www.givewell.org/charities/top-charities General range: $3,000-$5,500 per life saved (GiveWell top charities) Helen Keller International (Vitamin A): $3,500 average (2022-2024); varies $1,000-$8,500 by country Against Malaria Foundation: $5,500 per life saved New Incentives (vaccination incentives): $4,500 per life saved Malaria Consortium (seasonal malaria chemoprevention): $3,500 per life saved VAS program details: $2 to provide vitamin A supplements to child for one year Note: Figures accurate for 2024. Helen Keller VAS program has wide country variation ($1K-$8.5K) but $3,500 is accurate average. Among most cost-effective interventions globally Additional sources: https://www.givewell.org/charities/top-charities | https://www.givewell.org/charities/helen-keller-international | https://ourworldindata.org/cost-effectiveness
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19.
AARP. Unpaid caregiver hours and economic value.
AARP 2023 https://www.aarp.org/caregiving/financial-legal/info-2023/unpaid-caregivers-provide-billions-in-care.html (2023)
Average family caregiver: 25-26 hours per week (100-104 hours per month) 38 million caregivers providing 36 billion hours of care annually Economic value: $16.59 per hour = $600 billion total annual value (2021) 28% of people provided eldercare on a given day, averaging 3.9 hours when providing care Caregivers living with care recipient: 37.4 hours per week Caregivers not living with recipient: 23.7 hours per week Note: Disease-related caregiving is subset of total; includes elderly care, disability care, and child care Additional sources: https://www.aarp.org/caregiving/financial-legal/info-2023/unpaid-caregivers-provide-billions-in-care.html | https://www.bls.gov/news.release/elcare.nr0.htm | https://www.caregiver.org/resource/caregiver-statistics-demographics/
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MMWR, C. Childhood vaccination economic benefits.
CDC MMWR https://www.cdc.gov/mmwr/volumes/73/wr/mm7331a2.htm (1994)
US programs (1994-2023): $540B direct savings, $2.7T societal savings ( $18B/year direct, $90B/year societal) Global (2001-2020): $820B value for 10 diseases in 73 countries ( $41B/year) ROI: $11 return per $1 invested Measles vaccination alone saved 93.7M lives (61% of 154M total) over 50 years (1974-2024) Additional sources: https://www.cdc.gov/mmwr/volumes/73/wr/mm7331a2.htm | https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(24
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22.
Labor Statistics, U. S. B. of.
CPI inflation calculator. (2024)
CPI-U (1980): 82.4 CPI-U (2024): 313.5 Inflation multiplier (1980-2024): 3.80× Cumulative inflation: 280.48% Average annual inflation rate: 3.08% Note: Official U.S. government inflation data using Consumer Price Index for All Urban Consumers (CPI-U). Additional sources: https://www.bls.gov/data/inflation_calculator.htm
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23.
Del Rosal, I. The empirical measurement of rent-seeking costs.
Journal of Economic Surveys https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1467-6419.2009.00621.x (2011)
A comprehensive survey of empirical estimates finds rent-seeking costs range from 0.2% to 23.7% of GDP across different methodologies and countries. Laband & Sophocleus (1988) estimated up to 45% for the US.
24.
via, D. analysis. ClinicalTrials.gov cumulative enrollment data (2025).
Direct analysis via ClinicalTrials.gov API v2 https://clinicaltrials.gov/data-api/api Analysis of 100,000 active/recruiting/completed trials on ClinicalTrials.gov (November 2025) shows cumulative enrollment of 12.2 million participants: Phase 1 (722k), Phase 2 (2.2M), Phase 3 (6.5M), Phase 4 (2.7M). Median participants per trial: Phase 1 (33), Phase 2 (60), Phase 3 (237), Phase 4 (90). Additional sources: https://clinicaltrials.gov/data-api/api
.
25.
CAN, A. Clinical trial patient participation rate.
ACS CAN: Barriers to Clinical Trial Enrollment https://www.fightcancer.org/policy-resources/barriers-patient-enrollment-therapeutic-clinical-trials-cancer Only 3-5% of adult cancer patients in US receive treatment within clinical trials About 5% of American adults have ever participated in any clinical trial Oncology: 2-3% of all oncology patients participate Contrast: 50-60% enrollment for pediatric cancer trials (<15 years old) Note: 20% of cancer trials fail due to insufficient enrollment; 11% of research sites enroll zero patients Additional sources: https://www.fightcancer.org/policy-resources/barriers-patient-enrollment-therapeutic-clinical-trials-cancer | https://hints.cancer.gov/docs/Briefs/HINTS_Brief_48.pdf
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26.
ScienceDaily. Global prevalence of chronic disease.
ScienceDaily: GBD 2015 Study https://www.sciencedaily.com/releases/2015/06/150608081753.htm (2015)
2.3 billion individuals had more than five ailments (2013) Chronic conditions caused 74% of all deaths worldwide (2019), up from 67% (2010) Approximately 1 in 3 adults suffer from multiple chronic conditions (MCCs) Risk factor exposures: 2B exposed to biomass fuel, 1B to air pollution, 1B smokers Projected economic cost: $47 trillion by 2030 Note: 2.3B with 5+ ailments is more accurate than "2B with chronic disease." One-third of all adults globally have multiple chronic conditions Additional sources: https://www.sciencedaily.com/releases/2015/06/150608081753.htm | https://pmc.ncbi.nlm.nih.gov/articles/PMC10830426/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC6214883/
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27.
C&EN. Annual number of new drugs approved globally: 50.
C&EN https://cen.acs.org/pharmaceuticals/50-new-drugs-received-FDA/103/i2 (2025)
50 new drugs approved annually Additional sources: https://cen.acs.org/pharmaceuticals/50-new-drugs-received-FDA/103/i2 | https://www.fda.gov/drugs/development-approval-process-drugs/novel-drug-approvals-fda
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28.
estimates, I. Clinical trial abandonment.
Average: 10% abandoned before completion
.
32.
GiveWell. Cost per DALY for deworming programs.
https://www.givewell.org/international/technical/programs/deworming/cost-effectiveness Schistosomiasis treatment: $28.19-$70.48 per DALY (using arithmetic means with varying disability weights) Soil-transmitted helminths (STH) treatment: $82.54 per DALY (midpoint estimate) Note: GiveWell explicitly states this 2011 analysis is "out of date" and their current methodology focuses on long-term income effects rather than short-term health DALYs Additional sources: https://www.givewell.org/international/technical/programs/deworming/cost-effectiveness
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33.
Numbers, T. by. Pre-1962 drug development costs and timeline (think by numbers).
Think by Numbers: How Many Lives Does FDA Save? https://thinkbynumbers.org/health/how-many-net-lives-does-the-fda-save/ (1962)
Historical estimates (1970-1985): USD $226M fully capitalized (2011 prices) 1980s drugs: $65M after-tax R&D (1990 dollars), $194M compounded to approval (1990 dollars) Modern comparison: $2-3B costs, 7-12 years (dramatic increase from pre-1962) Context: 1962 regulatory clampdown reduced new treatment production by 70%, dramatically increasing development timelines and costs Note: Secondary source; less reliable than Congressional testimony Additional sources: https://thinkbynumbers.org/health/how-many-net-lives-does-the-fda-save/ | https://en.wikipedia.org/wiki/Cost_of_drug_development | https://www.statnews.com/2018/10/01/changing-1962-law-slash-drug-prices/
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34.
(BIO), B. I. O. BIO clinical development success rates 2011-2020.
Biotechnology Innovation Organization (BIO) https://go.bio.org/rs/490-EHZ-999/images/ClinicalDevelopmentSuccessRates2011_2020.pdf (2021)
Phase I duration: 2.3 years average Total time to market (Phase I-III + approval): 10.5 years average Phase transition success rates: Phase I→II: 63.2%, Phase II→III: 30.7%, Phase III→Approval: 58.1% Overall probability of approval from Phase I: 12% Note: Largest publicly available study of clinical trial success rates. Efficacy lag = 10.5 - 2.3 = 8.2 years post-safety verification. Additional sources: https://go.bio.org/rs/490-EHZ-999/images/ClinicalDevelopmentSuccessRates2011_2020.pdf
.
35.
Medicine, N. Drug repurposing rate ( 30%).
Nature Medicine https://www.nature.com/articles/s41591-024-03233-x (2024)
Approximately 30% of drugs gain at least one new indication after initial approval. Additional sources: https://www.nature.com/articles/s41591-024-03233-x
.
36.
EPI. Education investment economic multiplier (2.1).
EPI: Public Investments Outside Core Infrastructure https://www.epi.org/publication/bp348-public-investments-outside-core-infrastructure/ Early childhood education: Benefits 12X outlays by 2050; $8.70 per dollar over lifetime Educational facilities: $1 spent → $1.50 economic returns Energy efficiency comparison: 2-to-1 benefit-to-cost ratio (McKinsey) Private return to schooling: 9% per additional year (World Bank meta-analysis) Note: 2.1 multiplier aligns with benefit-to-cost ratios for educational infrastructure/energy efficiency. Early childhood education shows much higher returns (12X by 2050) Additional sources: https://www.epi.org/publication/bp348-public-investments-outside-core-infrastructure/ | https://documents1.worldbank.org/curated/en/442521523465644318/pdf/WPS8402.pdf | https://freopp.org/whitepapers/establishing-a-practical-return-on-investment-framework-for-education-and-skills-development-to-expand-economic-opportunity/
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37.
PMC. Healthcare investment economic multiplier (1.8).
PMC: California Universal Health Care https://pmc.ncbi.nlm.nih.gov/articles/PMC5954824/ (2022)
Healthcare fiscal multiplier: 4.3 (95% CI: 2.5-6.1) during pre-recession period (1995-2007) Overall government spending multiplier: 1.61 (95% CI: 1.37-1.86) Why healthcare has high multipliers: No effect on trade deficits (spending stays domestic); improves productivity & competitiveness; enhances long-run potential output Gender-sensitive fiscal spending (health & care economy) produces substantial positive growth impacts Note: "1.8" appears to be conservative estimate; research shows healthcare multipliers of 4.3 Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC5954824/ | https://cepr.org/voxeu/columns/government-investment-and-fiscal-stimulus | https://ncbi.nlm.nih.gov/pmc/articles/PMC3849102/ | https://set.odi.org/wp-content/uploads/2022/01/Fiscal-multipliers-review.pdf
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38.
Bank, W. Infrastructure investment economic multiplier (1.6).
World Bank: Infrastructure Investment as Stimulus https://blogs.worldbank.org/en/ppps/effectiveness-infrastructure-investment-fiscal-stimulus-what-weve-learned (2022)
Infrastructure fiscal multiplier: 1.6 during contractionary phase of economic cycle Average across all economic states: 1.5 (meaning $1 of public investment → $1.50 of economic activity) Time horizon: 0.8 within 1 year, 1.5 within 2-5 years Range of estimates: 1.5-2.0 (following 2008 financial crisis & American Recovery Act) Italian public construction: 1.5-1.9 multiplier US ARRA: 0.4-2.2 range (differential impacts by program type) Economic Policy Institute: Uses 1.6 for infrastructure spending (middle range of estimates) Note: Public investment less likely to crowd out private activity during recessions; particularly effective when monetary policy loose with near-zero rates Additional sources: https://blogs.worldbank.org/en/ppps/effectiveness-infrastructure-investment-fiscal-stimulus-what-weve-learned | https://www.gihub.org/infrastructure-monitor/insights/fiscal-multiplier-effect-of-infrastructure-investment/ | https://cepr.org/voxeu/columns/government-investment-and-fiscal-stimulus | https://www.richmondfed.org/publications/research/economic_brief/2022/eb_22-04
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39.
Mercatus. Military spending economic multiplier (0.6).
Mercatus: Defense Spending and Economy https://www.mercatus.org/research/research-papers/defense-spending-and-economy Ramey (2011): 0.6 short-run multiplier Barro (1981): 0.6 multiplier for WWII spending (war spending crowded out 40¢ private economic activity per federal dollar) Barro & Redlick (2011): 0.4 within current year, 0.6 over two years; increased govt spending reduces private-sector GDP portions General finding: $1 increase in deficit-financed federal military spending = less than $1 increase in GDP Variation by context: Central/Eastern European NATO: 0.6 on impact, 1.5-1.6 in years 2-3, gradual fall to zero Ramey & Zubairy (2018): Cumulative 1% GDP increase in military expenditure raises GDP by 0.7% Additional sources: https://www.mercatus.org/research/research-papers/defense-spending-and-economy | https://cepr.org/voxeu/columns/world-war-ii-america-spending-deficits-multipliers-and-sacrifice | https://www.rand.org/content/dam/rand/pubs/research_reports/RRA700/RRA739-2/RAND_RRA739-2.pdf
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40.
FDA. FDA-approved prescription drug products (20,000+).
FDA https://www.fda.gov/media/143704/download There are over 20,000 prescription drug products approved for marketing. Additional sources: https://www.fda.gov/media/143704/download
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42.
ACLED. Active combat deaths annually.
ACLED: Global Conflict Surged 2024 https://acleddata.com/2024/12/12/data-shows-global-conflict-surged-in-2024-the-washington-post/ (2024)
2024: 233,597 deaths (30% increase from 179,099 in 2023) Deadliest conflicts: Ukraine (67,000), Palestine (35,000) Nearly 200,000 acts of violence (25% higher than 2023, double from 5 years ago) One in six people globally live in conflict-affected areas Additional sources: https://acleddata.com/2024/12/12/data-shows-global-conflict-surged-in-2024-the-washington-post/ | https://acleddata.com/media-citation/data-shows-global-conflict-surged-2024-washington-post | https://acleddata.com/conflict-index/index-january-2024/
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43.
UCDP. State violence deaths annually.
UCDP: Uppsala Conflict Data Program https://ucdp.uu.se/ Uppsala Conflict Data Program (UCDP): Tracks one-sided violence (organized actors attacking unarmed civilians) UCDP definition: Conflicts causing at least 25 battle-related deaths in calendar year 2023 total organized violence: 154,000 deaths; Non-state conflicts: 20,900 deaths UCDP collects data on state-based conflicts, non-state conflicts, and one-sided violence Specific "2,700 annually" figure for state violence not found in recent UCDP data; actual figures vary annually Additional sources: https://ucdp.uu.se/ | https://en.wikipedia.org/wiki/Uppsala_Conflict_Data_Program | https://ourworldindata.org/grapher/deaths-in-armed-conflicts-by-region
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44.
Data, O. W. in. Terror attack deaths (8,300 annually).
Our World in Data: Terrorism https://ourworldindata.org/terrorism (2024)
2023: 8,352 deaths (22% increase from 2022, highest since 2017) 2023: 3,350 terrorist incidents (22% decrease), but 56% increase in avg deaths per attack Global Terrorism Database (GTD): 200,000+ terrorist attacks recorded (2021 version) Maintained by: National Consortium for Study of Terrorism & Responses to Terrorism (START), U. of Maryland Geographic shift: Epicenter moved from Middle East to Central Sahel (sub-Saharan Africa) - now >50% of all deaths Additional sources: https://ourworldindata.org/terrorism | https://reliefweb.int/report/world/global-terrorism-index-2024 | https://www.start.umd.edu/gtd/ | https://ourworldindata.org/grapher/fatalities-from-terrorism
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45.
Health Metrics, I. for & (IHME), E. IHME global burden of disease 2021 (2.88B DALYs, 1.13B YLD).
Institute for Health Metrics and Evaluation (IHME) https://vizhub.healthdata.org/gbd-results/ (2024)
In 2021, global DALYs totaled approximately 2.88 billion, comprising 1.75 billion Years of Life Lost (YLL) and 1.13 billion Years Lived with Disability (YLD). This represents a 13% increase from 2019 (2.55B DALYs), largely attributable to COVID-19 deaths and aging populations. YLD accounts for approximately 39% of total DALYs, reflecting the substantial burden of non-fatal chronic conditions. Additional sources: https://vizhub.healthdata.org/gbd-results/ | https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(24 | https://www.healthdata.org/research-analysis/about-gbd
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46.
War, B. W. C. of. Environmental cost of war ($100B annually).
Brown Watson Costs of War: Environmental Cost https://watson.brown.edu/costsofwar/costs/social/environment War on Terror emissions: 1.2B metric tons GHG (equivalent to 257M cars/year) Military: 5.5% of global GHG emissions (2X aviation + shipping combined) US DoD: World’s single largest institutional oil consumer, 47th largest emitter if nation Cleanup costs: $500B+ for military contaminated sites Gaza war environmental damage: $56.4B; landmine clearance: $34.6B expected Climate finance gap: Rich nations spend 30X more on military than climate finance Note: Military activities cause massive environmental damage through GHG emissions, toxic contamination, and long-term cleanup costs far exceeding current climate finance commitments Additional sources: https://watson.brown.edu/costsofwar/costs/social/environment | https://earth.org/environmental-costs-of-wars/ | https://transformdefence.org/transformdefence/stats/
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47.
ScienceDaily. Medical research lives saved annually (4.2 million).
ScienceDaily: Physical Activity Prevents 4M Deaths https://www.sciencedaily.com/releases/2020/06/200617194510.htm (2020)
Physical activity: 3.9M early deaths averted annually worldwide (15% lower premature deaths than without) COVID vaccines (2020-2024): 2.533M deaths averted, 14.8M life-years preserved; first year alone: 14.4M deaths prevented Cardiovascular prevention: 3 interventions could delay 94.3M deaths over 25 years (antihypertensives alone: 39.4M) Pandemic research response: Millions of deaths averted through rapid vaccine/drug development Additional sources: https://www.sciencedaily.com/releases/2020/06/200617194510.htm | https://pmc.ncbi.nlm.nih.gov/articles/PMC9537923/ | https://www.ahajournals.org/doi/10.1161/CIRCULATIONAHA.118.038160 | https://pmc.ncbi.nlm.nih.gov/articles/PMC9464102/
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48.
SIPRI. 36:1 disparity ratio of spending on weapons over cures.
SIPRI: Military Spending https://www.sipri.org/commentary/blog/2016/opportunity-cost-world-military-spending (2016)
Global military spending: $2.7 trillion (2024, SIPRI) Global government medical research: $68 billion (2024) Actual ratio: 39.7:1 in favor of weapons over medical research Military R&D alone: $85B (2004 data, 10% of global R&D) Military spending increases crowd out health: 1% ↑ military = 0.62% ↓ health spending Note: Ratio actually worse than 36:1. Each 1% increase in military spending reduces health spending by 0.62%, with effect more intense in poorer countries (0.962% reduction) Additional sources: https://www.sipri.org/commentary/blog/2016/opportunity-cost-world-military-spending | https://pmc.ncbi.nlm.nih.gov/articles/PMC9174441/ | https://www.congress.gov/crs-product/R45403
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49.
Numbers, T. by. Lost human capital due to war ($270B annually).
Think by Numbers: War Costs $74 <https://thinkbynumbers.org/military/war/the-economic-case-for-peace-a-comprehensive-financial-analysis/> (2021)
Lost human capital from war: $300B annually (economic impact of losing skilled/productive individuals to conflict) Broader conflict/violence cost: $14T/year globally 1.4M violent deaths/year; conflict holds back economic development, causes instability, widens inequality, erodes human capital 2002: 48.4M DALYs lost from 1.6M violence deaths = $151B economic value (2000 USD) Economic toll includes: commodity prices, inflation, supply chain disruption, declining output, lost human capital Additional sources: <https://thinkbynumbers.org/military/war/the-economic-case-for-peace-a-comprehensive-financial-analysis/> | https://www.weforum.org/stories/2021/02/war-violence-costs-each-human-5-a-day/ | https://pubmed.ncbi.nlm.nih.gov/19115548/
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50.
PubMed. Psychological impact of war cost ($100B annually).
PubMed: Economic Burden of PTSD https://pubmed.ncbi.nlm.nih.gov/35485933/ PTSD economic burden (2018 U.S.): $232.2B total ($189.5B civilian, $42.7B military) Civilian costs driven by: Direct healthcare ($66B), unemployment ($42.7B) Military costs driven by: Disability ($17.8B), direct healthcare ($10.1B) Exceeds costs of other mental health conditions (anxiety, depression) War-exposed populations: 2-3X higher rates of anxiety, depression, PTSD; women and children most vulnerable Note: Actual burden $232B, significantly higher than "$100B" claimed Additional sources: https://pubmed.ncbi.nlm.nih.gov/35485933/ | https://news.va.gov/103611/study-national-economic-burden-of-ptsd-staggering/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC9957523/
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51.
CGDev. UNHCR average refugee support cost.
CGDev https://www.cgdev.org/blog/costs-hosting-refugees-oecd-countries-and-why-uk-outlier (2024)
The average cost of supporting a refugee is $1,384 per year. This represents total host country costs (housing, healthcare, education, security). OECD countries average $6,100 per refugee (mean 2022-2023), with developing countries spending $700-1,000. Global weighted average of $1,384 is reasonable given that 75-85% of refugees are in low/middle-income countries. Additional sources: https://www.cgdev.org/blog/costs-hosting-refugees-oecd-countries-and-why-uk-outlier | https://www.unhcr.org/sites/default/files/2024-11/UNHCR-WB-global-cost-of-refugee-inclusion-in-host-country-health-systems.pdf
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52.
Bank, W. World bank trade disruption cost from conflict.
World Bank https://www.worldbank.org/en/topic/trade/publication/trading-away-from-conflict Estimated $616B annual cost from conflict-related trade disruption. World Bank research shows civil war costs an average developing country 30 years of GDP growth, with 20 years needed for trade to return to pre-war levels. Trade disputes analysis shows tariff escalation could reduce global exports by up to $674 billion. Additional sources: https://www.worldbank.org/en/topic/trade/publication/trading-away-from-conflict | https://www.nber.org/papers/w11565 | http://blogs.worldbank.org/en/trade/impacts-global-trade-and-income-current-trade-disputes
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53.
VA. Veteran healthcare cost projections.
VA https://department.va.gov/wp-content/uploads/2025/06/2026-Budget-in-Brief.pdf (2026)
VA budget: $441.3B requested for FY 2026 (10% increase). Disability compensation: $165.6B in FY 2024 for 6.7M veterans. PACT Act projected to increase spending by $300B between 2022-2031. Costs under Toxic Exposures Fund: $20B (2024), $30.4B (2025), $52.6B (2026). Additional sources: https://department.va.gov/wp-content/uploads/2025/06/2026-Budget-in-Brief.pdf | https://www.cbo.gov/publication/45615 | https://www.legion.org/information-center/news/veterans-healthcare/2025/june/va-budget-tops-400-billion-for-2025-from-higher-spending-on-mandated-benefits-medical-care
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55.
size, D. from global market & ratios, public/private funding. Private industry clinical trial spending.
Private pharmaceutical and biotech industry spends approximately $75-90 billion annually on clinical trials, representing roughly 90% of global clinical trial spending.
56.
IHME Global Burden of Disease (2.55B DALYs), C. from & GDP per capita valuation, global. $109 trillion annual global disease burden.
The global economic burden of disease, including direct healthcare costs (\(8.2 trillion) and lost productivity (\)100.9 trillion from 2.55 billion DALYs × \(39,570 per DALY), totals approximately\)109.1 trillion annually.
57.
Trials, A. C. Global government spending on interventional clinical trials: $3-6 billion/year.
Applied Clinical Trials https://www.appliedclinicaltrialsonline.com/view/sizing-clinical-research-market Estimated range based on NIH ( $0.8-5.6B), NIHR ($1.6B total budget), and EU funding ( $1.3B/year). Roughly 5-10% of global market. Additional sources: https://www.appliedclinicaltrialsonline.com/view/sizing-clinical-research-market | https://www.thelancet.com/journals/langlo/article/PIIS2214-109X(20
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58.
Suisse/UBS, C. Credit suisse global wealth report 2023.
Credit Suisse/UBS https://www.ubs.com/global/en/family-office-uhnw/reports/global-wealth-report-2023.html (2023)
Total global household wealth: USD 454.4 trillion (2022) Wealth declined by USD 11.3 trillion (-2.4%) in 2022, first decline since 2008 Wealth per adult: USD 84,718 Additional sources: https://www.ubs.com/global/en/family-office-uhnw/reports/global-wealth-report-2023.html
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59.
budgets:, S. component country. Global government medical research spending ($67.5B, 2023–2024).
See component country budgets: NIH Budget #nih-budget-fy2025.
61.
budgets, E. from major foundation & activities. Nonprofit clinical trial funding estimate.
Nonprofit foundations spend an estimated $2-5 billion annually on clinical trials globally, representing approximately 2-5% of total clinical trial spending.
62.
IQVIA, I. reports: Global pharmaceutical r&d spending.
Total global pharmaceutical R&D spending is approximately $300 billion annually. Clinical trials represent 15-20% of this total ($45-60B), with the remainder going to drug discovery, preclinical research, regulatory affairs, and manufacturing development.
63.
UN. Global population reaches 8 billion.
UN: World Population 8 Billion Nov 15 2022 https://www.un.org/en/desa/world-population-reach-8-billion-15-november-2022 (2022)
Milestone: November 15, 2022 (UN World Population Prospects 2022) Day of Eight Billion" designated by UN Added 1 billion people in just 11 years (2011-2022) Growth rate: Slowest since 1950; fell under 1% in 2020 Future: 15 years to reach 9B (2037); projected peak 10.4B in 2080s Projections: 8.5B (2030), 9.7B (2050), 10.4B (2080-2100 plateau) Note: Milestone reached Nov 2022. Population growth slowing; will take longer to add next billion (15 years vs 11 years) Additional sources: https://www.un.org/en/desa/world-population-reach-8-billion-15-november-2022 | https://www.un.org/en/dayof8billion | https://en.wikipedia.org/wiki/Day_of_Eight_Billion
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64.
School, H. K. 3.5% participation tipping point.
Harvard Kennedy School https://www.hks.harvard.edu/centers/carr/publications/35-rule-how-small-minority-can-change-world (2020)
The research found that nonviolent campaigns were twice as likely to succeed as violent ones, and once 3.5% of the population were involved, they were always successful. Chenoweth and Maria Stephan studied the success rates of civil resistance efforts from 1900 to 2006, finding that nonviolent movements attracted, on average, four times as many participants as violent movements and were more likely to succeed. Key finding: Every campaign that mobilized at least 3.5% of the population in sustained protest was successful (in their 1900-2006 dataset) Note: The 3.5% figure is a descriptive statistic from historical analysis, not a guaranteed threshold. One exception (Bahrain 2011-2014 with 6%+ participation) has been identified. The rule applies to regime change, not policy change in democracies. Additional sources: https://www.hks.harvard.edu/centers/carr/publications/35-rule-how-small-minority-can-change-world | https://www.hks.harvard.edu/sites/default/files/2024-05/Erica%20Chenoweth_2020-005.pdf | https://www.bbc.com/future/article/20190513-it-only-takes-35-of-people-to-change-the-world | https://en.wikipedia.org/wiki/3.5%25_rule
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65.
NHGRI. Human genome project and CRISPR discovery.
NHGRI https://www.genome.gov/11006929/2003-release-international-consortium-completes-hgp (2003)
Your DNA is 3 billion base pairs Read the entire code (Human Genome Project, completed 2003) Learned to edit it (CRISPR, discovered 2012) Additional sources: https://www.genome.gov/11006929/2003-release-international-consortium-completes-hgp | https://www.nobelprize.org/prizes/chemistry/2020/press-release/
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66.
PMC. Only 12% of human interactome targeted.
PMC https://pmc.ncbi.nlm.nih.gov/articles/PMC10749231/ (2023)
Mapping 350,000+ clinical trials showed that only 12% of the human interactome has ever been targeted by drugs. Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC10749231/
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67.
WHO. ICD-10 code count ( 14,000).
WHO https://icd.who.int/browse10/2019/en (2019)
The ICD-10 classification contains approximately 14,000 codes for diseases, signs and symptoms. Additional sources: https://icd.who.int/browse10/2019/en
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68.
Wikipedia. Longevity escape velocity (LEV) - maximum human life extension potential.
Wikipedia: Longevity Escape Velocity https://en.wikipedia.org/wiki/Longevity_escape_velocity Longevity escape velocity: Hypothetical point where medical advances extend life expectancy faster than time passes Term coined by Aubrey de Grey (biogerontologist) in 2004 paper; concept from David Gobel (Methuselah Foundation) Current progress: Science adds 3 months to lifespan per year; LEV requires adding >1 year per year Sinclair (Harvard): "There is no biological upper limit to age" - first person to live to 150 may already be born De Grey: 50% chance of reaching LEV by mid-to-late 2030s; SENS approach = damage repair rather than slowing damage Kurzweil (2024): LEV by 2029-2035, AI will simulate biological processes to accelerate solutions George Church: LEV "in a decade or two" via age-reversal clinical trials Natural lifespan cap: 120-150 years (Jeanne Calment record: 122); engineering approach could bypass via damage repair Key mechanisms: Epigenetic reprogramming, senolytic drugs, stem cell therapy, gene therapy, AI-driven drug discovery Current record: Jeanne Calment (122 years, 164 days) - record unbroken since 1997 Note: LEV is theoretical but increasingly plausible given demonstrated age reversal in mice (109% lifespan extension) and human cells (30-year epigenetic age reversal) Additional sources: https://en.wikipedia.org/wiki/Longevity_escape_velocity | https://pmc.ncbi.nlm.nih.gov/articles/PMC423155/ | https://www.popularmechanics.com/science/a36712084/can-science-cure-death-longevity/ | https://www.diamandis.com/blog/longevity-escape-velocity
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69.
OpenSecrets. Lobbyist statistics for washington d.c.
OpenSecrets: Lobbying in US https://en.wikipedia.org/wiki/Lobbying_in_the_United_States Registered lobbyists: Over 12,000 (some estimates); 12,281 registered (2013) Former government employees as lobbyists: 2,200+ former federal employees (1998-2004), including 273 former White House staffers, 250 former Congress members & agency heads Congressional revolving door: 43% (86 of 198) lawmakers who left 1998-2004 became lobbyists; currently 59% leaving to private sector work for lobbying/consulting firms/trade groups Executive branch: 8% were registered lobbyists at some point before/after government service Additional sources: https://en.wikipedia.org/wiki/Lobbying_in_the_United_States | https://www.opensecrets.org/revolving-door | https://www.citizen.org/article/revolving-congress/ | https://www.propublica.org/article/we-found-a-staggering-281-lobbyists-whove-worked-in-the-trump-administration
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70.
Vaccines, M. Measles vaccination ROI.
MDPI Vaccines https://www.mdpi.com/2076-393X/12/11/1210 (2024)
Single measles vaccination: 167:1 benefit-cost ratio. MMR (measles-mumps-rubella) vaccination: 14:1 ROI. Historical US elimination efforts (1966-1974): benefit-cost ratio of 10.3:1 with net benefits exceeding USD 1.1 billion (1972 dollars, or USD 8.0 billion in 2023 dollars). 2-dose MMR programs show direct benefit/cost ratio of 14.2 with net savings of $5.3 billion, and 26.0 from societal perspectives with net savings of $11.6 billion. Additional sources: https://www.mdpi.com/2076-393X/12/11/1210 | https://www.tandfonline.com/doi/full/10.1080/14760584.2024.2367451
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73.
Orphanet Journal of Rare Diseases (2024), C. from. Diseases getting first effective treatment each year.
Calculated from Orphanet Journal of Rare Diseases (2024) https://ojrd.biomedcentral.com/articles/10.1186/s13023-024-03398-1 (2024)
Under the current system, approximately 10-15 diseases per year receive their FIRST effective treatment. Calculation: 5% of 7,000 rare diseases ( 350) have FDA-approved treatment, accumulated over 40 years of the Orphan Drug Act = 9 rare diseases/year. Adding 5-10 non-rare diseases that get first treatments yields 10-20 total. FDA approves 50 drugs/year, but many are for diseases that already have treatments (me-too drugs, second-line therapies). Only 15 represent truly FIRST treatments for previously untreatable conditions.
74.
NIH. NIH budget (FY 2025).
NIH https://www.nih.gov/about-nih/organization/budget (2024)
The budget total of \(47.7 billion also includes\)1.412 billion derived from PHS Evaluation financing... Additional sources: https://www.nih.gov/about-nih/organization/budget | https://officeofbudget.od.nih.gov/
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75.
al., B. et. NIH spending on clinical trials: 3.3%.
Bentley et al. https://www.fiercebiotech.com/biotech/nih-spending-clinical-trials-reached-81b-over-decade (2023)
NIH spent $8.1 billion on clinical trials for approved drugs (2010-2019), representing 3.3% of relevant NIH spending. Additional sources: https://www.fiercebiotech.com/biotech/nih-spending-clinical-trials-reached-81b-over-decade | https://www.fiercebiotech.com/biotech/nih-spending-clinical-trials-reached-81b-over-decade
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76.
PMC. Standard medical research ROI ($20k-$100k/QALY).
PMC: Cost-effectiveness Thresholds Used by Study Authors https://pmc.ncbi.nlm.nih.gov/articles/PMC10114019/ (1990)
Typical cost-effectiveness thresholds for medical interventions in rich countries range from $50,000 to $150,000 per QALY. The Institute for Clinical and Economic Review (ICER) uses a $100,000-$150,000/QALY threshold for value-based pricing. Between 1990-2021, authors increasingly cited $100,000 (47% by 2020-21) or $150,000 (24% by 2020-21) per QALY as benchmarks for cost-effectiveness. Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC10114019/ | https://icer.org/our-approach/methods-process/cost-effectiveness-the-qaly-and-the-evlyg/
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77.
Institute, M. RECOVERY trial 82× cost reduction.
Manhattan Institute: Slow Costly Trials https://manhattan.institute/article/slow-costly-clinical-trials-drag-down-biomedical-breakthroughs RECOVERY trial: $500 per patient ($20M for 48,000 patients = $417/patient) Typical clinical trial: $41,000 median per-patient cost Cost reduction: 80-82× cheaper ($41,000 ÷ $500 ≈ 82×) Efficiency: $50 per patient per answer (10 therapeutics tested, 4 effective) Dexamethasone estimated to save >630,000 lives Additional sources: https://manhattan.institute/article/slow-costly-clinical-trials-drag-down-biomedical-breakthroughs | https://pmc.ncbi.nlm.nih.gov/articles/PMC9293394/
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78.
Trials. Patient willingness to participate in clinical trials.
Trials: Patients’ Willingness Survey https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-015-1105-3 Recent surveys: 49-51% willingness (2020-2022) - dramatic drop from 85% (2019) during COVID-19 pandemic Cancer patients when approached: 88% consented to trials (Royal Marsden Hospital) Study type variation: 44.8% willing for drug trial, 76.2% for diagnostic study Top motivation: "Learning more about my health/medical condition" (67.4%) Top barrier: "Worry about experiencing side effects" (52.6%) Additional sources: https://trialsjournal.biomedcentral.com/articles/10.1186/s13063-015-1105-3 | https://www.appliedclinicaltrialsonline.com/view/industry-forced-to-rethink-patient-participation-in-trials | https://pmc.ncbi.nlm.nih.gov/articles/PMC7183682/
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79.
CSDD, T. Cost of drug development.
Various estimates suggest $1.0 - $2.5 billion to bring a new drug from discovery through FDA approval, spread across 10 years. Tufts Center for the Study of Drug Development often cited for $1.0 - $2.6 billion/drug. Industry reports (IQVIA, Deloitte) also highlight $2+ billion figures.
80.
Health, V. in. Average lifetime revenue per successful drug.
Value in Health: Sales Revenues for New Therapeutic Agents02754-2/fulltext) https://www.valueinhealthjournal.com/article/S1098-3015(24 Study of 361 FDA-approved drugs from 1995-2014 (median follow-up 13.2 years): Mean lifetime revenue: $15.2 billion per drug Median lifetime revenue: $6.7 billion per drug Revenue after 5 years: $3.2 billion (mean) Revenue after 10 years: $9.5 billion (mean) Revenue after 15 years: $19.2 billion (mean) Distribution highly skewed: top 25 drugs (7%) accounted for 38% of total revenue ($2.1T of $5.5T) Additional sources: https://www.valueinhealthjournal.com/article/S1098-3015(24 | https://www.sciencedirect.com/science/article/pii/S1098301524027542
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81.
Lichtenberg, F. R.
How many life-years have new drugs saved? A three-way fixed-effects analysis of 66 diseases in 27 countries, 2000-2013.
International Health 11, 403–416 (2019)
Using 3-way fixed-effects methodology (disease-country-year) across 66 diseases in 22 countries, this study estimates that drugs launched after 1981 saved 148.7 million life-years in 2013 alone. The regression coefficients for drug launches 0-11 years prior (beta=-0.031, SE=0.008) and 12+ years prior (beta=-0.057, SE=0.013) on years of life lost are highly significant (p<0.0001). Confidence interval for life-years saved: 79.4M-239.8M (95 percent CI) based on propagated standard errors from Table 2.
82.
Deloitte. Pharmaceutical r&d return on investment (ROI).
Deloitte: Measuring Pharmaceutical Innovation 2025 https://www.deloitte.com/ch/en/Industries/life-sciences-health-care/research/measuring-return-from-pharmaceutical-innovation.html (2025)
Deloitte’s annual study of top 20 pharma companies by R&D spend (2010-2024): 2024 ROI: 5.9% (second year of growth after decade of decline) 2023 ROI: 4.3% (estimated from trend) 2022 ROI: 1.2% (historic low since study began, 13-year low) 2021 ROI: 6.8% (record high, inflated by COVID-19 vaccines/treatments) Long-term trend: Declining for over a decade before 2023 recovery Average R&D cost per asset: $2.3B (2022), $2.23B (2024) These returns (1.2-5.9% range) fall far below typical corporate ROI targets (15-20%) Additional sources: https://www.deloitte.com/ch/en/Industries/life-sciences-health-care/research/measuring-return-from-pharmaceutical-innovation.html | https://www.prnewswire.com/news-releases/deloittes-13th-annual-pharmaceutical-innovation-report-pharma-rd-return-on-investment-falls-in-post-pandemic-market-301738807.html | https://hitconsultant.net/2023/02/16/pharma-rd-roi-falls-to-lowest-level-in-13-years/
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83.
Discovery, N. R. D. Drug trial success rate from phase i to approval.
Nature Reviews Drug Discovery: Clinical Success Rates https://www.nature.com/articles/nrd.2016.136 (2016)
Overall Phase I to approval: 10-12.8% (conventional wisdom 10%, studies show 12.8%) Recent decline: Average LOA now 6.7% for Phase I (2014-2023 data) Leading pharma companies: 14.3% average LOA (range 8-23%) Varies by therapeutic area: Oncology 3.4%, CNS/cardiovascular lowest at Phase III Phase-specific success: Phase I 47-54%, Phase II 28-34%, Phase III 55-70% Note: 12% figure accurate for historical average. Recent data shows decline to 6.7%, with Phase II as primary attrition point (28% success) Additional sources: https://www.nature.com/articles/nrd.2016.136 | https://pmc.ncbi.nlm.nih.gov/articles/PMC6409418/ | https://academic.oup.com/biostatistics/article/20/2/273/4817524
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84.
SofproMed. Phase 3 cost per trial range.
SofproMed https://www.sofpromed.com/how-much-does-a-clinical-trial-cost Phase 3 clinical trials cost between $20 million and $282 million per trial, with significant variation by therapeutic area and trial complexity. Additional sources: https://www.sofpromed.com/how-much-does-a-clinical-trial-cost | https://www.cbo.gov/publication/57126
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85.
PMC. Pragmatic trial cost per patient (median $97).
PMC: Costs of Pragmatic Clinical Trials https://pmc.ncbi.nlm.nih.gov/articles/PMC6508852/ The median cost per participant was $97 (IQR $19–$478), based on 2015 dollars. Systematic review of 64 embedded pragmatic clinical trials. 25% of trials cost <$19/patient; 10 trials exceeded $1,000/patient. U.S. studies median $187 vs non-U.S. median $27. Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC6508852/
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86.
WHO. Polio vaccination ROI.
WHO https://www.who.int/news-room/feature-stories/detail/sustaining-polio-investments-offers-a-high-return (2019)
For every dollar spent, the return on investment is nearly US$ 39." Total investment cost of US$ 7.5 billion generates projected economic and social benefits of US$ 289.2 billion from sustaining polio assets and integrating them into expanded immunization, surveillance and emergency response programmes across 8 priority countries (Afghanistan, Iraq, Libya, Pakistan, Somalia, Sudan, Syria, Yemen). Additional sources: https://www.who.int/news-room/feature-stories/detail/sustaining-polio-investments-offers-a-high-return
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88.
Hayek, F. A.
The use of knowledge in society.
American Economic Review 35, 519–530 (1945)
The knowledge of the circumstances which we must make use of never exists in concentrated or integrated form but solely as dispersed bits of incomplete and frequently contradictory knowledge which all the separate individuals possess.
89.
Kydland, F. E. & Prescott, E. C.
Rules rather than discretion: The inconsistency of optimal plans.
Journal of Political Economy 85, 473–492 (1977)
Time-inconsistency describes situations where, with the passing of time, policies that were determined to be optimal yesterday are no longer perceived to be optimal today and are not implemented... This insight shifted the focus of policy analysis from the study of individual policy decisions to the design of institutions that mitigate the time consistency problem.
90.
ICRC. International campaign to ban landmines (ICBL) - ottawa treaty (1997).
ICRC https://www.icrc.org/en/doc/resources/documents/article/other/57jpjn.htm (1997)
ICBL: Founded 1992 by 6 NGOs (Handicap International, Human Rights Watch, Medico International, Mines Advisory Group, Physicians for Human Rights, Vietnam Veterans of America Foundation) Started with ONE staff member: Jody Williams as founding coordinator Grew to 1,000+ organizations in 60 countries by 1997 Ottawa Process: 14 months (October 1996 - December 1997) Convention signed by 122 states on December 3, 1997; entered into force March 1, 1999 Achievement: Nobel Peace Prize 1997 (shared by ICBL and Jody Williams) Government funding context: Canada established $100M CAD Canadian Landmine Fund over 10 years (1997); International donors provided $169M in 1997 for mine action (up from $100M in 1996) Additional sources: https://www.icrc.org/en/doc/resources/documents/article/other/57jpjn.htm | https://en.wikipedia.org/wiki/International_Campaign_to_Ban_Landmines | https://www.nobelprize.org/prizes/peace/1997/summary/ | https://un.org/press/en/1999/19990520.MINES.BRF.html | https://www.the-monitor.org/en-gb/reports/2003/landmine-monitor-2003/mine-action-funding.aspx
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91.
OpenSecrets.
Revolving door: Former members of congress. (2024)
388 former members of Congress are registered as lobbyists. Nearly 5,400 former congressional staffers have left Capitol Hill to become federal lobbyists in the past 10 years. Additional sources: https://www.opensecrets.org/revolving-door
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92.
Kinch, M. S. & Griesenauer, R. H.
Lost medicines: A longer view of the pharmaceutical industry with the potential to reinvigorate discovery.
Drug Discovery Today 24, 875–880 (2019)
Research identified 1,600+ medicines available in 1962. The 1950s represented industry high-water mark with >30 new products in five of ten years; this rate would not be replicated until late 1990s. More than half (880) of these medicines were lost following implementation of Kefauver-Harris Amendment. The peak of 1962 would not be seen again until early 21st century. By 2016 number of organizations actively involved in R&D at level not seen since 1914.
93.
Wikipedia. US military spending reduction after WWII.
Wikipedia https://en.wikipedia.org/wiki/Demobilization_of_United_States_Armed_Forces_after_World_War_II (2020)
Peaking at over $81 billion in 1945, the U.S. military budget plummeted to approximately $13 billion by 1948, representing an 84% decrease. The number of personnel was reduced almost 90%, from more than 12 million to about 1.5 million between mid-1945 and mid-1947. Defense spending exceeded 41 percent of GDP in 1945. After World War II, the US reduced military spending to 7.2 percent of GDP by 1948. Defense spending doubled from the 1948 low to 15 percent at the height of the Korean War in 1953. Additional sources: https://en.wikipedia.org/wiki/Demobilization_of_United_States_Armed_Forces_after_World_War_II | https://www.americanprogress.org/article/a-historical-perspective-on-military-budgets/ | https://www.stlouisfed.org/on-the-economy/2020/february/war-highest-military-spending-measured | https://www.usgovernmentspending.com/defense_spending_history
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94.
Baily, M. N. Pre-1962 drug development costs (baily 1972).
Baily (1972) https://samizdathealth.org/wp-content/uploads/2020/12/hlthaff.1.2.6.pdf (1972)
Pre-1962: Average cost per new chemical entity (NCE) was $6.5 million (1980 dollars) Inflation-adjusted to 2024 dollars: $6.5M (1980) ≈ $22.5M (2024), using CPI multiplier of 3.46× Real cost increase (inflation-adjusted): $22.5M (pre-1962) → $2,600M (2024) = 116× increase Note: This represents the most comprehensive academic estimate of pre-1962 drug development costs based on empirical industry data Additional sources: https://samizdathealth.org/wp-content/uploads/2020/12/hlthaff.1.2.6.pdf
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95.
Numbers, T. by. Pre-1962 physician-led clinical trials.
Think by Numbers: How Many Lives Does FDA Save? https://thinkbynumbers.org/health/how-many-net-lives-does-the-fda-save/ (1966)
Pre-1962: Physicians could report real-world evidence directly 1962 Drug Amendments replaced "premarket notification" with "premarket approval", requiring extensive efficacy testing Impact: New regulatory clampdown reduced new treatment production by 70%; lifespan growth declined from 4 years/decade to 2 years/decade Drug Efficacy Study Implementation (DESI): NAS/NRC evaluated 3,400+ drugs approved 1938-1962 for safety only; reviewed >3,000 products, >16,000 therapeutic claims FDA has had authority to accept real-world evidence since 1962, clarified by 21st Century Cures Act (2016) Note: Specific "144,000 physicians" figure not verified in sources Additional sources: https://thinkbynumbers.org/health/how-many-net-lives-does-the-fda-save/ | https://www.fda.gov/drugs/enforcement-activities-fda/drug-efficacy-study-implementation-desi | http://www.nasonline.org/about-nas/history/archives/collections/des-1966-1969-1.html
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96.
GAO. 95% of diseases have 0 FDA-approved treatments.
GAO https://www.gao.gov/products/gao-25-106774 (2025)
95% of diseases have no treatment Additional sources: https://www.gao.gov/products/gao-25-106774 | https://globalgenes.org/rare-disease-facts/
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98.
al., N. E. Á. et. RECOVERY trial global lives saved ( 1 million).
NHS England: 1 Million Lives Saved https://www.england.nhs.uk/2021/03/covid-treatment-developed-in-the-nhs-saves-a-million-lives/ (2021)
Dexamethasone saved 1 million lives worldwide (NHS England estimate, March 2021, 9 months after discovery). UK alone: 22,000 lives saved. Methodology: Águas et al. Nature Communications 2021 estimated 650,000 lives (range: 240,000-1,400,000) for July-December 2020 alone, based on RECOVERY trial mortality reductions (36% for ventilated, 18% for oxygen-only patients) applied to global COVID hospitalizations. June 2020 announcement: Dexamethasone reduced deaths by up to 1/3 (ventilated patients), 1/5 (oxygen patients). Impact immediate: Adopted into standard care globally within hours of announcement. Additional sources: https://www.england.nhs.uk/2021/03/covid-treatment-developed-in-the-nhs-saves-a-million-lives/ | https://www.nature.com/articles/s41467-021-21134-2 | https://pharmaceutical-journal.com/article/news/steroid-has-saved-the-lives-of-one-million-covid-19-patients-worldwide-figures-show | https://www.recoverytrial.net/news/recovery-trial-celebrates-two-year-anniversary-of-life-saving-dexamethasone-result
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99.
Museum, N. S. 11. M. &.
September 11 attack facts. (2024)
2,977 people were killed in the September 11, 2001 attacks: 2,753 at the World Trade Center, 184 at the Pentagon, and 40 passengers and crew on United Flight 93 in Shanksville, Pennsylvania.
100.
Bank, W. World bank singapore economic data.
World Bank https://data.worldbank.org/country/singapore (2024)
Singapore GDP per capita (2023): $82,000 - among highest in the world Government spending: 15% of GDP (vs US 38%) Life expectancy: 84.1 years (vs US 77.5 years) Singapore demonstrates that low government spending can coexist with excellent outcomes Additional sources: https://data.worldbank.org/country/singapore
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101.
Fund, I. M.
IMF singapore government spending data. (2024)
Singapore government spending is approximately 15% of GDP This is 23 percentage points lower than the United States (38%) Despite lower spending, Singapore achieves excellent outcomes: - Life expectancy: 84.1 years (vs US 77.5) - Low crime, world-class infrastructure, AAA credit rating Additional sources: https://www.imf.org/en/Countries/SGP
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102.
Organization, W. H.
WHO life expectancy data by country. (2024)
Life expectancy at birth varies significantly among developed nations: Switzerland: 84.0 years (2023) Singapore: 84.1 years (2023) Japan: 84.3 years (2023) United States: 77.5 years (2023) - 6.5 years below Switzerland, Singapore Global average: 73 years Note: US spends more per capita on healthcare than any other nation, yet achieves lower life expectancy Additional sources: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-life-expectancy-and-healthy-life-expectancy
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104.
PMC. Contribution of smoking reduction to life expectancy gains.
PMC: Benefits Smoking Cessation Longevity https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1447499/ (2012)
Population-level: Up to 14% (9% men, 14% women) of total life expectancy gain since 1960 due to tobacco control efforts Individual cessation benefits: Quitting at age 35 adds 6.9-8.5 years (men), 6.1-7.7 years (women) vs continuing smokers By cessation age: Age 25-34 = 10 years gained; age 35-44 = 9 years; age 45-54 = 6 years; age 65 = 2.0 years (men), 3.7 years (women) Cessation before age 40: Reduces death risk by 90% Long-term cessation: 10+ years yields survival comparable to never smokers, averts 10 years of life lost Recent cessation: <3 years averts 5 years of life lost Additional sources: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1447499/ | https://www.cdc.gov/pcd/issues/2012/11_0295.htm | https://www.ajpmonline.org/article/S0749-3797(24 | https://www.nejm.org/doi/full/10.1056/NEJMsa1211128
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105.
ICER. Value per QALY (standard economic value).
ICER https://icer.org/wp-content/uploads/2024/02/Reference-Case-4.3.25.pdf (2024)
Standard economic value per QALY: $100,000–$150,000. This is the US and global standard willingness-to-pay threshold for interventions that add costs. Dominant interventions (those that save money while improving health) are favorable regardless of this threshold. Additional sources: https://icer.org/wp-content/uploads/2024/02/Reference-Case-4.3.25.pdf
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106.
GAO. Annual cost of u.s. Sugar subsidies.
GAO: Sugar Program https://www.gao.gov/products/gao-24-106144 Consumer costs: $2.5-3.5 billion per year (GAO estimate) Net economic cost: $1 billion per year 2022: US consumers paid 2X world price for sugar Program costs $3-4 billion/year but no federal budget impact (costs passed directly to consumers via higher prices) Employment impact: 10,000-20,000 manufacturing jobs lost annually in sugar-reliant industries (confectionery, etc.) Multiple studies confirm: Sweetener Users Association ($2.9-3.5B), AEI ($2.4B consumer cost), Beghin & Elobeid ($2.9-3.5B consumer surplus) Additional sources: https://www.gao.gov/products/gao-24-106144 | https://www.heritage.org/agriculture/report/the-us-sugar-program-bad-consumers-bad-agriculture-and-bad-america | https://www.aei.org/articles/the-u-s-spends-4-billion-a-year-subsidizing-stalinist-style-domestic-sugar-production/
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107.
Bank, W. Swiss military budget as percentage of GDP.
World Bank: Military Expenditure https://data.worldbank.org/indicator/MS.MIL.XPND.GD.ZS?locations=CH 2023: 0.70272% of GDP (World Bank) 2024: CHF 5.95 billion official military spending When including militia system costs: 1% GDP (CHF 8.75B) Comparison: Near bottom in Europe; only Ireland, Malta, Moldova spend less (excluding microstates with no armies) Additional sources: https://data.worldbank.org/indicator/MS.MIL.XPND.GD.ZS?locations=CH | https://www.avenir-suisse.ch/en/blog-defence-spending-switzerland-is-in-better-shape-than-it-seems/ | https://tradingeconomics.com/switzerland/military-expenditure-percent-of-gdp-wb-data.html
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108.
Bank, W. Switzerland vs. US GDP per capita comparison.
World Bank: Switzerland GDP Per Capita https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?locations=CH 2024 GDP per capita (PPP-adjusted): Switzerland $93,819 vs United States $75,492 Switzerland’s GDP per capita 24% higher than US when adjusted for purchasing power parity Nominal 2024: Switzerland $103,670 vs US $85,810 Additional sources: https://data.worldbank.org/indicator/NY.GDP.PCAP.CD?locations=CH | https://tradingeconomics.com/switzerland/gdp-per-capita-ppp | https://www.theglobaleconomy.com/USA/gdp_per_capita_ppp/
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109.
Economic Co-operation, O. for & Development.
OECD government spending as percentage of GDP. (2024)
OECD government spending data shows significant variation among developed nations: United States: 38.0% of GDP (2023) Switzerland: 35.0% of GDP - 3 percentage points lower than US Singapore: 15.0% of GDP - 23 percentage points lower than US (per IMF data) OECD average: approximately 40% of GDP Additional sources: https://data.oecd.org/gga/general-government-spending.htm
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110.
Economic Co-operation, O. for & Development.
OECD median household income comparison. (2024)
Median household disposable income varies significantly across OECD nations: United States: $77,500 (2023) Switzerland: $55,000 PPP-adjusted (lower nominal but comparable purchasing power) Singapore: $75,000 PPP-adjusted Additional sources: https://data.oecd.org/hha/household-disposable-income.htm
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111.
Institute, C. Chance of dying from terrorism statistic.
Cato Institute: Terrorism and Immigration Risk Analysis https://www.cato.org/policy-analysis/terrorism-immigration-risk-analysis Chance of American dying in foreign-born terrorist attack: 1 in 3.6 million per year (1975-2015) Including 9/11 deaths; annual murder rate is 253x higher than terrorism death rate More likely to die from lightning strike than foreign terrorism Note: Comprehensive 41-year study shows terrorism risk is extremely low compared to everyday dangers Additional sources: https://www.cato.org/policy-analysis/terrorism-immigration-risk-analysis | https://www.nbcnews.com/news/us-news/you-re-more-likely-die-choking-be-killed-foreign-terrorists-n715141
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112.
Wikipedia. Thalidomide scandal: Worldwide cases and mortality.
Wikipedia https://en.wikipedia.org/wiki/Thalidomide_scandal The total number of embryos affected by the use of thalidomide during pregnancy is estimated at 10,000, of whom about 40% died around the time of birth. More than 10,000 children in 46 countries were born with deformities such as phocomelia. Additional sources: https://en.wikipedia.org/wiki/Thalidomide_scandal
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113.
One, P. Health and quality of life of thalidomide survivors as they age.
PLOS One https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0210222 (2019)
Study of thalidomide survivors documenting ongoing disability impacts, quality of life, and long-term health outcomes. Survivors (now in their 60s) continue to experience significant disability from limb deformities, organ damage, and other effects. Additional sources: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0210222
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115.
NCBI, F. S. via. Trial costs, FDA study.
FDA Study via NCBI https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6248200/ Overall, the 138 clinical trials had an estimated median (IQR) cost of \(19.0 million (\)12.2 million-\(33.1 million)... The clinical trials cost a median (IQR) of\)41,117 (\(31,802-\)82,362) per patient. Additional sources: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6248200/
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116.
GBD 2019 Diseases and Injuries Collaborators.
Global burden of disease study 2019: Disability weights.
The Lancet 396, 1204–1222 (2020)
Disability weights for 235 health states used in Global Burden of Disease calculations. Weights range from 0 (perfect health) to 1 (death equivalent). Chronic conditions like diabetes (0.05-0.35), COPD (0.04-0.41), depression (0.15-0.66), and cardiovascular disease (0.04-0.57) show substantial variation by severity. Treatment typically reduces disability weights by 50-80 percent for manageable chronic conditions.
117.
WHO. Annual global economic burden of alzheimer’s and other dementias.
WHO: Dementia Fact Sheet https://www.who.int/news-room/fact-sheets/detail/dementia (2019)
Global cost: $1.3 trillion (2019 WHO-commissioned study) 50% from informal caregivers (family/friends, 5 hrs/day) 74% of costs in high-income countries despite 61% of patients in LMICs $818B (2010) → $1T (2018) → $1.3T (2019) - rapid growth Note: Costs increased 35% from 2010-2015 alone. Informal care represents massive hidden economic burden Additional sources: https://www.who.int/news-room/fact-sheets/detail/dementia | https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.12901
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118.
Oncology, J. Annual global economic burden of cancer.
JAMA Oncology: Global Cost 2020-2050 https://jamanetwork.com/journals/jamaoncology/fullarticle/2801798 (2020)
2020-2050 projection: $25.2 trillion total ($840B/year average) 2010 annual cost: $1.16 trillion (direct costs only) Recent estimate: $3 trillion/year (all costs included) Top 5 cancers: lung (15.4%), colon/rectum (10.9%), breast (7.7%), liver (6.5%), leukemia (6.3%) Note: China/US account for 45% of global burden; 75% of deaths in LMICs but only 50.0% of economic cost Additional sources: https://jamanetwork.com/journals/jamaoncology/fullarticle/2801798 | https://www.nature.com/articles/d41586-023-00634-9
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120.
Care, D. Annual global economic burden of diabetes.
Diabetes Care: Global Economic Burden https://diabetesjournals.org/care/article/41/5/963/36522/Global-Economic-Burden-of-Diabetes-in-Adults 2015: $1.3 trillion (1.8% of global GDP) 2030 projections: $2.1T-2.5T depending on scenario IDF health expenditure: $760B (2019) → $845B (2045 projected) 2/3 direct medical costs ($857B), 1/3 indirect costs (lost productivity) Note: Costs growing rapidly; expected to exceed $2T by 2030 Additional sources: https://diabetesjournals.org/care/article/41/5/963/36522/Global-Economic-Burden-of-Diabetes-in-Adults | https://www.thelancet.com/journals/landia/article/PIIS2213-8587(17
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121.
World Bank, B. of E. A. US GDP 2024 ($28.78 trillion).
World Bank https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?locations=US (2024)
US GDP reached $28.78 trillion in 2024, representing approximately 26% of global GDP. Additional sources: https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?locations=US | https://www.bea.gov/news/2024/gross-domestic-product-fourth-quarter-and-year-2024-advance-estimate
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122.
Cardiology, I. J. of. Annual global economic burden of heart disease.
Int’l Journal of Cardiology: Global Heart Failure Burden02238-9/abstract) https://www.internationaljournalofcardiology.com/article/S0167-5273(13 (2050)
Heart failure alone: $108 billion/year (2012 global analysis, 197 countries) US CVD: $555B (2016) → projected $1.8T by 2050 LMICs total CVD loss: $3.7T cumulative (2011-2015, 5-year period) CVD is costliest disease category in most developed nations Note: No single $2.1T global figure found; estimates vary widely by scope and year Additional sources: https://www.internationaljournalofcardiology.com/article/S0167-5273(13 | https://www.ahajournals.org/doi/10.1161/CIR.0000000000001258
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123.
CSV, S. U. L. E. F. B. 1543-2019.
US life expectancy growth 1880-1960: 3.82 years per decade. (2019)
Pre-1962: 3.82 years/decade Post-1962: 1.54 years/decade Reduction: 60% decline in life expectancy growth rate Additional sources: https://ourworldindata.org/life-expectancy | https://www.mortality.org/ | https://www.cdc.gov/nchs/nvss/mortality_tables.htm
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124.
CSV, S. U. L. E. F. B. 1543-2019.
Post-1962 slowdown in life expectancy gains. (2019)
Pre-1962 (1880-1960): 3.82 years/decade Post-1962 (1962-2019): 1.54 years/decade Reduction: 60% decline Temporal correlation: Slowdown occurred immediately after 1962 Kefauver-Harris Amendment See detailed calculation: [life-expectancy-increase-pre-1962](#life-expectancy-increase-pre-1962) Additional sources: https://ourworldindata.org/life-expectancy | https://www.mortality.org/ | https://www.cdc.gov/nchs/nvss/mortality_tables.htm
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125.
Disease Control, C. for & Prevention.
US life expectancy 2023. (2024)
US life expectancy at birth was 77.5 years in 2023 Male life expectancy: 74.8 years Female life expectancy: 80.2 years This is 6-7 years lower than peer developed nations despite higher healthcare spending Additional sources: https://www.cdc.gov/nchs/fastats/life-expectancy.htm
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126.
Bureau, U. C.
US median household income 2023. (2024)
US median household income was $77,500 in 2023 Real median household income declined 0.8% from 2022 Gini index: 0.467 (income inequality measure) Additional sources: https://www.census.gov/library/publications/2024/demo/p60-282.html
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127.
Statista. US military budget as percentage of GDP.
Statista https://www.statista.com/statistics/262742/countries-with-the-highest-military-spending/ (2024)
U.S. military spending amounted to 3.5% of GDP in 2024. In 2024, the U.S. spent nearly $1 trillion on its military budget, equal to 3.4% of GDP. Additional sources: https://www.statista.com/statistics/262742/countries-with-the-highest-military-spending/ | https://www.sipri.org/sites/default/files/2025-04/2504_fs_milex_2024.pdf
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128.
Bureau, U. C. Number of registered or eligible voters in the u.s.
US Census Bureau https://www.census.gov/newsroom/press-releases/2025/2024-presidential-election-voting-registration-tables.html (2024)
73.6% (or 174 million people) of the citizen voting-age population was registered to vote in 2024 (Census Bureau). More than 211 million citizens were active registered voters (86.6% of citizen voting age population) according to the Election Assistance Commission. Additional sources: https://www.census.gov/newsroom/press-releases/2025/2024-presidential-election-voting-registration-tables.html | https://www.eac.gov/news/2025/06/30/us-election-assistance-commission-releases-2024-election-administration-and-voting
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129.
Senate, U. S. Treaties.
U.S. Senate https://www.senate.gov/about/powers-procedures/treaties.htm The Constitution provides that the president ’shall have Power, by and with the Advice and Consent of the Senate, to make Treaties, provided two-thirds of the Senators present concur’ (Article II, section 2). Treaties are formal agreements with foreign nations that require two-thirds Senate approval. 67 senators (two-thirds of 100) must vote to ratify a treaty for it to take effect. Additional sources: https://www.senate.gov/about/powers-procedures/treaties.htm
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130.
Commission, F. E.
Statistical summary of 24-month campaign activity of the 2023-2024 election cycle. (2023)
Presidential candidates raised $2 billion; House and Senate candidates raised $3.8 billion and spent $3.7 billion; PACs raised $15.7 billion and spent $15.5 billion. Total federal campaign spending approximately $20 billion. Additional sources: https://www.fec.gov/updates/statistical-summary-of-24-month-campaign-activity-of-the-2023-2024-election-cycle/
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131.
OpenSecrets.
Federal lobbying hit record $4.4 billion in 2024. (2024)
Total federal lobbying reached record $4.4 billion in 2024. The $150 million increase in lobbying continues an upward trend that began in 2016. Additional sources: https://www.opensecrets.org/news/2025/02/federal-lobbying-set-new-record-in-2024/
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132.
Kirk (2011), H. &.
Valley of death in drug development. (2011)
The overall failure rate of drugs that passed into Phase 1 trials to final approval is 90%. This lack of translation from promising preclinical findings to success in human trials is known as the "valley of death." Estimated 30-50% of promising compounds never proceed to Phase 2/3 trials primarily due to funding barriers rather than scientific failure. The late-stage attrition rate for oncology drugs is as high as 70% in Phase II and 59% in Phase III trials.
133.
DOT. DOT value of statistical life ($13.6M).
DOT: VSL Guidance 2024 https://www.transportation.gov/office-policy/transportation-policy/revised-departmental-guidance-on-valuation-of-a-statistical-life-in-economic-analysis (2024)
Current VSL (2024): $13.7 million (updated from $13.6M) Used in cost-benefit analyses for transportation regulations and infrastructure Methodology updated in 2013 guidance, adjusted annually for inflation and real income VSL represents aggregate willingness to pay for safety improvements that reduce fatalities by one Note: DOT has published VSL guidance periodically since 1993. Current $13.7M reflects 2024 inflation/income adjustments Additional sources: https://www.transportation.gov/office-policy/transportation-policy/revised-departmental-guidance-on-valuation-of-a-statistical-life-in-economic-analysis | https://www.transportation.gov/regulations/economic-values-used-in-analysis
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134.
ONE, P. Cost per DALY for vitamin a supplementation.
PLOS ONE: Cost-effectiveness of "Golden Mustard" for Treating Vitamin A Deficiency in India (2010) https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0012046 (2010)
India: $23-$50 per DALY averted (least costly intervention, $1,000-$6,100 per death averted) Sub-Saharan Africa (2022): $220-$860 per DALY (Burkina Faso: $220, Kenya: $550, Nigeria: $860) WHO estimates for Africa: $40 per DALY for fortification, $255 for supplementation Uganda fortification: $18-$82 per DALY (oil: $18, sugar: $82) Note: Wide variation reflects differences in baseline VAD prevalence, coverage levels, and whether intervention is supplementation or fortification Additional sources: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0012046 | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0266495
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136.
PMC. Cost-effectiveness threshold ($50,000/QALY).
PMC https://pmc.ncbi.nlm.nih.gov/articles/PMC5193154/ The $50,000/QALY threshold is widely used in US health economics literature, originating from dialysis cost benchmarks in the 1980s. In US cost-utility analyses, 77.5% of authors use either $50,000 or $100,000 per QALY as reference points. Most successful health programs cost $3,000-10,000 per QALY. WHO-CHOICE uses GDP per capita multiples (1× GDP/capita = "very cost-effective", 3× GDP/capita = "cost-effective"), which for the US ( $70,000 GDP/capita) translates to $70,000-$210,000/QALY thresholds. Additional sources: https://pmc.ncbi.nlm.nih.gov/articles/PMC5193154/ | https://pmc.ncbi.nlm.nih.gov/articles/PMC9278384/
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137.
Institute, I. B. Chronic illness workforce productivity loss.
Integrated Benefits Institute 2024 https://www.ibiweb.org/resources/chronic-conditions-in-the-us-workforce-prevalence-trends-and-productivity-impacts (2024)
78.4% of U.S. employees have at least one chronic condition (7% increase since 2021) 58% of employees report physical chronic health conditions 28% of all employees experience productivity loss due to chronic conditions Average productivity loss: $4,798 per employee per year Employees with 3+ chronic conditions miss 7.8 days annually vs 2.2 days for those without Note: 28% productivity loss translates to roughly 11 hours per week (28% of 40-hour workweek) Additional sources: https://www.ibiweb.org/resources/chronic-conditions-in-the-us-workforce-prevalence-trends-and-productivity-impacts | https://www.onemedical.com/mediacenter/study-finds-more-than-half-of-employees-are-living-with-chronic-conditions-including-1-in-3-gen-z-and-millennial-employees/ | https://debeaumont.org/news/2025/poll-the-toll-of-chronic-health-conditions-on-employees-and-workplaces/
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