The Survey to End War and Disease
war-on-disease, 1-percent-treaty, medical-research, public-health, peace-dividend, decentralized-trials, dfda, dih, victory-bonds, health-economics, cost-benefit-analysis, clinical-trials, drug-development, regulatory-reform, military-spending, peace-economics, decentralized-governance, wishocracy, blockchain-governance, impact-investing
1. Should every patient be able to join a pragmatic clinical trial of any promising treatment through their regular doctor, with informed consent?
Why we ask: Most patients cannot join a trial because no trial exists at their hospital. The right to try a treatment you cannot access is the right to board a flight that does not exist. If every provider could enroll patients, every treatment gets a running scorecard: how much it helps, what side effects it causes, and what it costs, ranked against every other treatment for the same condition.
Prediction: Before the 2018 federal Right to Try Act, 41 US states had already passed right-to-try laws1.
If a majority of humanity says yes: Legislators remove the legal barriers. Hospitals can enroll patients through a shared reporting system, allowing each tested treatment to accumulate a public outcome label: measured changes from baseline across all positive and negative effects, ranked against alternatives.
Evidence and calculations: Ubiquitous Pragmatic Trial Impact Analysis2
2. Most promising treatments are never tested, because no company can profit from testing them. Should patients be allowed to fund and join trials of treatments for their own disease?
Why we ask: 95% of diseases have zero FDA-approved treatments3. At current speed, testing every promising treatment takes 443 years (90% CI: 255 years-841 years). A trial needs money. If no company can patent the treatment, no company pays, and it stays on a shelf.
Prediction: No direct polling exists. Access to unapproved treatments polls between 54% and 90% depending on framing, but those polls did not test patient funding or its equity implications.
If a majority of humanity says yes: Regulators can permit patient-funded trials without political risk. Treatments with no patent value get tested.
Evidence and calculations: Appendix: Calculations2
3. How should public money be divided between these two uses?
- Weapons and military spending
- Pragmatic clinical trials comparing promising treatments
Pragmatic clinical trials: Your doctor enrolls you. The trial runs through ordinary care instead of a special facility. It costs less. Every treatment gets a public outcome label showing all measured effects, positive and negative.
Why we ask: Disease costs about 13% of global GDP. Military, conflict, and security spending consumes 11.5% of GDP and grows faster than the productive economy4. Weapons become obsolete. Treatments compound. Oxford’s RECOVERY trial tested 6 treatments on 48,000 patients at about $500 (95% CI: $400-$2,500) per patient versus roughly $41,000 (95% CI: $20,000-$120,000) for a conventional Phase III trial. That is a cost reduction of about 82x (90% CI: 21.4x-195x). After WW2, the US cut military spending by 87.6% in two years and stumbled into the largest economic boom in its history. This survey asks about 1%.
Prediction: Most people allocate more than the 0.17% that goes to clinical trials today. In US polling, 57% supported cutting the military budget by 10% to fund health and other domestic needs5.
If the median allocation gives trials at least 1 percentage point more than today’s share: That is a global mandate for the 1% reallocation: $27.2 billion per year for pragmatic trials, a 12.3x (90% CI: 4.92x-50.8x) increase in trial capacity, and a timeline drop from 443 years (90% CI: 255 years-841 years) to 36 years (90% CI: 8.15 years-106 years). Even after discounting for the chance it never happens politically, the reallocation would cost $1.99 (90% CI: $0.37-$38) per healthy year of life saved6. Vaccinating a child costs $30. A bed net costs $184 (90% CI: $113-$252).
Evidence and calculations: Allocation Impact Analysis6
4. Should governments collect and analyze data on how their policies and budgets affect median healthy life years and real after-tax median income, using the natural variation across thousands of jurisdictions to determine which policies work best?
Why we ask: Thousands of jurisdictions have adopted different policies at different times: different tax rates, drug laws, education budgets, healthcare systems. The outcomes are recorded. Together, these policy differences provide quasi-experimental evidence that can help estimate which policies improve median healthy life years and real after-tax median income. Governments do not systematically analyze these outcomes to identify better policies.
Prediction: In US polling, 91% of voters agree that data and evidence should be a top influence in government policy, bipartisan7. The specific mandate to analyze cross-jurisdictional outcomes has not been polled.
If a majority of humanity says yes: The Optimal Policy Generator uses causal inference on this cross-jurisdictional data to determine which policies improved median healthy life years and real after-tax median income and which did not, then produces recommendations for any jurisdiction: enact, replace, repeal, or keep8. The Optimal Budget Generator does the same for spending levels9. The recommendations and the votes are both public.
Evidence and calculations: Optimal Policy Generator8
5. If government action kills or injures your family, should you have the same right to sue as if a corporation did it?
Why we ask: Since 1900, governments have spent $170 trillion on the capacity to kill people and used it to kill 310 million of them, including 102 million children. The chance of dying from terrorism is 1 in 30 million10. The chance of dying from disease is 100%. Governments built the military around the first number. If a company made this trade, you could sue. Sovereign immunity means that when a government does it, you mostly cannot11.
Prediction: In adjacent US polling, 63% favor ending qualified immunity for government officials12 and 66% favor giving civilians the power to sue officers for misconduct13. The equal-treatment framing in this question has not been directly polled.
If a majority of humanity says yes: A global consensus removes the assumption that sustains immunity: that everyone else accepts it. That creates a mandate to establish a court where states face the same liability as corporations.
Evidence and calculations: Appendix: Calculations14
Why counting matters
A majority can exist and not know it exists. Pluralistic ignorance15 can make a majority believe it is a minority. The uncertainty remains until somebody counts.
Erica Chenoweth studied every major nonviolent campaign of the last century and found that none had ever failed after achieving 3.5% (95% CI: 1%-10%) sustained participation16. Not one.
What happens if all five pass
If the 1% reallocation happens, the models project global GDP of $322 trillion (90% CI: $245 trillion-$404 trillion) and average income of $34,972 (90% CI: $26,587-$43,903) in year 204. If every institution the mandate enables works as modeled, year-20 global GDP is $10.7 quadrillion (90% CI: $3.95 quadrillion-$28 quadrillion) and median after-tax income is $194,130 (90% CI: $70,137-$507,535)4. The second number’s growth assumptions are outside historical precedent.
Costs
A verified response costs $6.5 (90% CI: $4-$9.14): $1.5 (95% CI: $1-$3) for identity verification and processing, $5 (95% CI: $2-$10) for incentives. Organizations that distribute the questions receive compensation per verified response; terms are in the Organization Kit. If the treaty passes, each response corresponds to 2.6 lives saved, at $2.5 (90% CI: $1.12-$4.68) per life.
Appendix: Calculations
The 0.17%. Military spending is 604 (90% CI: 453-888) times government clinical trial spending, so trials receive roughly 1/604 of what weapons receive:
\[ \begin{gathered} Ratio_{mil:gov} \\ = \frac{Spending_{mil}}{Spending_{trials,gov}} \\ = \frac{\$2.72T}{\$4.5B} \\ = 604 \end{gathered} \]
The RECOVERY cost reduction:
\[ \begin{gathered} k_{RECOVERY} \\ = \frac{Cost_{P3,pt}}{Cost_{RECOVERY,pt}} \\ = \frac{\$41K}{\$500} \\ = 82 \end{gathered} \]
Annual funding from a 1% reallocation:
\[ \begin{gathered} Funding_{treaty} \\ = Spending_{mil} \times Reduce_{treaty} \\ = \$2.72T \times 1\% \\ = \$27.2B \end{gathered} \]
The treatment-testing timeline, including the status quo 443-year estimate and the 12.3x (90% CI: 4.92x-50.8x) capacity multiplier it improves on:
\[
\begin{gathered}
T_{queue,trial} \\
= \frac{T_{queue,SQ}}{k_{capacity}} \\
= \frac{443}{12.3} \\
= 36
\end{gathered}
\]
where:
\[
\begin{gathered}
T_{queue,SQ} \\
= \frac{N_{untreated}}{Treatments_{new,ann}} \\
= \frac{6{,}650}{15} \\
= 443
\end{gathered}
\]
where:
\[
\begin{gathered}
N_{untreated} \\
= N_{rare} \times 0.95 \\
= 7{,}000 \times 0.95 \\
= 6{,}650
\end{gathered}
\]
where:
\[
\begin{gathered}
k_{capacity} \\
= \frac{N_{fundable,ref}}{Slots_{curr}} \\
= \frac{23.4M}{1.9M} \\
= 12.3
\end{gathered}
\]
where:
\[
\begin{gathered}
N_{fundable,ref} \\
= \frac{Subsidies_{trial,ref}}{Cost_{pragmatic,pt}} \\
= \frac{\$21.8B}{\$929} \\
= 23.4M
\end{gathered}
\]
where:
\[
\begin{gathered}
Subsidies_{trial,ref} \\
= Funding_{trial,ref} - OPEX_{trial} \\
= \$21.8B - \$40M \\
= \$21.8B
\end{gathered}
\]
where:
\[
\begin{gathered}
OPEX_{trial} \\
= Cost_{platform} + Cost_{staff} + Cost_{infra} \\
+ Cost_{regulatory} + Cost_{community} \\
= \$15M + \$10M + \$8M + \$5M + \$2M \\
= \$40M
\end{gathered}
\]
Cumulative military spending expressed in years of clinical trial funding:
\[ \begin{gathered} Years_{mil \to trials,gov} \\ = \frac{Spending_{mil,cum,fed}}{Spending_{trials,gov}} \\ = \frac{\$170T}{\$4.5B} \\ = 37{,}800 \end{gathered} \]
Source citations for all quantities are in the parameter registry.