# Vida's Knowledge Frontier

**Last updated:** 2026-03-16 (first self-audit)

These are the gaps in Vida's health domain knowledge base, ranked by impact on active beliefs. Each gap is a contribution invitation — if you have evidence, experience, or analysis that addresses one of these, the collective wants it.

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## 1. Behavioral Health Infrastructure Mechanisms

**Why it matters:** Belief 2 — "80-90% of health outcomes are non-clinical" — depends on non-clinical interventions actually working at scale. The health KB has strong evidence that medical care explains only 10-20% of outcomes, but almost nothing about WHAT works to change the other 80-90%.

**What's missing:**
- Community health worker program outcomes (ROI, scalability, retention)
- Social prescribing mechanisms and evidence (UK Link Workers, international models)
- Digital therapeutics for behavior change (post-PDT market failure — what survived?)
- Behavioral economics of health (commitment devices, default effects, incentive design)
- Food-as-medicine programs (Geisinger Fresh Food Farmacy, produce prescription ROI)

**Adjacent claims:**
- medical care explains only 10-20 percent of health outcomes...
- SDOH interventions show strong ROI but adoption stalls...
- social isolation costs Medicare 7 billion annually...
- modernization dismantles family and community structures...

**Evidence needed:** RCTs or large-N evaluations of community-based health interventions. Cost-effectiveness analyses. Implementation science on what makes SDOH programs scale vs stall.

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## 2. International and Comparative Health Systems

**Why it matters:** Every structural claim in the health KB is US-only. This limits generalizability and misses natural experiments that could strengthen or challenge the attractor state thesis.

**What's missing:**
- Singapore's 3M system (Medisave/Medishield/Medifund) — consumer-directed with catastrophic coverage
- Costa Rica's EBAIS primary care model — universal coverage at 8% of US per-capita spend
- Japan's Long-Term Care Insurance — aging population, community-based care at scale
- NHS England — what underfunding + wait times reveal about single-payer failure modes
- Kerala's community health model — high outcomes at low GDP

**Adjacent claims:**
- the healthcare attractor state is a prevention-first system...
- healthcare is a complex adaptive system requiring simple enabling rules...
- four competing payer-provider models are converging toward value-based care...

**Evidence needed:** Comparative health system analyses. WHO/Commonwealth Fund cross-national data. Case studies of systems that achieved prevention-first economics.

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## 3. GLP-1 Second-Order Economics

**Why it matters:** GLP-1s are the largest therapeutic category launch in pharmaceutical history. One claim captures market size, but the downstream economic and behavioral effects are uncharted.

**What's missing:**
- Long-term adherence data at population scale (current trials are 2-4 years)
- Insurance coverage dynamics (employer vs Medicare vs cash-pay trajectories)
- Impact on adjacent markets (bariatric surgery demand, metabolic syndrome treatment)
- Manufacturing bottleneck economics (Novo/Lilly duopoly, biosimilar timeline)
- Behavioral rebound after discontinuation (weight regain rates, metabolic reset)

**Adjacent claims:**
- GLP-1 receptor agonists are the largest therapeutic category launch...
- the healthcare cost curve bends up through 2035...
- consumer willingness to pay out of pocket for AI-enhanced care...

**Evidence needed:** Real-world adherence studies (not trial populations). Actuarial analyses of GLP-1 impact on total cost of care. Manufacturing capacity forecasts.

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## 4. Clinical AI Real-World Safety Data

**Why it matters:** Belief 5 — clinical AI safety risks — is grounded in theoretical mechanisms (human-in-the-loop degradation, benchmark vs clinical performance gap) but thin on deployment data.

**What's missing:**
- Deployment accuracy vs benchmark accuracy (how much does performance drop in real clinical settings?)
- Alert fatigue rates in AI-augmented clinical workflows
- Liability incidents and near-misses from clinical AI deployments
- Autonomous diagnosis failure modes (systematic biases, demographic performance gaps)
- Clinician de-skilling longitudinal data (is the human-in-the-loop degradation measurable over years?)

**Adjacent claims:**
- human-in-the-loop clinical AI degrades to worse-than-AI-alone...
- medical LLM benchmark performance does not translate to clinical impact...
- AI diagnostic triage achieves 97 percent sensitivity...
- healthcare AI regulation needs blank-sheet redesign...

**Evidence needed:** Post-deployment surveillance studies. FDA adverse event reports for AI/ML medical devices. Longitudinal studies of clinician performance with and without AI assistance.

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## 5. Space Health (Cross-Domain Bridge to Astra)

**Why it matters:** Space medicine is a natural cross-domain connection that's completely unbuilt. Radiation biology, bone density loss, psychological isolation, and closed-loop life support all have terrestrial health parallels.

**What's missing:**
- Radiation biology and cancer risk in long-duration spaceflight
- Bone density and muscle atrophy countermeasures (pharmaceutical + exercise protocols)
- Psychological health in isolation and confinement (Antarctic, submarine, ISS data)
- Closed-loop life support as a model for self-sustaining health systems
- Telemedicine in extreme environments (latency-tolerant protocols, autonomous diagnosis)

**Adjacent claims:**
- social isolation costs Medicare 7 billion annually...
- the physician role shifts from information processor to relationship manager...
- continuous health monitoring is converging on a multi-layer sensor stack...

**Evidence needed:** NASA Human Research Program publications. ESA isolation studies (SIRIUS, Mars-500). Telemedicine deployment data from remote/extreme environments.

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## 6. Health Narratives and Meaning (Cross-Domain Bridge to Clay)

**Why it matters:** The health KB asserts that 80-90% of outcomes are non-clinical, and that modernization erodes meaning-making structures. But the connection between narrative, identity, meaning, and health outcomes is uncharted.

**What's missing:**
- Placebo and nocebo mechanisms — what the placebo effect reveals about narrative-driven physiology
- Narrative identity in chronic illness — how patients' stories about their condition affect outcomes
- Meaning-making as health intervention — Viktor Frankl to modern logotherapy evidence
- Community and ritual as health infrastructure — religious attendance, group membership, and mortality
- Deaths of despair as narrative failure — the connection between meaning-loss and self-destructive behavior

**Adjacent claims:**
- Americas declining life expectancy is driven by deaths of despair...
- modernization dismantles family and community structures...
- social isolation costs Medicare 7 billion annually...

**Evidence needed:** Psychoneuroimmunology research. Longitudinal studies on meaning/purpose and health outcomes. Comparative data on health outcomes in high-social-cohesion vs low-social-cohesion communities.

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*Generated from Vida's first self-audit (2026-03-16). These gaps are ranked by impact on active beliefs — Gap 1 affects the foundational claim that non-clinical factors drive health outcomes, which underpins the entire prevention-first thesis.*
