Policy Brief
Invisible Illness Diagnostic & Funding Gaps
Infection-Associated Chronic Conditions in the United States
Executive Summary
Millions of Americans living with infection-associated chronic conditions (IACCs) -- including Long COVID, ME/CFS, Lyme Disease, Alpha-gal Syndrome, POTS, and Fibromyalgia -- are systematically invisible in federal health surveillance, insurance billing systems, and research funding formulas. This invisibility is not accidental; it is a direct consequence of missing or inadequate ICD-10 diagnostic codes, inconsistent provider coding practices, and a failure to designate key conditions as nationally notifiable diseases.
The consequences are severe. Alpha-gal Syndrome has no dedicated ICD-10 code at all, resulting in a documented 75% diagnostic undercount. Post-Treatment Lyme Disease Syndrome (PTLDS) similarly lacks a specific code, making surveillance of post-treatment complications impossible. ME/CFS, despite imposing an annual economic burden of $149B--$362B, receives only $15M per year in NIH funding -- a burden-to-funding ratio of 3,400:1, the most extreme of any disease in the United States.
This brief identifies the structural gaps in diagnostic coding, quantifies funding disparities across conditions, and presents six evidence-based policy recommendations that would bring these invisible patients into view of the systems designed to serve them.
Key Findings: ICD-10 Coding Gaps
Diagnostic coding is the foundation of health surveillance, insurance reimbursement, and research funding allocation. Gaps in this system render entire patient populations invisible.
| Condition | ICD-10 | Status | Critical Gap |
|---|---|---|---|
| Alpha-gal Syndrome | None | No Code | Completely invisible in all surveillance and billing systems; 75% undercount |
| Lyme (PTLDS) | A69.2x (acute only) | No Code | No code for post-treatment syndrome; patients coded under generic symptom codes |
| ME/CFS | G93.3 | Shared Code | Shared with "postviral fatigue" broadly; many providers use fatigue NOS instead |
| POTS | G90.3 | Non-Specific | G90.3 covers all autonomic disorders; no post-COVID POTS subtype; often miscoded as anxiety |
| Long COVID | U09.9 | Single Code | One code for all subtypes and severities; inconsistent provider application |
| Fibromyalgia | M79.7 | Adequate | Relatively recent addition; no infection-associated subtype |
Finding: Two of the six conditions tracked by InvisibleSignal have no dedicated ICD-10 code (AGS, PTLDS). The remaining four have codes that are either shared, non-specific, or inconsistently applied. This means that the populations most in need of targeted research and treatment are the least visible in the data systems that drive funding and policy decisions.
Funding Disparity Analysis
NIH research funding allocation does not reflect the economic burden or patient population size of infection-associated chronic conditions.
| Condition | Annual Burden | NIH Funding | Ratio | $/Patient/Year |
|---|---|---|---|---|
| ME/CFS | $250B | $15M | 16,667:1 | $4.55 |
| Long COVID | $218B | $1.1B | 198:1 | $61.11 |
| Lyme Disease | $1B | $35M | 29:1 | $17.50 |
| Alzheimer's (comparator) | $340B | $3.4B | 100:1 | $507.46 |
| HIV/AIDS (comparator) | $36B | $3.1B | 12:1 | $2,583.33 |
Finding: ME/CFS has the most extreme burden-to-funding ratio of any disease tracked by NIH. At $4.55 per patient per year, NIH spends less on ME/CFS research than the cost of a single cup of coffee. The condition affects 3.3 million Americans and imposes economic costs of $149B--$362B annually -- comparable to Alzheimer's disease ($340B/year). Achieving even Alzheimer's 100:1 ratio would require increasing ME/CFS funding from $15M to $2.5B per year.
Policy Recommendations
1. Create ICD-10 Codes for AGS and PTLDS
Alpha-gal Syndrome has no dedicated ICD-10 code. Post-Treatment Lyme Disease Syndrome (PTLDS) likewise lacks a specific code. Without codes, these conditions are invisible in every surveillance system, billing database, and research funding formula.
Impact: Would immediately enable epidemiological tracking of ~500,000+ currently invisible patients.
Stakeholders: WHO, CMS, AMA CPT Editorial Panel
2. Make AGS Nationally Notifiable
Alpha-gal Syndrome is the only major tick-borne condition that is NOT a nationally notifiable disease. State-level reporting is inconsistent, and the CDC has documented a 75% diagnostic undercount.
Impact: Would enable CDC to track geographic spread correlated with Lone Star tick range expansion.
Stakeholders: CSTE, CDC, State Health Departments
3. Increase NIH ME/CFS Funding Proportional to Burden
ME/CFS receives $15M/year from NIH against a $149B--$362B annual burden -- a 16,667:1 ratio, the most extreme of any disease in the United States. For comparison, HIV/AIDS has a 12:1 ratio.
Impact: Even reaching Alzheimer's 100:1 ratio would require increasing ME/CFS funding to $2.5B/year.
Stakeholders: NIH, Congressional Appropriations Committee, HHS
4. Standardize Long COVID Billing Practices
U09.9 adoption is inconsistent across providers. Many Long COVID visits are coded under symptom-level codes (fatigue, brain fog, dyspnea), fracturing the data across dozens of ICD-10 entries.
Impact: Standardized coding would improve burden estimates and enable targeted insurance coverage mandates.
Stakeholders: CMS, AHA, Private Insurers
5. Address Rural Diagnostic Access
FAIR Health data shows a 357% growth in rural Lyme claims (2007--2021), yet rural areas have the fewest specialists and longest travel distances to tick-borne disease clinics.
Impact: Telehealth expansion + rural clinic training could reduce the 4.4-year average Lyme diagnostic delay.
Stakeholders: HRSA, Rural Health Clinics, State Medicaid Programs
6. Mandate Post-Infection Screening Protocols
Patients recovering from COVID-19, Lyme, and other infections are not systematically screened for ME/CFS, POTS, or other post-infection sequelae. Early detection could prevent progression to severe disability.
Impact: Could identify at-risk patients within 3--6 months instead of the current 4--7 year diagnostic delay.
Stakeholders: Primary Care Physicians, CDC, Insurance Networks
InvisibleSignal
HHS TOPx Tech Sprint 2026
Data sources: CDC, NIH Reporter, FAIR Health, Tandfonline, CIDRAP
Generated September 9, 2026