The Human Variable 

Using CYNAERA’s US-CCUC™ (U.S. Chronic Condition Undercount Correction – Pediatric Edition) methodology, we estimate 1.5–3 million U.S. children and adolescents and 10–20 million globally meet ME/CFS criteria in 2025.

The Global-CCUC™ (Chronic Condition Undercount Correction – Global) model provides a recalibrated framework. By weighting diagnostic suppression, environmental terrain, social protections, clinical awareness, and pandemic burden, it reveals a truer picture: 94–127 million conservative cases and 220–290 million upper-bound cases worldwide.

Infection-associated chronic conditions (IACCs) such as Long COVID, ME/CFS, POTS, and MCAS are not disparate diagnoses — they are systemic sequelae following immune injury. For too long, medicine has treated these illnesses as anomalies or mysteries, when in fact, they follow a biologically predictable pattern of dysregulation.

As AI technology continues to revolutionize healthcare, one crucial aspect that cannot be overlooked is data privacy and security.

As AI technology continues to revolutionize healthcare, one crucial aspect that cannot be overlooked is data privacy and security.

By harnessing real-time data and predictive analytics, AI frameworks are enabling proactive management of chronic illnesses, which means patients can anticipate flare-ups and adjust their care before symptoms become severe.