How a Rutgers Statistician's Evidence Framework Got Sick Veterans Their Benefits

The typical sequence in evidence-based medicine runs: publish research, influence policy. For J. Scott Parrott's work on military burn pit exposure, the order was reversed. Federal policy changed first. The research paper explaining the methodology arrived later.

"Usually, you publish the research, and it changes policy," Parrott said. "This time, policy changed - and then the paper came out."

The unusual timeline reflects both the urgency of the problem and how long veterans had waited for resolution.

The Exposure Problem That Couldn't Be Solved Conventionally

Open-air burn pits operated at up to 86% of U.S. military bases in Iraq and Afghanistan, particularly between 2005 and 2012. They served as the primary waste disposal method, burning medical waste, plastics, batteries, vehicles, and human remains using jet fuel as accelerant. The smoke contained a complex mix of particulates, heavy metals, dioxins, and volatile organic compounds.

Veterans began reporting chronic respiratory conditions and rare lung diseases in increasing numbers. The link seemed intuitive. Establishing it legally and scientifically was far harder.

In 2020, the National Academies of Sciences, Engineering, and Medicine reviewed the evidence and found the connection between deployment to Southwest Asia and respiratory diseases inconclusive. The standard frameworks for causation - built around randomized trials and dose-response measurements - couldn't be applied. No one measured burn pit smoke exposure at the time. The exposures happened years or decades ago in active combat zones. The data that would have been needed simply doesn't exist and cannot be gathered retroactively.

Reframing the Question

Parrott, a professor with the Rutgers School of Health Professions and an expert in statistical methodology, received a VA grant in 2021 to reexamine the evidence. His team's insight was to ask a different question. If definitive experimental proof is unattainable, can the totality of available evidence - preclinical data, clinical patterns, environmental monitoring, epidemiology, deployment histories - point toward the most plausible explanation?

The framework they built assigns graded levels of confidence rather than demanding binary certainty. It asks whether clinical patterns are consistent with inhalational injury, whether biological findings align with known mechanisms of lung damage, whether deployment history correlates with disease onset. And it asks whether any alternative explanation accounts for the evidence as well.

"You can't prove it in the strictest sense," Parrott said. "But you can determine whether there is any other plausible explanation. And if there isn't, that's strong enough to guide policy."

The conclusion the team reached was direct: deployment to the Southwest Asia theater of operations increases the risk of developing a subset of interstitial lung diseases and constrictive bronchiolitis. The methodology gave the VA a path forward it hadn't had before.

Policy Before Publication

The Promise to Address Comprehensive Toxics (PACT) Act, passed by Congress in 2022, established the legislative framework for expanded veteran benefits. But implementation required a method for determining whether specific respiratory illnesses qualified as service-related. In December 2024, the VA adopted regulations that incorporated Parrott's methodology as the standard for that determination.

The research paper formalizing the approach published in Evidence-Based Technology in February 2026 - more than a year after the policy it underpins went into effect.

Personal Stakes and Ongoing Work

The issue is not abstract for Parrott. His son-in-law, James Petty, served multiple tours in Iraq and Afghanistan and later worked as a military contractor in Kuwait. After those deployments, Petty developed a rare lung condition. He now lives with chronic respiratory and cardiopulmonary disorders.

"It's also personal," Parrott said.

The work continues. Rutgers now hosts the evidence synthesis platform previously maintained by the U.S. Agency for Healthcare Research and Quality, which was decommissioned in November. Parrott's team rebuilt it as a continuously updated, open-source repository synthesizing research and data on military exposures. The team is also exploring how large-language models can accelerate evidence reviews for complex epidemiological questions without sacrificing methodological rigor.

The broader significance extends beyond veterans. Parrott's framework addresses a persistent problem in public health and regulatory science: how to make evidence-based decisions when the gold-standard data is unavailable, and when waiting for that data means denying benefits to people who may be suffering the consequences of state-sanctioned harm.