by Jon Fleetwood, Jon Fleetwood:
A third framework for understanding modern pandemics.
For more than five years, debate over the origin of COVID-19 has largely been confined to two competing explanations.
Either SARS-CoV-2 emerged naturally from wildlife and spilled into humans.
Or it escaped from a laboratory following research involving coronaviruses.
But what if both explanations are asking the wrong question?
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What if the defining infrastructure of a modern pandemic is not the physical pathogen itself, but the informational architecture surrounding it?
This publication refers to that possibility as the In Silico Theory, from in silico—meaning processes that occur inside a computer rather than in the physical world.
The In Silico Theory does not attempt to adjudicate between wildlife spillover and laboratory escape as competing explanations.
Instead, it proposes that modern pandemics may increasingly be operationalized through predictive algorithms, genomic reference architectures, laboratory-generated sequence information, surveillance systems, computational epidemiology, diagnostics, and pharmaceutical platforms that collectively create a self-reinforcing informational ecosystem.
Within such a framework, laboratories remain essential—not necessarily as the point where a pandemic begins, but as critical nodes in the generation, refinement, validation, and operationalization of the informational systems that define it.
Under such a model, the central question shifts from:
“Where did the pathogen come from?”
to:
“Who designed the systems that define what the pathogen is?”
DARPA’s Decade-Long Buildout
Beginning in 2010, the U.S. military, largely through DARPA, launched a succession of programs that appear to have progressively reduced the need to begin with a recognized outbreak, a widely observed epidemic, or even a conventionally characterized pathogen.
Instead, DARPA’s own documents describe an architecture increasingly built around predicted mutations, electronic sequence information, computational models, and pharmaceutical countermeasures developed before the need for them supposedly exists.
The effort was not hidden.
DARPA itself described the work as an:
“audacious portfolio of projects designed to generate pandemic-stopping know-how”
for rapidly preventing, diagnosing, and treating infectious diseases,
“even ones the world has never seen before.”
Taken individually, each program can be understood as a biodefense initiative.
Taken together, however, they appear to describe something much larger:
a pandemic architecture designed to move from models, to sequence information, to interventions, and finally to deployment.
Step One: Predict the Future Pathogen
The first layer appeared in 2010 with DARPA’s PROPHECY program.
DARPA sought to:
“develop technologies that predict natural viral evolution”
and:
“predict mutations and possibly reassortments in advance of their occurrence.”
To most readers, this language may not initially appear unusual.
In traditional public health thinking, however, scientists first observe a pathogen, characterize it, and only afterward begin designing interventions.
PROPHECY proposed reversing that sequence.
DARPA envisioned:
“predictive algorithms informed and validated experimentally using high throughput biological platforms”
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