DARPA has issued a Request for Information to gather insights on cutting-edge disease outbreak simulation computer models.  DARPA is interested in models that are capable of modelling intervention strategies, including vaccination campaigns, social distancing and quarantine protocols, as well as the use of artificial intelligence (“AI”) and machine learning in disease outbreak response strategies.

It seems the unscientific and harmful interventions deployed in response to the covid “pandemic” have become the new normal as far as disease outbreaks are concerned.  And AI and the military are going to play a bigger role next time around.

At the end of last month, the US Defence Advanced Research Projects Agency (“DARPA”) issued a Request for Information (“RFI”) titled ‘Advanced Disease Outbreaks Simulation Capabilities’.  The request invites responses from academia, startups and industry to help assess state-of-the-art disease outbreak simulation computer models.

This RFI aims to gather insights from the research and development community on cutting-edge outbreak modelling tools to enhance understanding of outbreak dynamics and improve future public health emergency preparedness.

DARPA is particularly interested in identifying tools and capabilities that go beyond traditional modelling techniques, such as agent-based models, hybrid network-mechanistic systems and AI-enabled simulations, to better represent transmission dynamics, public health interventions and end-stage outcomes.

DARPA explains the reason for requesting the information in its RFI document:

The emergence of natural or a man-made infectious agents pose a significant threat to the homeland and to deployed warfighters globally. It is imperative that (bio)technology innovation is efficiently and effectively directed to address, mitigate, and deter the impact of any biological agent. A critical resource in this effort is the development of accurate tunable models and simulation toolsets.

We are committed to developing advanced modelling capabilities to optimise response strategies and inform the next generation of (bio)technology innovations to protect the population from biological threats. We are particularly focused on understanding the complex interplay of factors that drive outbreak spread and evaluating the effectiveness of potential interventions.

Advanced Disease Outbreaks Simulation Capabilities, See attachment ‘DARPA-SN-25-72’, SAM.GOV, 27 May 2025

The RFI then goes on to ask multiple questions for which they are seeking answers from responders, stating in capital letters, “DO NOT INCLUDE ANY CLASSIFIED INFORMATION IN THE RFI RESPONSE.”

The questions cover the capability of the model; the software, programming languages and other technical details about their model; the organisation and expertise of the company or person responding; and, whether they would collaborate on research and development opportunities.

Interestingly, there appears to be nothing in it for those who respond, at least not a financial gain.  As Everglade Consulting states, “This RFI is a planning instrument and does not represent a funding opportunity. No awards will be made directly from this notice; however, responses may help shape future DARPA solicitations. Participating organisations may benefit from early exposure to upcoming funded opportunities and will be considered as contributors to a critical national security capability.”

So, what’s it all about?  Is it a fishing exercise to try to gauge who is capable of what, an intelligence gathering exercise on potential opponents or adversaries?  Or is it, as Sociable suggests, an indication that DARPA is looking to develop more effective lockdown and vaccination strategies, ultimately contributing to a more militaristic algorithmic approach to public health emergency response?

As the RFI questions imply, DARPA is interested in modelling a range of intervention strategies, including vaccination campaigns, social distancing measures, quarantine protocols, treatments and public health communication strategies, as well as the ability to model early intervention and its impact on outbreak trajectory.

The fact that DARPA is modelling these intervention strategies suggests that similar measures used during the covid era – such as lockdowns, social distancing and mass vaccination campaigns – will be used again in the future to respond to disease outbreaks.

Through the RFI, the agency is also seeking information on how fatality rates and varying levels of population immunity, whether natural or vaccine-induced, are incorporated into simulations, and how these factors affect the outcome of disease outbreaks.

Additionally, as noted in the preamble to its questions, the agency states it is interested in identifying optimal timelines and capabilities to detect, identify, attribute and respond to disease outbreaks, including the deployment of biosensors to achieve optimal detection timelines. And it appears that artificial intelligence (“AI”) and machine learning will play a significant role in the next generation of disease outbreak response strategies.

As Sociable highlights, this RFI shouldn’t be viewed in isolation.

Recently launched DARPA programmes, such as Kallisti (December 2024) and Methodological Advancements for Generalisable Insights into Complex Systems (“MAGICS”) (April 2025), aim to create algorithmic models to predict and influence collective human behaviour, which could be applied to simulating collective human behaviour during public health emergencies.

The MAGICS programme seeks to develop new methods and paradigms for modelling collective human behaviour; anticipating, predicting, understanding and forecasting complex social phenomena derived from sociotechnical data sets.  Interestingly, there is no mention of modelling or predicting the behaviour of adversaries.

The Kallisti programme, previously named the Theory of Mind, aims to develop new capabilities to enable national security decision-makers to optimise strategies for deterring or incentivising actions by undefined adversaries.  “Adversaries” could include people who question authoritative (false) messaging during a public health emergency.

The development of these programs and technologies has sparked concerns about governments and corporations using them to control and manipulate public behaviour, particularly in the context of public health emergencies, where measures such as lockdowns and vaccination strategies may be implemented.

“DARPA is in the business of R&D for national security purposes, so why is the Pentagon modelling disease outbreaks and intervention strategies while simultaneously looking to predict and manipulate collective human behaviour?” Sociable asked.

Part of the reason could be that the use of AI and machine learning will play a bigger role than during covid.  It will enable the modelling and prediction of human behaviour during public health emergencies, allowing for the development of targeted messaging strategies to promote compliance with public health measures.  And the military will also play a bigger role the next time around.

“From analysing wastewater to learning about disease spread; from developing pharmaceuticals to measuring the effects of lockdowns and vaccine passports, from modelling and predicting human behaviour to coming up with messaging strategies to keep everyone in compliance – ‘improving preparedness for future public health emergencies’ is becoming more militaristically algorithmic by the day,” Sociable writes.

You can read Sociable’s article ‘DARPA to simulate disease outbreaks: model lockdown, vaccination & messaging strategies’ HERE.

Related:

• Did Neil Ferguson’s modelling of the covid pandemic prove once and for all that epidemiology is useless?
• An Idiot’s Guide to Propaganda: How to cook the data (Part 1)
• Why you should raise objections with your MP about WHO’s proposed IHR amendments and Pandemic Treaty
• Covid Lies: Revised Definitions and Bizarre Statements

Featured image: DARPA’s Legged Squad Support System (LS3), aka “LS3 Pack Mule.”  Image taken from ‘If You Don’t Know What DARPA Is, You Should Probably Read This’, Biblioteca Pleyades, 15 February 2016

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