# Bio-threat modeling and war-gaming
A genuinely thin category — simulating biological-threat scenarios (pandemic tabletop exercises, AI-designed pathogen risk, biodefense war-games) is real and policy-relevant work, but concentrated in a small number of academic centers and think tanks rather than a commercial vendor market; one confirmed anchor institution as of 2026.
Source: https://en.bioecon.ru/technology/bio-threat-modeling-wargaming/
Updated: 2026-08-21
## Overview and value chain
Markers: [EC: none — informs US national biodefense strategy | OECD: biotech-health, cross-cutting | Regulator: FDA (USA)]
Bio-threat modeling and war-gaming simulates biological-threat scenarios — pandemic tabletop exercises, biodefense war-games, and structured risk assessment of emerging threats like AI-designed pathogens — to inform government policy, institutional preparedness, and research-governance decisions. This work is fundamentally advisory and analytical rather than a commercial product, and is dominated by a small number of academic biosecurity centers and policy think tanks rather than a broad vendor market with product pages. As of 2026 only one institution was confirmed with strong, on-topic evidence of an active bio-threat-modeling and exercise practice; several other named candidates (a biosurveillance company, a national laboratory) returned only generic academic papers that never actually named the specific candidate, a common false-confirmation pattern in this catalog area.
The key directions of bio-threat modeling and war-gaming are:
1. **Pandemic tabletop exercises:** structured scenario exercises that walk government or institutional participants through a simulated pandemic response, testing decision-making and coordination under realistic constraints.
2. **AI-designed pathogen risk assessment:** emerging analysis of the risk that AI tools could be used to design or enhance a biological threat, a rapidly developing 2026 policy concern.
3. **Biodefense war-gaming:** structured simulation of a deliberate biological-attack scenario to test national or institutional response capability.
4. **Congressional and policy-briefing scenario discussions:** interactive scenario sessions designed to inform legislators and policymakers on emerging biological-risk topics.
### Sectoral value chain
```
[Threat scenario design] ──> [Exercise/simulation execution] ──> [Participant response capture] ──> [Analysis]
│
(findings synthesis)
│
▼
[Policy/preparedness recommendations] <─── [Report publication] <─────────┘
```
### Value chain levels
| Level | Description | Key inputs/outputs |
|:---|:---|:---|
| **Scenario design** | A realistic biological-threat scenario is designed, grounded in current epidemiological or biosecurity science | **In:** threat intelligence, epidemiological science.
**Out:** a structured scenario. |
| **Exercise/simulation execution** | Government, institutional, or legislative participants work through the scenario in a structured session | **In:** scenario, participants.
**Out:** captured participant decisions and responses. |
| **Response capture** | Participant decisions and coordination gaps are systematically recorded during the exercise | **In:** exercise session.
**Out:** a structured response record. |
| **Analysis** | Analysts assess the response for capability gaps, coordination failures, and policy implications | **In:** response record.
**Out:** analytical findings. |
| **Report publication** | Findings are published for policymakers, institutions, or the public | **In:** analytical findings.
**Out:** a published report. |
| **Policy/preparedness recommendations** | The report's findings feed into updated policy or institutional preparedness planning | **In:** published report.
**Out:** policy or preparedness changes. |
Cross-cutting technologies of the sector:
- **Scenario-design methodology:** structured approaches for building a realistic, policy-relevant biological-threat scenario.
- **AI-risk assessment frameworks:** emerging methodology for evaluating whether AI tools meaningfully increase biological-threat risk, a fast-moving 2026 policy area.
- **Exercise facilitation infrastructure:** the operational capability to run a multi-participant tabletop or simulation exercise and systematically capture its outputs.
---
## US
The US is the only region with a confirmed dedicated institution, reflecting the concentration of this work in a small number of elite US academic biosecurity centers.
### Pandemic exercises, AI-designed pathogen risk analysis
- **Johns Hopkins Center for Health Security:** ran the SPARS 2017 (a coronavirus pandemic scenario exercise still referenced in current training materials) and its current Biosecurity Simulation Exercise (BSX) course, and published commentary on AI-designed viral genome governance in 2026 — confirmed via a RAND Corporation research report referencing its work, the center's own LinkedIn posting on AI-designed pathogen risk, and independent coverage of its bioterrorism-preparedness history.
---
## CN
No Chinese institution with a dedicated, confirmed bio-threat-modeling and war-gaming practice was found on a live screen. This is consistent with the field's concentration in a small number of Western academic centers rather than a broad international vendor or institutional market.
### No confirmed dedicated institution
- **Market context:** this article found no Chinese institution with confirmed, on-topic evidence of a dedicated bio-threat-modeling and war-gaming practice.
- **Reopen condition:** if a Chinese institution with a confirmed bio-threat-modeling practice surfaces on a future screen, this section should be revised and the institution added to the table.
---
## EU
No EU institution with a dedicated, confirmed bio-threat-modeling and war-gaming practice was found on a live screen at the same confirmation strength as the US anchor institution.
### No confirmed dedicated institution
- **Market context:** this article found no EU institution with confirmed, on-topic evidence of a dedicated bio-threat-modeling and war-gaming practice comparable to Johns Hopkins' confirmed US evidence.
- **Reopen condition:** if an EU institution with a confirmed bio-threat-modeling practice surfaces on a future screen, this section should be revised and the institution added to the table.
---
## Leading companies and research institutes
| Company / Institute | Country | Key products / platforms | Tech features | Status 2026 |
|:---|:---|:---|:---|:---|
| **Johns Hopkins Center for Health Security** | 🇺🇸 USA | *SPARS 2017 pandemic scenario, Biosecurity Simulation Exercise (BSX) course* | Pandemic tabletop exercises, AI-designed pathogen risk analysis | Active, referenced in 2026 AI-biorisk policy discussion |
---
## Tech stack and innovations
The category's "technology" is scenario-design and exercise-facilitation methodology rather than a physical product, applied to an evolving set of biological-threat scenarios.
1. **Scenario exercise design:**
- The SPARS 2017 coronavirus scenario, developed years before COVID-19, is still referenced as a training tool — reflecting how a well-designed scenario can remain relevant across multiple real-world biological events.
2. **AI-biorisk governance analysis:**
- The center's 2026 commentary on AI-designed viral genome governance addresses an emerging risk category — the possibility that generative AI tools could meaningfully lower the barrier to designing a dangerous pathogen — a topic with active 2026 congressional and policy attention.
3. **Structured exercise facilitation:**
- The Biosecurity Simulation Exercise (BSX) course format applies structured facilitation methodology to walk participants through a realistic biosecurity scenario, systematically capturing decision-making gaps for later analysis.
---
## Value chains and production pipelines
### Industrial pipeline of a bio-threat tabletop exercise (informs US national biodefense strategy)
```
┌───────────────────────────┐ ┌───────────────────────────┐
│ 1. Scenario design │ ───> │ 2. Exercise/simulation execution │
└───────────────────────────┘ └───────────────────────────┘
│
▼
┌───────────────────────────┐ ┌───────────────────────────┐
│ 4. Analysis │ <─── │ 3. Response capture │
└───────────────────────────┘ └───────────────────────────┘
│
▼
┌───────────────────────────┐ ┌───────────────────────────┐
│ 5. Report publication │ ───> │ 6. Policy/preparedness recommendations │
└───────────────────────────┘ └───────────────────────────┘
```
#### Stage 1: Scenario design
A realistic biological-threat scenario is built, grounded in current epidemiological or biosecurity science — as with the SPARS 2017 coronavirus scenario.
#### Stage 2: Exercise/simulation execution
Government, institutional, or legislative participants work through the scenario in a structured session, such as the BSX course.
#### Stage 3: Response capture
Participant decisions, coordination gaps, and response times are systematically recorded during the exercise.
#### Stage 4: Analysis
Analysts assess the captured response for capability gaps and policy implications, including emerging risk categories like AI-designed pathogens.
#### Stage 5: Report publication
Findings are published for policymakers, institutions, or the public, such as the center's commentary on AI-designed viral genome governance.
#### Stage 6: Policy/preparedness recommendations
Published findings feed into updated national biodefense policy or institutional preparedness planning.
---