_This project was runner-up for the "Technical Research" prize on our Pandemics (May 2024) course. The text below is an excerpt from the final project._

- **Overview**: A Theory of Change (ToC) is a roadmap that outlines how a specific intervention is expected to lead to desired outcomes, mapping out the intermediary causal relationships. This review critically examines the theories of change of various interventions that use modelling tools — mathematical or computational frameworks for understanding disease dynamics — to prevent, contain or mitigate catastrophic pandemic scenarios.
- **Methodology**: interventions and ToCs were collected and synthesised from various biosecurity sources, then assessed based on decision relevance to catastrophic pandemics (including robustness, relevance, pathogen-agnosticism and empirical evidence), tractability, neglectedness, and dual-use risks.
- **Most Promising Modelling Interventions**:
    - _Assessing pathogen properties_: Crucial for early pandemic response by rapidly estimating key properties like transmissibility and virulence.
    - _Estimating the pandemic potential_: Essential for determining a pathogen's potential to cause a pandemic and credibly raising the alarm when necessary.
- **Promising Modelling Interventions**:
    - _Understanding factors of pathogen (re-)emergence_: Provides insights for prevention but may have limited relevance for worst-case scenarios; some dual-use risks exist.
    - _Simulating realistic preparedness scenarios_: Useful for stress-testing response strategies to diverse pandemic scenarios, including catastrophic ones.
    - _Detecting (stealth) outbreaks early_: Important for triggering mitigation measures, especially in stealth pandemics, though likely too delayed for containment
    - _Forecasting joint health and economic impacts of policies_: Aids decision-making by balancing pandemic response strategies in real-time, less relevant in extreme scenarios.
- **Less Promising Modelling Intervention**:
    - _Assessing countermeasure effectiveness in real-time_: Useful for long-term adjustment of responses, less critical in the early stages of catastrophic pandemics.
- **Key recommendations**:
    - Prioritise preparedness and early response models
    - Focus on catastrophic scenarios: Ensure models are robust enough to handle scenarios like "wildfire" (very rapid disruption) or "stealth" (initially asymptomatic spread) pandemics.
    - Invest in model development between pandemics: Prepare analytical pipelines ready for immediate use in various scenarios.
    - Enhance modeller-policymaker collaboration: Establish dedicated teams to bridge the gap between modelling efforts and policy application.
- Key challenges, open questions and areas to investigate further are detailed in the conclusion.

## Full project

_You can view the full project [here](https://forum.effectivealtruism.org/posts/bFfpFKGTePBW4eohK/critical-review-of-modelling-strategies-against-pandemics)._


Critical Review of Modelling Strategies against Pandemics

Jeremy Andreoletti • 2nd Place • October 2024