MM b/19 — Paper b19: SGIR Basic Gap-of-Germs Epidemiology

Matheo-b19 presents the SGIR (Susceptible-Gap-Infected-Removed) pandemic modeling framework, extending the classic SIR model by tracking the Gap between Susceptible and Infected populations. This gap governs pandemic dynamics: increasing the “Gap of Germs” through coordinated non-pharmaceutical interventions can reduce pandemic infections by orders of magnitude.

The model demonstrates that simple coordinated changes in viral Shed, Decay, and Catch rates can stop a 289+ million pandemic at 1.5 million infections. Using Evolvix simulations and 2020 epidemiological data, the paper shows that the biological knowledge for pandemic control existed early in COVID-19, but coordination mechanisms for implementing that knowledge did not.

Academic paper

The complete SGIR pandemic modeling study, formatted as an academic paper for the HEAVEN study series.

Matheo-b19 Contents

• Stopping a Pandemic in Mid-Flight: SGIR Models Show How Small Increases in Germ Gaps Can Avert Mass Casualties

Supplementary Materials

• Prompt: Adversarial Review of the SGIR / PandemicSociety101 Paper
• Stopping a Pandemic in Mid-Flight: How Small Changes in Virus Transmission Parameters Can Avert Mass Casualties

Companion papers

• Matheo-b20: MM b/20 — Paper b20: Work-Logic Cascades and Global Infrastructure — Institutional analysis extending SGIR modeling to work-logic cascades and global research infrastructure

• STa2-WWV Origins: STa2-WWV — World War V on Virulence and ViroDefense Olympics — Original stadium context for World War V on Virulence

Development trail

• Original location: The SGIR papers originated in the STa2-WWV (World War V on Virulence) stadium as part of pandemic preparedness analysis

• Migration rationale: Moved to HEAVEN series for navigation accessibility (4-level navbar limitation) while maintaining thematic connections

• Session logs: Development history preserved in original STa2-WWV documentation and HEAVEN series development logs