Matheo-b19 — SGIR, stopping a pandemic in mid-flight#
SGIR extends the classical SIR model with a Germ Gap that separates infectious particles from hosts; widening that gap (masks, ventilation, distancing) can blunt a COVID-sized pandemic without a vaccine. It is the most developed paper of the series (it reached PPv1 in HELL before the pour).
How to use: The files below are MockupModels = MM. Their maturity approximates that of a newborn baby that still has a lot of growing up and surviving to do before it can leave its current helpless state by growing into someone who can do “useful” things. This baby feeds on constructive criticism; flattery is like sugar: nice but mostly useless; killing a baby is easy, raising it to become a responsible adult is hard. LLoL got these files so far. Now LLoL has to pass on the baton in this global race. To raise a responsible mathematical theology takes a world. Nowadays it takes a global village to raise a responsible child. Neither can succeed without the other. Hence, LLoL calls to #AuditTheMath, either as a participant or expert contributor or by buying in as a Select Stadion Backer to support those who work on this monumental task.
Stopping a Pandemic in Mid-Flight: SGIR Models Show How Small Increases in Germ Gaps Can Avert Mass Casualties#
Broader Significance
Pandemics are arguably on the more tractable end of the civilizational-scale threats that humanity faces today. Unlike nuclear risks or climate change, a respiratory pandemic plays out on a timescale where coordinated behavior change — masks, ventilation, distancing — can measurably alter outcomes within weeks.
The main scientific result of this study is a mechanistic forecast of a 42-fold reduction in deaths caused by modest coordinated actions that increase Germ Gaps. Yet, such coordination requires overcoming a wide range of cognitive traps, some of which directly obscure a pandemic trajectory from inside a pandemic. This study discusses some of these blind-spots under the label of “linear fooling” to help find strategies for overcoming them. The deeper message is that there currently exists no infrastructure for explaining relevant virodefense mechanisms nor for deploying the gentle kind reasonable coordination required to stop a pandemic.
Readers concerned with pandemic preparedness, global health infrastructure, cross-disciplinary modeling, or the governance foundations required for coordinated species-scale work-logic cascades will find this paper’s methods and findings relevant.
Readers who can’t stand fear-mongering, abhor needlessly drastic quarantines, and wish to fight pandemics with gentle kind reasonable fun may find here a basic mechanism for motivating Virodefense Olympics, to be organized globally each year by growing wide interdisciplinary diversity-encouraging Flying University Networks. By investing in such open wid-e FUN actions, humanity can grow the general citizen science skills required to beat the next pandemic before it starts.
Abstract
The COVID-19 pandemic demonstrated that humanity’s ability to respond to novel respiratory viruses remains dangerously inadequate.
This study extends the classical Susceptible-Infected-Removed (SIR) model to include a Germ Gap — that spatially and temporally separates individual infectious particles (“Germs”) from Infected individuals and Susceptible hosts. The resulting SGIR framework enables more principled predictions of extinctions of Germ populations in the Germ Gap.
To test this SGIR framework it was implemented in “PandemicSociety101”, a stochastic pure mass-action model with seven infection stages, a simplified testing laboratory, hospital capacity monitoring, and multiple pathways to death or recovery. It was written for the Prototype Evolvix Compiler to facilitate seamless switching between ordinary differential equation systems (ODE, faster for huge populations) and the Stochastic Simulation Algorithm (SSA, more accurate by respecting the indivisibility of individuals).
Using parameters calibrated in Spring 2020 to the US COVID-19 pandemic (330 million population, 16 infections on 2020-02-14), this study simulates an uncontrolled pandemic that infects approximately 289 million people and kills approximately 13 million in Scenario 1 (without behavioral changes).
Scenario 2 starts with 1.5 million infections on 2020-05-17 but can also assume a 50% reduction in probabilities for Actions that both Shed and Catch the virus. Such a modest reduction is achievable through coordinated use of face masks, hygiene, and distancing. Simulations show that despite the late start such organizing can stop this pandemic at approximately 4.8 million total infections and 310,000 deaths. This represents a 60-fold reduction in infections and a 42-fold reduction in deaths compared to uncontrolled spread. This study also identifies a dangerous cognitive trap here called linear fooling. In it limited testing capacity creates an illusion of pandemic control precisely when infections are growing fastest.
These results suggest that non-pharmaceutical interventions, which increase the Germ Gap can be remarkably effective without vaccines or herd immunity, provided they are deployed with sufficient coordination across populations. The mechanistically simple Germ Gap model – if well-explained – might play a key role in helping to persuade communities to voluntarily improve pandemic resistance by measuring key parameters of the Germ Gap in citizen science projects that cover the most relevant cases of use in gentle kind reasonable ways.
To help continue improving pandemic resistance over the long term may critically depend on open, well-organized, annual, global Virodefense Olympics. Such games can encourage the wide interdisciplinary diversity-encouraging (“wid-e”) research, which is essential for finding gentle kind reasonable solutions that increase the Germ Gap in the myriads of real-life scenarios that matter most.