What Happens When People Stop Trusting Vaccines?

SIR Infectious Disease Modeling · 500 U.S. Counties Across All Regions · Logistic Regression in R · Sai Manasa Adduru, PharmD, MPH

500 U.S. Counties SIR Compartmental Model Logistic Regression · R Geospatial Analysis Presented to Portage County Health District
500
U.S. counties analyzed · spanning all 4 Census regions and diverse demographic profiles
17,375
Excess infections per 100k at moderate hesitancy · the study's central finding
−0.934
Correlation between social composite score and county hesitancy (p < 0.001)
3
Hesitancy scenarios modeled · low (10%), moderate (25%), and high (40%)

SIR Model · Infected Peak by Hesitancy Scenario

Low Hesitancy (10%) Moderate (25%) High Hesitancy (40%)
At moderate hesitancy (25%), the infected peak is nearly 2× higher and persists 3+ weeks longer · compounding community transmission significantly.

Excess Infections per 100k by Hesitancy Level

The relationship is non-linear · moving from 25% to 40% hesitancy nearly doubles excess infections, revealing a critical tipping point in herd immunity.

Social Drivers of Hesitancy · Correlation with County Rates

Political environment and lower education access are the strongest structural predictors · hesitancy is not purely an individual choice but a community-level condition.

County Hesitancy Rate by U.S. Census Region

500 counties sampled proportionally across South (165), Midwest (135), West (120), and Northeast (80) · reflecting national geographic diversity.

Southern counties show avg. 32% hesitancy · more than double that of Northeastern counties (15%), pointing to the need for region-specific public health strategies.