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Internal and external factors affecting vaccination coverage: Modeling the interactions between vaccine hesitancy,
Kerri-Ann M Anderson1, Nicole Creanza1
1Department of Biological Sciences and Evolutionary Studies Initiative, Vanderbilt University, Nashville, Tennessee, United States of America.
Societal factors influence health decisions. Mathematical models show vaccine mandates can increase vaccination coverage despite high hesitancy, and access doesn't always dictate confidence.
Area of Science:
- Public Health
- Sociology
- Mathematical Modeling
Background:
- Individual health behaviors and perceptions are shaped by societal and cultural contexts.
- Increasing vaccine hesitancy correlates with decreased vaccination coverage and more vaccine-preventable disease outbreaks, especially in developed nations.
- Understanding evolving local vaccination cultures is crucial for public health strategies.
Purpose of the Study:
- To investigate how external factors like vaccine mandates and inaccessibility influence population-level vaccine hesitancy and vaccination behavior.
- To explore the dynamics of cultural evolution in response to vaccine policies.
- To analyze the interplay between individual beliefs, cultural context, and health decisions.
Main Methods:
- Development and application of a mathematical model simulating cultural evolution.
- Analysis of vaccine mandates, vaccine inaccessibility, and cultural selection trajectories.
- Modeling population dynamics of vaccine hesitancy and vaccination coverage.
Main Results:
- Vaccine mandates can result in high vaccine hesitancy coexisting with high vaccination coverage.
- Sustained high vaccine confidence is possible even with limited vaccine accessibility.
- Cultural evolution models reveal complex interactions between policy and public behavior.
Conclusions:
- External factors significantly shape population vaccination decisions and health culture.
- Policy interventions like mandates can have counterintuitive effects on vaccine hesitancy and coverage.
- Mathematical modeling provides valuable insights into public health dynamics and cultural shifts.
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