Risk Perception Influence on Vaccination Program on COVID-19 in Chile: A Mathematical Model

Area of Science:

• Epidemiology
• Mathematical Modeling
• Public Health

Background:

• The SARS-CoV-2 pandemic necessitated widespread safety measures, with varying public adherence to protocols like personal protective equipment (PPE) use.
• Understanding the interplay between biological and behavioral factors is crucial for managing viral outbreaks.

Purpose of the Study:

• To develop a mathematical model simulating SARS-CoV-2 contagion dynamics in Chile.
• To assess the interaction between biological factors (e.g., vaccination) and behavioral factors (e.g., risk perception) on virus spread.

Main Methods:

• Development of a mathematical contagion model.
• Utilized Chilean epidemiological data for model calibration and analysis.
• Simulated various scenarios by altering risk perception and PPE usage variables.

Main Results:

• The model consistently predicted three distinct waves of SARS-CoV-2 contagion, with the second wave being the most significant.
• The timing and intensity of these waves were largely independent of variable alterations, which primarily influenced total infection numbers.
• Reduced population risk perception and lower willingness to use PPE were directly associated with increased contagion waves and mortality.

Conclusions:

• Behavioral factors, specifically risk perception and PPE adoption, significantly impact SARS-CoV-2 transmission dynamics and outcomes.
• Mathematical modeling provides valuable insights into managing infectious disease outbreaks by integrating biological and behavioral data.
• Public health strategies should consider behavioral interventions to mitigate the impact of viral contagions.