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Linking Spontaneous Behavioral Changes to Disease Transmission Dynamics: Behavior Change Includes Periodic
Tangjuan Li1, Yanni Xiao2, Jane Heffernan3
1School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, People's Republic of China.
Bulletin of Mathematical Biology
|May 13, 2024
Summary
Integrating behavior change into disease transmission models shows that spontaneous measures alone are insufficient. Increasing sensitivity to perceived infection can help control disease spread, but limited resources pose challenges.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Behavioral Science
Background:
- Disease transmission dynamics are significantly influenced by population behavior during outbreaks.
- Spontaneous preventive measures are crucial but their impact on disease spread requires quantitative analysis.
- Existing models often lack detailed integration of adaptive behavior change mechanisms.
Purpose of the Study:
- To develop and analyze a model integrating spontaneous behavior change with disease transmission dynamics.
- To investigate the conditions under which non-pharmaceutical interventions (NPIs) can effectively control disease spread.
- To assess the impact of factors like infection sensitivity and resource limitations on outbreak outcomes.
Main Methods:
- A mathematical model representing behavior change via an imitation process based on payoff.
- Analysis of disease dynamics contingent on the basic reproduction number (R0) for NPI scenarios.
- Parameterization of the model using COVID-19 data and Tokyo subway ridership for real-world illustration.
Main Results:
- Sole reliance on spontaneous behavior change is insufficient for disease eradication.
- Increased sensitivity to perceived infection can maintain low disease levels or minor fluctuations.
- Higher rates of behavior change can reduce peak infection prevalence during oscillations.
- Limited medical resources can exacerbate infection scale, leading to complex bifurcations.
- Increased sensitivity to perceived infection can accelerate the peak time and reduce the peak size of infection.
Conclusions:
- Behavior change dynamics are critical for disease control, especially when R0 is low.
- Adaptive responses, like increased sensitivity to infection, are vital for managing outbreaks.
- Model simulations highlight the interplay between behavior, disease spread, and resource availability.
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