Faster Uptake, Slower Let-Down: Asymmetric Community Responses to Changing Risks During a Pandemic.

Area of Science:

• Social Psychology
• Epidemiology
• Computational Social Science

Background:

• Social processes often involve information assimilation to form opinions and perceptions, guiding actions.
• Empirically identifying perception delays in response to information, such as disease dynamics, is challenging.
• Existing models often assume fixed or symmetric delay structures, which may not reflect reality.

Purpose of the Study:

• To investigate the empirical identification of perception delays in human responses to disease dynamics.
• To evaluate the impact of assumed delay structures on estimates of public sensitivity to risk.
• To explore and apply asymmetric delay structures to model public risk perception during pandemics.

Main Methods:

• Utilized synthetic data to demonstrate biases from incorrect or symmetric delay structures.
• Developed and applied alternative, asymmetric delay structures.
• Analyzed state-level US COVID-19 disease and mobility data.

Main Results:

• Incorrect delay structures and symmetric delay assumptions lead to biased estimates.
• Public risk perception during the COVID-19 pandemic adjusted with asymmetric delays.
• Perception of rising risks was faster than the perception of declining risks.

Conclusions:

• Asymmetric delay structures are crucial for accurately modeling public perception of risk.
• Understanding these asymmetric delays is vital for effective public health communication and policy during disease outbreaks.
• Human responses to risk are complex and exhibit differential adjustment speeds based on risk trajectory.