Modelling behavioural interactions in infection disclosure during an outbreak: An evolutionary game theory approach

Area of Science:

• Epidemiology
• Game Theory
• Mathematical Biology

Background:

• Effective disease outbreak management relies on voluntary disclosure of potential infection and adherence to self-quarantine.
• Past pandemics, like COVID-19, saw quarantine measures used to reduce disease spread and stigma.

Purpose of the Study:

• To develop a game-theoretic model analyzing behavioral interactions in infection disclosure during outbreaks.
• To determine the minimum voluntary disclosure level needed to break transmission chains.

Main Methods:

• Utilized a game-theoretic framework to model individual disclosure decisions.
• Employed a fractional derivative approach to simulate disease propagation.
• Calibrated model parameters using COVID-19 hospitalization data from Chile.

Main Results:

• Higher transmission rates and perceived infection severity incentivize greater voluntary disclosure.
• Increased disclosure proportion effectively reduces disease incidence.
• Model successfully estimated behavioral parameters and transmission rates.

Conclusions:

• Voluntary infection disclosure is a critical factor in controlling disease outbreaks.
• Effective risk communication strategies can enhance public disclosure rates.
• Understanding behavioral dynamics is key to mitigating epidemic spread.