Analyzing evolutionary game theory in epidemic management: A study on social distancing and mask-wearing strategies
Data files
May 24, 2024 version files 901.94 KB
Abstract
When combating a respiratory disease outbreak, the effectiveness of protective measures hinges on spontaneous shifts in human behavior driven by risk perception and careful cost-benefit analysis. In this study, a novel concept has been introduced, integrating social distancing and mask-wearing strategies into a unified framework that combines evolutionary game theory with an extended classical epidemic model. To yield deeper insights into human decision-making during COVID-19, we integrate both the prevalent dilemma faced at the epidemic’s onset regarding mask-wearing and social distancing practices, along with a comprehensive cost-benefit analysis. We explore the often-overlooked aspect of effective mask adoption among undetected infectious individuals to evaluate the significance of source control. Both undetected and detected infectious individuals can significantly reduce the risk of infection for non-masked individuals by wearing effective facemasks. When the economic burden of mask usage becomes unsustainable in the community, promoting affordable and safe social distancing becomes vital in slowing the epidemic’s progress, allowing crucial time for public health preparedness. In contrast, as the indirect expenses associated with safe social distancing escalate, affordable and effective facemask usage could be a feasible option. In our analysis, it was observed that during periods of heightened infection risk, there is a noticeable surge in public interest and dedication to complying with social distancing measures. However, its impact diminishes beyond a certain disease transmission threshold, as this strategy cannot completely eliminate the disease burden in the community. Maximum public compliance with social distancing and mask-wearing strategies can be achieved when they are affordable for the community. While implementing both strategies together could ultimately reduce the epidemic’s effective reproduction number (Re) to below one, countries still have the flexibility to prioritize either of them, easing strictness on the other based on their socio-economic conditions.
CONSOLE APPLICATION : Project Overview
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This file contains a summary of what you will find in each of the files that
make up your application.
We uploaded two data files:
- The code file involves performing numerical simulations using C++ in Visual Studio.
- Two tabular data files.
Requirements
- Visual Studio 2019 or later
- C++14 standard or higher
Installation
- Clone the repository:
- bash
- Copy code
- Open the project in Visual Studio:
- Launch Visual Studio.
- Select "Open a project or solution".
- Build the project:
- In the Solution Explorer, right-click on the solution and select "Build Solution" or press Ctrl+Shift+B.
Output File
Two sample Excel files, which were used to create the 2D graphs, have been uploaded. Using the C++ code provided in the Dryad system, 2D CSV files can be generated from the data. In each CSV file, each column represents various parameter values. The first column represents the data numbers. The following two columns represent the values for the x-axis (d) and y-axis (eta). The following two columns represent the R (FES) and M values. The final column optionally represents the category of our simulation.
Methods
Dataset collected from code.