Simulating Percentage of Workers Opting to Work from Home During the COVID-19 Pandemic Using N-Player Iterative Game Theory

The outbreak of the COVID-19 virus has led to several countries establishing guidelines asking citizens to stay secluded and at their homes as much as possible. This has a profound impact on the working lives in almost all professions. Hence, people have been advised to work from home. However, working from home has several limitations and on average will cause financial losses to an individual. This has given rise to a dilemma where each person has the choice of working from home or going outside with the incentive of earning more capital but also increasing the risk of capturing the virus. We have modeled this situation using an n-player game where each player is trying to maximize their payoff, i.e., trying to make as much money as possible but limiting the risk of catching the virus. We aim to predict the proportion of a population cooperating, i.e., the following work from home guidelines at a particular stage of spread. This project presents an algorithm to model the n-player game and has used actual COVID-19 case numbers from various Indian states to simulate the situation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Underweighting of rare events in social interactions and its implications to the design of voluntary health applications

Research on small repeated decisions from experience suggests that people often behave as if they underweight rare events and choose the options that are frequently better. In a pandemic, this tendency implies complacency and reckless behavior. Furthermore, behavioral contagion exacerbates this problem. In two pre-registered experiments (Ntotal = 312), we validate these predictions and highlight a potential solution. Groups of participants played a repeated game in one of two versions. In the basic version, people clearly preferred the dangerous reckless behavior that was better most of the time over the safer responsible behavior. In the augmented version, we gave participants an additional alternative ing the use of an application that frequently saves time but can sometimes have high costs. This alternative was stochastically dominated by the responsible choice option and was thus normatively irrelevant to the decision participants made. Nevertheless, most participants chose the new("irrelevant") alternative, providing the first clear demonstration of underweighting of rare events in fully described social games. We discuss public policies that can make the responsible use of health applications better most of the time, thus helping them get traction despite being voluntary. In one field demonstration of this idea amid the COVID-19 pandemic, usage rates of a contact tracing application among nursing home employees more than tripled when using the app also started saving them a little time each day, and the high usage rates sustained over at least four weeks. (PsycInfo Database Record (c) 2022 APA, all rights reserved)