Exploring how the costs of a pandemic can lead to a self-enforcing lockdown in a networked economy, analyzing the resulting changes in network structure and the existence of stable equilibria.Exploring how the costs of a pandemic can lead to a self-enforcing lockdown in a networked economy, analyzing the resulting changes in network structure and the existence of stable equilibria.

The Economics of Self-Isolation: A Game-Theoretic Analysis of Contagion in a Free Economy

2025/09/17 23:00
3 min read

Abstract and 1. Introduction

  1. A free and fair economy: definition, existence and uniqueness

    2.1 A free economy

    2.2 A free and fair economy

  2. Equilibrium existence in a free and fair economy

    3.1 A free and fair economy as a strategic form game

    3.2 Existence of an equilibrium

  3. Equilibrium efficiency in a free and fair economy

  4. A free economy with social justice and inclusion

    5.1 Equilibrium existence and efficiency in a free economy with social justice

    5.2 Choosing a reference point to achieve equilibrium efficiency

  5. Some applications

    6.1 Teamwork: surplus distribution in a firm

    6.2 Contagion and self-enforcing lockdown in a networked economy

    6.3 Bias in academic publishing

    6.4 Exchange economies

  6. Contributions to the closely related literature

  7. Conclusion and References

Appendix

6.2 Contagion and self-enforcing lockdown in a networked economy

In this section, we provide an application of a free and fair economy to contagion and selfenforcing lockdown in a networked economy. We show how the costs of a pandemic from a virus outbreak can affect agents’ decisions to form and sever bilateral relationships in the economy. Specifically, we illustrate this application by using the contagion potential of a network [Pongou, 2010, Pongou and Serrano, 2013, 2016, Pongou and Tondji, 2018].

\ Consider an economy M involving agents who freely form and sever bilateral links according to their preferences. Agents’ choices lead to a network, defined as a set of bilateral links. Assume that rational behavior is captured by a certain equilibrium notion (for example, Nash equilibrium, pairwise-Nash equilibrium, etc.). Such an economy may have multiple equilibria. Denote by E(M) the set of its equilibria. Our main goal is to assess agent’s decisions in response to the spread of a random infection (for example, COVID-19) that might hit the economy. As the pandemic evolves in the economy, will some agents decide to sever existing links and self-isolate themselves? How does network structure depend on the infection cost?

\

\

\

\

\

\ Figure 2: Possible network formation in M

\

\ Interestingly, the value of λ depends on the nature of the virus. Viruses induce different severity levels. For example, COVID-19 and the flu virus have different values, inducing different network configurations in equilibrium. The different network configurations in Figure 2 can therefore be interpreted as the networks that will arise in different scenarios regarding the nature of the virus.

\

:::info Authors:

(1) Ghislain H. Demeze-Jouatsa, Center for Mathematical Economics, University of Bielefeld (demeze jouatsa@uni-bielefeld.de);

(2) Roland Pongou, Department of Economics, University of Ottawa (rpongou@uottawa.ca);

(3) Jean-Baptiste Tondji, Department of Economics and Finance, The University of Texas Rio Grande Valley (jeanbaptiste.tondji@utrgv.edu).

:::


:::info This paper is available on arxiv under CC BY 4.0 DEED license.

:::

\

Market Opportunity
SQUID MEME Logo
SQUID MEME Price(GAME)
$36.9384
$36.9384$36.9384
+0.98%
USD
SQUID MEME (GAME) Live Price Chart
Disclaimer: The articles reposted on this site are sourced from public platforms and are provided for informational purposes only. They do not necessarily reflect the views of MEXC. All rights remain with the original authors. If you believe any content infringes on third-party rights, please contact service@support.mexc.com for removal. MEXC makes no guarantees regarding the accuracy, completeness, or timeliness of the content and is not responsible for any actions taken based on the information provided. The content does not constitute financial, legal, or other professional advice, nor should it be considered a recommendation or endorsement by MEXC.

You May Also Like

The Strategic Importance of Corporate Culture in a Tech-Driven Business Environment

The Strategic Importance of Corporate Culture in a Tech-Driven Business Environment

As we move through 2026, the traditional assets of a Business—such as proprietary Technology and capital—are increasingly becoming commodities. In this environment
Share
Techbullion2026/02/19 23:24
Sternlicht Says U.S. Regulation Blocking RWA Tokenization Push

Sternlicht Says U.S. Regulation Blocking RWA Tokenization Push

The post Sternlicht Says U.S. Regulation Blocking RWA Tokenization Push appeared on BitcoinEthereumNews.com. Sternlicht has questioned the U.S. regulatory system
Share
BitcoinEthereumNews2026/02/19 23:09
SUI Price Eyes Breakout, Targets $11 Says Analyst

SUI Price Eyes Breakout, Targets $11 Says Analyst

The post SUI Price Eyes Breakout, Targets $11 Says Analyst appeared on BitcoinEthereumNews.com. SUI price shows a technical setup for a macro breakout with analyst Dan Gambardello targeting $10-$11 levels. Recent partnership with Google’s Agentic Payments Protocol adds fundamental support to the technical analysis as SUI moves closer to potential breakout levels. SUI Price Analysis Points to $10-$11 Breakout Target Dan Gambardello has identified a clear ascending triangle formation on SUI price daily chart with upside targets around $10.79. The analyst simplified this target range to $10-$11 for practical trading purposes. The pattern shows sustained higher lows meeting resistance at current levels before a potential breakout. VanEck maintains more aggressive SUI crypto targets ranging from $13-$25 according to Gambardello’s research. SUI Price Analysis | Source: Dan Gambardello, X The $10 level is a more conservative higher high area for the current cycle. Midterm targets point to $7.50 in the 1.618 Fibonacci extension zone before longer-term objectives. The monthly RSI shows extreme compression that Gambardello describes as “screaming for a macro breakout to the upside.” This momentum oscillator behavior typically precedes major price movements in the crypto market. SUI crypto risk model currently sits at 51 and matches pre-bull market levels seen in coins like Ethereum. Gambardello compared this to Ethereum’s December 2020 reading of 51 before its major breakout. The March 2017 Ethereum reading of 53 preceded that cycle’s parabolic move. The analyst also noted that SUI price trades near the same levels from almost a year ago in November 2024. Bollinger Bands Signal Historic Compression CryptoBullet has identified the tightest Bollinger Bands in SUI’s entire trading history on the weekly chart. The BBW indicator compression reached levels that were historically followed by major price movements. This setup mirrors conditions before SUI’s previous major rallies. Historical data shows SUI price delivered +253% gains between December 2023 and March 2024 following similar compression. SUI…
Share
BitcoinEthereumNews2025/09/18 11:32