How Culture Influences the Management of a Pandemic: A Simulation of the COVID-19 Crisis

Abstract

Since its first appearance in Wuhan (China), countries have been employing, to varying degrees of success, a series of non-pharmaceutical interventions aimed at limiting the spread of SARS-CoV-2 within their populations. In this article, we build on scientific work that demonstrates that culture is part of the explanation for the observed variability between countries in their ability to effectively control the transmission of SARS-CoV-2. We present a theoretical framework of how culture influences decision-making at the level of the individual. This conceptualization is formalized in an agent-based model that simulates how cultural factors can combine to produce differences across populations in terms of the behavioral responses of individuals to the COVID-19 crisis. We illustrate that, within our simulated environment, the culturally-dependent willingness of people to comply with public health related measures might constitute an important determinant of differences in infection dynamics across populations. Our model generates the highest rates of non-compliance within cultures marked as individualist, progressive and egalitarian. Our model illustrates the potential role of culture as a population-level predictor of infections associated with COVID-19. In doing so, the model, and theoretical framework on which it is based, may inform future studies aimed at incorporating the effect of culture on individual decision-making processes during a pandemic within social simulation models.

Collecting Data in an Immersive Video Environment to Set up an Agent-Based Model of Pedestrians’ Compliance with COVID-Related Interventions

“…The number of participants in our case study was limited to 26 and all of these participants were German. Thus, our results, especially the compliance rates, are tied to the German context in terms of cultural dimensions (Hofstede 2011;Kruelen et al 2022), such as individualism versus collectivism (the need for autonomy (Kruelen et al 2022) or self-interest to efficiently reach the destination versus disease risk for others) and short-term versus long-term orientation (saving some minutes by not complying with a one-way street or risking getting ill in a few days).…”

“…Following a discussion about the neglection of important behavioral, social, and geographical factors in this and other disease-spreading ABMs, models based on more nuanced theories were designed. For example, Dignum et al (2020) included people's motives broken down into achievement, affiliation, power, and avoidance when testing the effect of interventions; Kruelen et al (2022) modelled how the willingness of people to comply with policy interventions is culturally-dependent; Briscese et al (2020) examined the duration of policies, the severity of penalties for noncompliance, and individuals' attitudes towards science as motivational factors; and Klôh et al (2020) simulated infections in densely populated favelas compared to other neighborhoods including motivational and environmental factors.…”

“…Another way to still be able to build agent-based models of the effects of policy interventions in the COVID-19 pandemic was to collect no data at all. Instead, researchers made assumptions based on the current state of affairs and logical reasoning (Dignum et al 2020;Blibli & Bouchair 2023), or connected the compliance with COVID-induced interventions directly to known concepts, such as fulfilment of needs and risk-perception (Kruelen et al 2022). However, building an ABM solely based on assumptions, logical reasoning and/or transferring findings from related research incurs risks such as completely missing specific relevant aspects or misjudging the relative impact of these on people's behavior.…”

Social Simulation as a Prognostic Tool for Communication Processes: Theoretical and Philosophical Perspectives

“…However, the relevance of this topic is not diminished as it is reinforced by events that occur in social environments, certain emerging transformations, and challenges, that is, everything that raises questions about the need for forecasting one or other trends in order to anticipate the further direction of a certain social/community development in one or other changing/changeable social, political, economic, or other conditions (e.g. the COVID-19 pandemic, see Kreulen et al 2022; Orge Retzlaff et al 2022; Lorig et al 2021;Cremonini, Maghool 2020). Social simulation, based on a variety of computational methods, attracts the attention of researchers in various fields and disciplines, including philosophers.…”

Editorial: Modelling Values in Social, Technical, and Ecological Systems

“…Agentbased modelling is particularly suitable in this context as it can capture the multilevel complexity of complex socio-cognitive phenomena (Dignum et al, 2022), involving both emergent and aggregated phenomena (upwards causation) as well as the influence of the macro-social level on individuals via their values (downwards causation). Its multi-level ability allows it to mediate between several academic disciplines and perspectives on values (e.g., Boshuijzen-van Burken et al, 2020;Mercuur et al, 2019;de Wildt et al, 2021;Kreulen et al, 2022;Harbers, 2021), which is why agent-based modelling and the study of values go well together. 1.3 We invite our readers to dive into exploring the role of values in individual and collective decisions, actions, and behaviour, as well as on the system level, in the field of social simulation and agent-based modelling.…”