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This paper presents a methodology that combines information transmission, contact networks, and changes of human behaviors in modeling the dynamics of infectious diseases. The methodology presented is based on a spatial evolutionary game with additional information representing human behavior. This approach is used to model the transmission process...
Contexts in source publication
Context 1
... Scenario 2 with switchers, values of four parameters are changed as follows: m 1 = 500, m 2 = 100, γ 1 = 0.25, and γ 2 = 0.25. The simulation result is shown in Figure 5. ...
Citations
... A review of 84 studies on religiosity and death anxiety found a positive correlation in 27 studies, no correlation in 41 studies, and a negative correlation in 40 studies (Pandya & Kathuria, 2021;Zhang et al., 2019). Coping mechanisms are shaped by early socialization, belief systems, and ideology (Zhao et al., 2015). Negative religious coping can reduce the connection between COVID-19 fear and depression, death anxiety, and distress (Kızılgeçit & Yıldırım, 2022). ...
Background: The mental health of healthcare workers (HCWs) has been significantly impacted by the COVID-19 pandemic. To address this, spirituality and religious coping mechanisms have been suggested as a way to maintain well-being and reduce anxiety levels. Additionally, vaccination has been shown to play an essential role in lowering anxiety levels, including death anxiety. However, there is a lack of evidence on how positive religious coping strategies and COVID-19 immunization affect death anxiety levels. To fill this gap, this study uses a Pakistani HCWs sample. Methods: This study collected cross-sectional data from 389 HCWs on socio-demographics, positive religious coping strategies, vaccine acceptance, and death anxiety. Hypothesis testing was done using Statistical Package for the Social Sciences (SPSS) and Partial Least Squares (PLS) by adopting the Structural Equation Modeling (SEM) technique. Results: The results showed that the positive religious coping strategy and acceptance of the COVID-19 vaccine reduced death anxiety among HCWs in Pakistan. HCWs practicing the positive religious coping strategy and vaccine acceptance had lower levels of death anxiety symptoms. Thus, the positive religious coping strategy has a direct effect on reducing death anxiety. Conclusion: In conclusion, COVID-19 immunization positively affects individual mental health by reducing death anxiety. Vaccines protect individuals from COVID-19 infection, providing a sense of security that reduces the chance of death anxiety among HCWs attending to COVID-19 patients.
... Moreover, several authors showed that the way in which individuals perceive health risks and communicate the effectiveness of protective measures influences the spread of a disease. From this point of view, Zhao et al. (2015) explained that to help prevent epidemics and their spread, it is important to understand how information spreads. They showed that people who are geographically close to each other tend to share more information about life-threatening diseases, including in the context of social media having an increasing role in the dissemination of information. ...
... In contrast to the existing literature, our study is the first to find evidence that spatial spillovers increase hesitancy towards COVID-19 vaccination among people with low education levels. Our results corroborate those of Abdulkareem et al. (2020) and Zhao et al. (2015), who found that people who are geographically close to each other tend to share more information in the context of epidemics. It is conceivable that since anti-vaccine sentiment is higher among less educated people, they tend to spread the word locally. ...
COVID-19 vaccines have so far been the most powerful weapon in the current pandemic, yet many people still show hesitancy toward them. This paper is one of the first studies that examine the factors affecting the COVID-19 vaccine uptake decision from a spatial perspective in Turkey. This study setting allows us to specify the spatial effects that are influential in this decision without which the true nature of the association between vaccination rates and various socioeconomic factors can be determined. Our findings reveal the existence of global spatial interactions in vaccination rates. In addition, age, the level of conservatism, and low education levels show spillovers that amplify their total effects on vaccination rates.
... Good response and preventive strategies at individual and governmental level is crucial for controlling infectious disease outbreak, this is based on extent of understanding of the disease and behavioral response of the individuals. 26,27 This was the first study in Ethiopia to assess risk perception and behavioral response and associated factors among teachers to COVID-19. This study reported that 79.1% of the teachers had high risk perception to COVID-19. ...
Introduction:
Coronavirus disease 2019 (COVID-19) is an infectious illness which was first identified in Wuhan China. The mode of transmission of COVID-19 is mainly from person-to-person by respiratory transmission and from contact with contaminated surfaces. Teachers may have a significant higher number of social interactions than other professions, putting them at greater risk of contracting the virus.
Objective:
The aim of this study was to assess the risk perception and behavioral response of teachers to COVID-19 in Gamo zone, Southern Ethiopia.
Methods:
The study was conducted in Gamo zone from February to march, 2021. An Institution-based-cross sectional study design was employed and multi stage sampling technique was utilized to select 634 study participants. The data were collected using Kobo collect survey tool through interviewer administered questionnaire. The data were analyzed by SPSS version 25. Both bivariable and multivariable logistic regression models were fitted to identify factor associated with risk perception and behavioral response. Odds ratio with 95% confidence interval was computed to determine the level of significance; in multivariable analysis, variables with a P value less than 0.05 with 95% confidence interval were considered as statistically significant.
Results:
About 79.1% and 75.1% of the teachers had high risk perception and good protective behavior, respectively. Having children ((AOR=1.84, 95% CI: 1.15-2.94), COVID-19 update (AOR=3.7, 95% CI: 1.66-8.59) and good protective behavior (AOR= 1.98, 95% CI: 1.18-3.34) were associated with high risk perception. On the other hand, educational status (AOR=9.42, 95% CI: 4.94-17.96) and availability of personal protective equipment (AOR=5.85, 95CI:2.27-15.02) were associated with good protective behavior.
Conclusion:
Although majority of the teachers had good protective behavior, some protective measures were not frequently adopted. There were few individuals who had low risk perception; this could be a potential cause for the occurrence of school outbreak. Therefore, the stakeholder should provide adequate resource and training on COVID-19 to enhance their risk perception and to promote adoption of protective methods.
... In the face of social isolation and lockdown, individuals go through complex decisionmaking about how to cope and survive (Abdulkareem et al. 2020). Strategies for coping usually emerge from early socialization (Ruland et al. 2015), ideology and belief systems (Zhao et al. 2015). ...
Investigating the role of religiosity in coping with health anxiety during the outbreak of COVID-19 assumes significance given the continued onslaught of the pandemic and the importance of religion in many societies of the world. The aim of this study is to test the relationship between religious coping and health anxiety in Pakistani Muslims. The online survey method was used to collect data from 408 respondents. Structural equational modeling was performed, with results indicating that people who are suffering with health anxiety opt for religious coping (β = .54, R2 = .29, p < .001). We conclude that it is important to consider the role of religion and spirituality during pandemic-induced anxiety. There are implications for counselors, physicians and researchers to integrate religious coping methods when planning mental health interventions during pandemics and otherwise.
... Infectious disease's outbreak can cause behavioral changes among large populations (Tan et al., 2004). Therefore choice of strategy emerges from complex social interaction (Ruland et al., 2015) and information available to decision makers (Zhao, Wu & Ben-Arieh, 2015). ...
This study aims to investigate the role of religiosity in coping with health anxiety during the outbreak of COVID-19, a deadliest pandemic of century which is still affecting billions of lives globally. Using online survey method, the researchers collected the data from 408 Pakistani Muslim respondents. Health anxiety and religious coping were measured through seven items Likert scales. Psychometric analysis showed that both scales, health anxiety (Cronbach's alpha ά=.87, composite reliability CR=.869) and religious coping (Cronbach's alpha ά=.893, composite reliability CR=.888), showed good internal consistency. Path analysis, structural equational modeling performed, was performed. All the t indices (GFI=.932, CFI=.954, TLI=.941, RMSEA=.073 & RMR=.035) were within acceptable limit. The regression results indicated that those who were suffering with health anxiety opted religious coping (β=.54, R2=.29, p<.001). These ndings can be helpful for psychiatrists, physicians and researchers to understand psychological complications pertaining infectious diseases.
... Several researchers have investigated the interplay between diseases and decisions by combining compartmental models with game theory [1][2][3][4][5]. Common considerations are dynamics on networks or lattices [5][6][7][8][9][10][11][12][13][14][15][16][17][18] and well-mixed populations [19][20][21][22][23][24][25][26][27][28]. The former's strength is that it captures the effect of population structures, while the latter's strength is that it highlights the individuals' perception of the payoff. ...
In the face of a pandemic, individuals may decide whether they take actions to mitigate the spread of the disease (cooperate), or not (defect), resulting in a 'disease dilemma' similar to the prisoner's dilemma. Cooperation requires an individual to change their routine behaviours to benefit others. The rate of cooperation within a population is directly linked to the rate of spread of the disease. Unfortunately, evolutionary game dynamics predict that all individuals evolve to 'defect.' Here, we combine the disease dilemma with the compartmental model used for diseases which do not confer immunity. We prove that if the time scale at which individuals receive information is sufficiently rapid compared to the time scale at which the disease spreads, then cooperation emerges, and the disease can be controlled. Our results may have implications for the best course of action when confronted with a new infectious disease.
... Hence, good responsive and preventive strategies at both the individual and government levels are vital for saving lives. A choice of strategy depends on behavioral aspects, complex interactions among people [2], and the information available about a disease [3]. Perceiving the risk of an infectious disease may trigger behavioral change, as during the 2003 SARS epidemic [4]. ...
... Here, a combination of modeling with data-driven machine learning becomes particularly attractive. Simulation tools are commonly used to assess the effects of policy impacts in the health domain [3,11,12]. Among the models for policy-making, agent-based modeling (ABM) is recommended as the most promising modeling approach [13]. ...
Modern societies are exposed to a myriad of risks ranging from disease to natural hazards and technological disruptions. Exploring how the awareness of risk spreads and how it triggers a diffusion of coping strategies is prominent in the research agenda of various domains. It requires a deep understanding of how individuals perceive risks and communicate about the effectiveness of protective measures, highlighting learning and social interaction as the core mechanisms driving such processes. Methodological approaches that range from purely physics-based diffusion models to data-driven environmental methods rely on agent-based modeling to accommodate context-dependent learning and social interactions in a diffusion process. Mixing agent-based modeling with data-driven machine learning has become popularity. However, little attention has been paid to the role of intelligent learning in risk appraisal and protective decisions, whether used in an individual or a collective process. The differences between collective learning and individual learning have not been sufficiently explored in diffusion modeling in general and in agent-based models of socio-environmental systems in particular. To address this research gap, we explored the implications of intelligent learning on the gradient from individual to collective learning, using an agent-based model enhanced by machine learning. Our simulation experiments showed that individual intelligent judgement about risks and the selection of coping strategies by groups with majority votes were outperformed by leader-based groups and even individuals deciding alone. Social interactions appeared essential for both individual learning and group learning. The choice of how to represent social learning in an agent-based model could be driven by existing cultural and social norms prevalent in a modeled society.
... Perceiving the risk of infectious diseases may lead people to change their behaviour spontaneously, as shown during the epidemic of SARS in 2003 (Tan et al., 2004). People change behaviour and adapt to protect themselves based on the information they receive about the disease (Zhao et al., 2015). Gathering information and experience through multiple sources is essential for increasing disease risk awareness and taking protective measures (Williams et al., 2010). ...
... Simulation tools are commonly used in assessing policy impacts in the health domain. Different types of models are used, varying from mathematical models (Kerkhove and Ferguson, 2012) to spatial games (Zhao et al., 2015). Boulanger and Bréchet in their evaluation of six paradigm models for policy-making recommended agent-based modelling (ABM) as the most promising modelling approach (Boulanger and Bréchet, 2005). ...
Complexity in human behaviour can play a crucial role in socio-environmental processes like disease diffusion. An example of such complex behaviour is risk perception, and behavioural change due to perceived risk. Computational models, and in particular Agent-based models (ABMs), have evolved as tools for simulating complex real-world processes.
ABMs for describing and simulating a system composed of behavioural entities, ABMs provide the most natural environment. ABMs often use naive deterministic algorithms, which are rule-based, to simulate behavioural change in agents. While agents in ABMs are sometimes endowed with memory, the actual learning in machine learning style is rarely implemented. The endogenous switching of expectations formation strategies using learning algorithm is underdeveloped in ABMs.
The goal of my PhD research is to systematically test the effects of implementing social and environmental intelligence on the dynamics and emergent outcomes of spatial ABM. Spatial ABMs often use spatial data (GIS data) to construct real geographic environments in which agents are situated. Agents need to take changes in the spatial environment into account and adjust their behaviour accordingly. In this PhD research, intelligence, rational, and risk perception are playing an important role in the decision making of agents. Understanding the learning processes of agents in the spatial ABM can assist developing better strategies in problem-solving and coordination mechanisms.
... In the classical method of updating strategy, each player updates its strategy to the strategy of the player with the highest payoff in its neighborhood [14]. In many other studies, the Fermi function is used as a probability function to change to the strategy of a neighbor [10], [16]- [18]. In this paper, a new approach in updating the strategy is used in which each susceptible player updates its strategy not just to the strategy of the neighbor with the highest payoff but also to the strategy of the number of neighbors with the highest payoffs. ...
Epidemics of infectious disease can be traced back to the early days of mankind. Only in the last two centuries vaccination has become a viable strategy to prevent such epidemics. In addition to the clinical efficacy of this strategy, the behavior and public attitudes affect the success of vaccines. This paper describes modeling the efficacy of vaccination considering the cost and benefit of vaccination to individual players. The model is based on the public goods game and is presented as a spatial game on a lattice. Using this model, individuals can contribute to the public health by paying the cost of vaccination or choose to be protected by the public who is vaccinated rather than pay the cost and share the risk of vaccination. Thus, in this model individuals can choose to stay susceptible, can become infected, or choose to vaccinate once in each episode. This paper presents the behavioral changes of the population and the cost to the society as a function of the cost of vaccines, cost of being infected, and the "fear factor" created by the public media.
... Perra et al. present a model that changes the infectiousness of an epidemic over time to reflect behaviour [29]. Other approaches include modifying network connections to simulate fear [30], introducing an additional edge weight to represent social connections [31], and the use of game theory to model strategies that can change as the epidemic spreads [32]. The idea of responsiveness was introduced by Kiss et al., with responsive individuals more likely to avoid infection or be treated quicker, reducing the spread of a disease [33]. ...
The propagation of concepts in a population of agents is a form of influence spread, which can be modelled as a cascade from a set of initially activated individuals. The study of such influence cascades, in particular the identification of influential individuals, has a wide range of applications including epidemic control, viral marketing and the study of social norms. In real-world environments there may be many concepts spreading and interacting. These interactions can affect the spread of a given concept, either boosting it and allowing it to spread further, or inhibiting it and limiting its capability to spread. Previous work does not consider how the interactions between concepts affect concept spread. Taking concept interactions into consideration allows for indirect concept manipulation, meaning that we can affect concepts we are not able to directly control. In this paper, we consider the problem of indirect concept manipulation, and propose heuristics for indirectly boosting or inhibiting concept spread in environments where concepts interact. We define a framework that allows for the interactions between any number of concepts to be represented, and present a heuristic that aims to identify important influence paths for a given target concept in order to manipulate its spread. We compare the performance of this heuristic, called maximum probable gain, against established heuristics for manipulating influence spread.
