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An evolutionary game modeling to assess the effect of border enforcement measures and socio-economic cost: export-importation epidemic dynamics

KM Ariful Kabir, S. M. Atiqur Rahman Chowdhury, Jun Tanimoto

Abstract

In the wake of the novel coronavirus, SARS-CoV-19, the world has undergone a critical situation in which grave threats to global public health emerged. Among human populations across the planet, travel restraints, border enforcement measures, quarantine, and isolation provisions were implemented to control and limit the spread of the contagion. Decisions on implementing and enforcing various control policies should be determined based on available real-world evidence and theoretical prediction. Further, countries around the globe-imposed force-quarantine and strict lockdown against the spreading could be unsustainable in the long run because of economic burden and people’s frustration. This study proposes a novel exportation- importation epidemic model associated with behavioral dynamics under the evolutionary game theory by considering the two-body system: a source country of a contagious disease and a neighboring disease-free state. The model is first applied to the original COVID-19 data in China, Italy, and the Republic of Korea (ROK) and observed through consistent fitting results with equivalent goodness-of-fit. Then, the data are estimated per the appropriate parameters. Driven by these parametric settings and considering the normalized population, the numerical analysis, and epidemiological exploration, this work further elucidates the substantial impact of quarantine policies, healthcare facilities, socio-economic cost, and the public counter-compliance effect. Extensive numerical analysis shows that funds spent on the individual level as “emergency relief-package” can reduce the infection and improve quarantine policy success. Our results also explore that controlling border measurement can work well in the final epidemic stage of disease only if the cost is low.

Abstract

In this paper, a new traffic flow model called the forward-backward velocity difference (FBVD) model based on the full velocity difference model is proposed to investigate the backward-looking effect by applying a modified backward optimal velocity using generalized backward maximum speed. The FBVD model belongs to the family of microscopic models that consider spatiotemporally continuous formulations. Neutral stability conditions of the discrete car-following model are derived using the linear stability theory. The stability analysis results prove that the modified backward optimal velocity has a significant positive effect in stabilizing the traffic flow. Through nonlinear analysis, a kink-antikink solution is derived from the modified Korteweg-de Vries equation of the FBVD model to explain traffic congestion of the model. The validity of this theoretical model is checked using numerical results, according to which traffic jams were found to have been significantly diminished by the introduction of the modified backward optimal velocity.

Abstract

The difference between conventional replicator dynamics and pairwise (PW) nonlinear Fermi dynamics can be discerned by studying the evolutionary dynamics of the interactions between the symmetric cyclic structure in the rock–paper–scissors game and inter- and intraspecific competitions. Often, conventional replicator models presume that the payoff difference among species is a linear function (a linear benefit). This study introduces a PW contrast under the properties of the well-known Fermi rule, where species play against one another in pairs. To model a PW nonlinear evolutionary environment (a nonlinear benefit) within this framework, both analytical and numerical approaches are applied. It is determined that the dynamics of the linear and nonlinear benefits can present the same stability conditions at equilibrium. Moreover, it is also demonstrated that, even in an identical equilibrium condition for both dynamics, the numerical result run by a deterministic approach presents a faster stability state for nonlinear benefit dynamics. This study also suggests that introducing mutation as demographic noise can effectively disrupt the phase regions and show the different relationships between linear and nonlinear dynamics. The symmetric bidirectional mutation among all the species reduced to the stable limit cycle by an arbitrary small mutation rate is also explored. Due to the environmental noise, however, linear and nonlinear exhibit the same steady state. Nevertheless, non-linearity illustrates more stable and faster stability situations. Our result suggests that environmental and demographic noise on the evolutionary dynamic framework can serve as a mechanism for supporting PW nonlinear dynamics in multi-species games.

Abstract

As protection against infectious disease, immunity is conferred by one of two main defense mechanisms, namely (i) resistance generated by previous infection (known as natural immunity) or (ii) by being vaccinated (known as artificial immunity). To analyze, a modified SVIRS epidemic model is established that integrates the effects of the durability of protection and imperfectness in the framework of the human decision-making process as a vaccination game. It is supposed that immunized people become susceptible again when their immunity expires, which depends on the duration of immunity. The current theory for most voluntary vaccination games assumes that seasonal diseases such as influenza are controlled by a temporal vaccine, the immunity of which lasts for only one season. Also, a novel perspective is established involving an individual’s immune system combined with self-interest to take the vaccine and natural immunity obtained from infection by coupling a disease-spreading model with an evolutionary game approach over a long period. Numerical simulations show that the longer attenuation helps significantly to control the spread of disease. Also discovered is the entire mechanism of active and passive immunities, in the sense of how they coexist with natural and artificial immunity. Thus, the prospect of finding the optimal strategy for eradicating a disease could help in the design of effective vaccination campaigns and policies.

Evolutionary game theory modeling to represent the behavioral dynamics of economic shutdowns and shield immunity in the COVID-19 pandemic

KM Ariful Kabir, Jun Tanimoto

Abstract

The unprecedented global spread of COVID-19 has prompted dramatic public-health measures like strict stay-at-home orders and economic shutdowns. Some governments have resisted such measures in the hope that naturally acquired shield immunity could slow the spread of the virus. In the absence of empirical data about the effectiveness of these measures, policy makers must turn to epidemiological modeling to evaluate options for responding to the pandemic. This paper combines compartmental epidemiological models with the concept of behavioral dynamics from evolutionary game theory (EGT). This innovation allows us to model how compliance with an economic lockdown might wane over time, as individuals weigh the risk of infection against the certainty of the economic cost of staying at home. Governments can, however, increase spending on social programs to mitigate the cost of a shutdown. Numerical analysis of our model suggests that emergency-relief funds spent at the individual level are effective in reducing the duration and overall economic cost of a pandemic. We also find that shield immunity takes hold in a population most easily when a lockdown is enacted with relatively low costs to the individual. Our qualitative analysis of a complex model provides evidence that the effects of shield immunity and economic shutdowns are complementary, such that governments should pursue them in tandem.

Social efficiency deficit deciphers social dilemmas

Md. Rajib Arefin,KM Ariful Kabir, Marko Jusup, Hiromu Ito, Jun Tanimoto

Abstract

What do corruption, resource overexploitation, climate inaction, vaccine hesitancy, traffic congestion, and even cancer metastasis have in common? All these socioeconomic and sociobiological phenomena are known as social dilemmas because they embody in one form or another a fundamental conflict between immediate self-interest and long-term collective interest. A shortcut to the resolution of social dilemmas has thus far been reserved solely for highly stylised cases reducible to dyadic games (e.g., the Prisoner’s Dilemma), whose nature and outcome coalesce in the concept of dilemma strength. We show that a social efficiency deficit, measuring an actor’s potential gain in utility or fitness by switching from an evolutionary equilibrium to a social optimum, generalises dilemma strength irrespective of the underlying social dilemma’s complexity. We progressively build from the simplicity of dyadic games for which the social efficiency deficit and dilemma strength are mathematical duals, to the complexity of carcinogenesis and a vaccination dilemma for which only the social efficiency deficit is numerically calculable. The results send a clear message to policymakers to enact measures that increase the social efficiency deficit until the strain between what is and what could be incentivises society to switch to a more desirable state.

Hypothetical assessment of efficiency, willingnessto- accept and willingness-to-pay for dengue vaccine and treatment: a contingent valuation survey in Bangladesh

KM Ariful Kabir, Aya Hagishima, Jun Tanimoto

Abstract

In 2019, Bangladesh has grappled with a record-breaking surge in dengue fever, experiencing the highest number of dengue cases since the year 2000. Together, the intensification of dengue fever combined with a lack of dengue vaccines and appropriate medicines are expected to further the public and government's interests in appropriate and potential dengue vaccines to control the epidemic. We considered people's characteristics, dengue experience, and knowledge to assess their willingness-to-accept (WTA) and willingness-to-pay (WTP) for a hypothetical dengue vaccine and ex-post treatment in Bangladesh (June-July 2019). This study implemented a contingent valuation (CV) method with 3,251 respondents in 10 different locations of Bangladesh. All respondents participated in a hypothetical dengue vaccine scenario consisting of 65% (vaccine A), 80% (vaccine B), and 95% (vaccine C) effectiveness levels with three doses of each vaccine and ex-post dengue treatment. Around 71.2% of respondents were willing to pay for at least one of the hypothetical vaccines: A, B, or C. The average WTPs of the three vaccines amounted to US$ 47.0, US$ 66.0, and US$ 89.0, which were defined as the total cost of the doses necessary to obtain immunity. In Bangladesh, there is a significant demand for low-priced dengue vaccines, which was proven by people's higher acceptance of vaccination practices. Though dengue vaccines are not yet available in Bangladesh, this study provides significant support that both the government and private sectors should work together to develop a reliable and affordable dengue vaccine.

Effect of Lockdown and Isolation to Suppress the COVID-19 in Bangladesh: An Epidemic Compartments Model

Md. Shahidul Islam, Jannatun Irana Ira, KM Ariful Kabir, Md. Kamrujjaman

Abstract

In the promptness of the COVID-19 outbreak, it would be very important to observe and estimate the pattern of diseases to reduce the contagious infection. To study this effect, we developed a COVID-19 analytical epidemic framework that combines with isolation and lockdown effect by incorporating five various groups of individuals. Then we analyze the model by evaluating the equilibrium points and analyzing their stability as well as determining the basic reproduction number. The extensive numerical simulations show the dynamics of a different group of the population over time. Thus, our findings based on the sensitivity analysis and the reproduction number highlight the role of outbreak of the virus that can be useful to avoid a massive collapse in Bangladesh and rest of the world. The outcome of this study concludes that outbreak will be in control which ensures the social and economic stability.

Abstract

In the context of voluntary vaccination, we consider two additional provisions as well as pre-emptive vaccination for a unified model over epidemiology and evolutionary game theory to assess the extent to which advanced and late provisions restrict the spread of disease. To circumvent infection, people can be vaccinated pre-emptively before the epidemic season, but the imperfectness of vaccination or an unwillingness to be vaccinated may cause people instead to either be late-vaccinated or use self-protection. Here, self-protection corresponds to actions such as wearing a mask, washing hands, or using a mosquito net and is defined as the third strategy after pre-emptive vaccination (the first strategy) and late-vaccination (the second strategy). Our model can reproduce multiple social dilemma situations resulting from what is known as the vaccination dilemma (originating from preemptive vaccination), which works on a global time scale (i.e., repeated seasons approaching social equilibrium), and also from two other dilemmas due to late provisions, which work on a local time scale (i.e., every time step in a single season). To reproduce how an individual can acquire information for adaptation from neighbors or the society for a suitable provision, we introduce several strategy-updating rules for both global and local time scales and this behavioral feedback has a significant effect to reducing a transmissible disease. We also establish the social efficiency deficit (SED) indicator for a triple-dilemma game to quantify the existence of a social dilemma. Relying fully on a theoretical framework, our model provides a new perspective for evaluations: (i) how much more advantageous and effective pre-emptive vaccination is in eradicating a communicable disease compared with late provisions such as late vaccination and self-protection, and (ii) the extent of the social dilemma resulting from each of the three provisions, given the new idea of SED. The main effect of the triple-dilemma is that expensive provision displays no SED (no dilemma) until the efficiency or effectiveness of provisions reaches a certain level.

Abstract

Records of epidemics acknowledge immunological multi-serotype illnesses as an important aspect of the occurrence and control of contagious diseases. These patterns occur due to antibody-dependent-enhancement (ADE) among serotype diseases, which leads to infection of secondary infectious classes. One example of this is dengue hemorrhagic fever and dengue shock syndrome, which comprises the following four serotypes: DEN-1, DEN-2, DEN-3, and DEN-4. The evolutionary vaccination game approach is able to shed light on this long-standing issue in a bid to evaluate the success of various control programs. Although immunization is regarded as one of the most accepted approaches for minimizing the risk of infection, cost and efficiency are important factors that must also be considered. To analyze the n-serovar aspect alongside ADE consequence in voluntary vaccination, this study establishes a new mathematical epidemiological model that is dovetailed with evolutionary game theory, an approach through which we explored two vaccine programs: primary and secondary. Our findings illuminate that the ‘cost-efficiency’ effect for vaccination decision exhibits an impact on controlling n-serovar infectious diseases and should be designed in such a manner as to avoid adverse effects. Furthermore, our numerical result justifies the fact that adopting ADE significantly boosted emerging disease incidence, it also suggest that the joint vaccine policy works even better when the complex cyclical epidemic outbreak takes place among multi serotypes interactions. Research also exposes that the primary vaccine is a better controlling tool than the secondary; however, introducing a highly-efficiency secondary vaccine against secondary infection plays a key role to control the disease prevalence.

“Do humans play according to the game theory when facing the social dilemma situation?” A survey study.

Md. Ahsan Habib, KM Ariful Kabir, Jun Tanimoto
Journal Paper Evergreen

Abstract

The aim of this study is to verify whether a human can detect the social dilemma class and its strength for four various games: Prisoner's dilemma, Trivial, Chicken, and Stag-Hunt by using a web-based structural cross-sectional survey. We considered respondent's cooperative and defective behavior by designing multiple sets of 2 × 2 games for two classes in terms of game opponents: whether he is an intimate friend or an unknown person in the questionnaire. In total, 375 respondents participated in this survey. We found that Prisoner's dilemma and Trivial game are recognized easily by the respondents, but they are not aware of the dilemma strength and difference of game opponent's attribute whether the opponent is a close or unknown person.

Abstract

Outbreaks of repeated pandemics and heavy epidemics are daunting threats to human life. This study aims at investigating the dynamics of disease conferring temporary or waning immunity with several forced-control policies aided by vaccination game theory. Considering an infinite and well-mixed homogenous population, our proposed model further illustrates the significance of introducing two well-known forced control techniques, namely, quarantine and isolation, in order to model the dynamics of an infectious disease that spreads within a human population where pre-emptive vaccination has partially been taken before the epidemic season begins. Moreover, we carefully examine the combined effects of these two types (pre-emptive and forced) of protecting measures using the SEIR-type epidemic model. An in-depth investigation based on evolutionary game theory numerically quantifies the weighing impact of individuals' vaccinating decisions to improve the efficacy of forced control policies leading up to the relaxation of the epidemic spreading severity. A deterministic SVEIR model, including vaccinated (V) and exposed (E) states, is proposed having no spatial structure while implementing these intervention techniques. This study uses a mixed control strategy relying on quarantine and isolation policies to quantify the optimum requirement of vaccines for eradicating disease prevalence completely from human societies. Furthermore, our theoretical study justifies the fact that adopting forced control policies significantly reduces the required level of vaccination to suppress emerging disease prevalence, and it also confirms that the joint policy works even better when the epidemic outbreak takes place at a higher transmission rate. Research reveals that the isolation policy is a better disease attenuation tool than the quarantine policy, especially in endemic regions where the disease progression rate is relatively higher. However, a meager progression rate gradually weakens the speed of an epidemic outbreak and, therefore, applying a moderate level of control policies is sufficient to restore the disease-free state. Essentially, positive measures (pre-emptive vaccination) regulate the position of the critical line between two phases, whereas exposed provisions (quarantine or isolation) are rather dedicated to mitigating the disease spreading in endemic regions. Thus, an optimal interplay between these two types of intervention techniques works remarkably well in attenuating the epidemic size. Despite having advanced on the development of new vaccines and control strategies to mitigate epidemics, many diseases like measles, tuberculosis, Ebola, and flu are still persistent. Here, we present a dynamic analysis of the SVEIR model using mean-field theory to develop a simple but efficient strategy for epidemic control based on the simultaneous application of the quarantine and isolation policies.

Abstract

We propose a mean-field vaccination game framework that combines two distinct processes: the simultaneous spreading of two strains of an influenza-like disease, and the adoption of vaccination based on evolutionary game theory presuming an infinite and well-mixed population. The vaccine is presumed to be imperfect such that it shows better efficacy against the original (resident) strain rather than the new one (mutant). The vaccination-decision takes place at the beginning of an epidemic season and depends upon the vaccine-effectiveness along with the cost. Additionally, we explore a situation if the original strain continuously converts to a new strain through the process of mutation. With the aid of numerical experiments, we explore the impact of vaccinating behavior on a specific strain prevalence. Our results suggest that the emergence of vaccinators can create the possibility of infection-prevalence of the new strain if the vaccine cannot bestow a considerable level of efficiency against that strain. On the other hand, the resident strain can continue to dominate under large-scale vaccine avoidance. Moreover, in the case of continuous mutation, the vaccine efficacy against the new strain plays a pivotal role to control the disease prevalence. We successfully obtain phase diagrams, displaying the infected fraction with each strain, final epidemic size, vaccination coverage, and average social payoff considering two-different strategy-update rules and provide a comprehensive discussion to get an encompassing idea, justifying how the vaccinating behavior can affect the spread of a disease having two strains.

Abstract

The information spreading of awareness can prompt the manners of human to ease the infectious possibility and assist to recover swiftly. A dynamic system of Susceptible-Infected-Recovered (SIR) with Unaware-Aware (UA) process (SIR-UA) is newly developed by using compartment model through analytical approach with assumption of an infinite and well-mixed population. Moreover, individuals in a population can be classified into six states as unaware susceptible(SU), aware susceptible(SA), unaware infected(IU), aware infected(IA), unaware recovered(RU), and aware recovered(RA). Compared with previous models, the new dynamic set of equations described the more widespread situation and incorporated all possible states of Unaware-Aware (UA) with SIR process. The effect of awareness is explored carefully to show the significance on epidemic model with time steps. Consequently, the properties of parameters on the epidemic awareness model are studied to deliberate different physical situations. Finally, full phase diagrams are explored to show the epidemic sizes of susceptible and recovered individuals for various parameters.

Abstract

The information awareness about contagious diseases have an influential effect on an individual's decision to suppress the diffusion of infections. In this work, a new mathematical framework for a vaccination game combined with susceptible-infected-recovered (SIR) and unaware-aware (UA) situation is considered. Altering wearing mask or taking protection against diseases, we consider the information spreading effect that might be represented the situation of self-protection. The information spreading is supposed only for local situation for a season, but has a very significant effect to reduce the infection through a generation. Within this concept, unaware and aware states are taken for susceptible, infected and vaccinated individuals for an infinite and well mixed population. Moreover, three different strategy updating rules concerning whether an individual committing or not vaccination: individual based, strategy based and direct selection are studied to show the comparison by depicting as full phase diagram. Finally, it can be seen that information spreading can subdue the spreading of epidemic within a population.

Abstract

The two layer SIR/V-UA epidemic diffusion model is incorporated in metapopulation migration model for random walkers to study the impact of awareness (rumor) for evolutionary vaccination game approach. In metapopulation, each node denoted a sub-population where the individuals migrate from one node to another by random walk following different graphs; star, cycle, wheel and complete. The framework of epidemic migration model in vaccination game with information spreading effect is observed in one single season as well as generation by some strategy update rules for an individual either taking vaccination or not. Furthermore, individuals in each node are divided into seven situations as; unaware susceptible, aware susceptible, unaware vaccinated, aware vaccinated, unaware infected, aware infected and recovered in a single season. Two strategy updating rules: individual based risk assessment (IB-RA) and strategy based risk assessment (SB-RA) are discussed for game theoretical approach for four new states; healthy vaccinated, infected vaccinated, successfully free rider and failed free rider at the end of each season to explore how different graphs of an underlying social network giving impact on the final epidemic size through the effect of information spreading in the complex population network with various number of nodes. Accordingly, the information spreading with migration in metapopulation model can enhance the epidemic threshold effectiveness and help to overcome on controlling disease diffusion.

Abstract

To avoid the infection, the epidemic outburst plays a significant role that encourages people to take vaccination and induce behavioral changes. The interplay between disease incidence, vaccine uptake and the behavior of individuals are taking place on the local time scale. Here, we analyze the individual's behavior in disease-vaccination interaction model based on the evolutionary game approach that captures the idea of vaccination decisions on disease prevalence that also include social learning. The effect of herd immunity is partly important when the individuals are deciding whether to take the vaccine or not. The possibility that an individual taking a vaccination or becoming infected depends upon how many other people are vaccinated. To apprehend this interplay, four strategy updating rules: individual based risk assessment (IB-RA), society based risk assessment (SB-RA), direct commitment (DC) and modified replicator dynamics (MRD) are contemplated for game theoretical approach by how one individual can learn from society or neighbors. The theory and findings of this paper provide a new perspective for vaccination taking policy in daily basis that provision of prompt learning with the collective information reliefs to reduce infection, which gives a new ‘vaccination game’ from other previous models.

Abstract

A two-layer susceptible-infected-recovered/unaware-aware (SIR-UA) epidemic model is presented to analyze the effect of different heterogeneous networks in a population. Random, scale-free, and small-world network topologies are tested to investigate the impact of awareness on the spread of epidemics in a two-layer network with diverse combinations of degree and structure. Susceptible and infected (both unaware and aware) individuals are associated with their neighboring nodes in a social network structure with various degree distributions. In the two-layer SIR-UA epidemic model, a virtual network represents the connections that spread information, while a physical network represents the physical social interactions that spread diseases. We test various combinations of network structures in virtual or physical networks, to understand the impact of information diffusion on the spread of epidemics in a heterogeneous network structure. Then, the effects of awareness on the spread of a disease are discussed. Finally, phase diagrams are illustrated to reveal the final regions covered by an epidemic with various network parameters. We find that a disease spreads less if the virtual social network is more connected than the network of physical connections.

Abstract

Pre-emptive vaccination is regarded as one of the most protective measures to control influenza outbreak. There are mainly two types of influenza viruses -influenza A and B with several subtypes- that are commonly found to circulate among humans. The traditional trivalent (TIV) flu vaccine targets two strains of influenza A and one strain of influenza B. The quadrivalent (QIV) vaccine targets one extra B virus strain that ensures better protection against influenza, however, the use of QIV vaccine can be costly, hence impose an extra financial burden to the society. This scenario might create a dilemma in choosing vaccine types at the individual level. This article endeavors to explain such dilemma through the framework of vaccination game, where individuals can opt one of the three options -choose either of QIV and TIV vaccine or none. Our approach presumes a mean-field framework of vaccination game in an infinite and well-mixed population, entangling the disease spreading process of influenza with the coevolution of two types vaccination decision-making process taking place before an epidemic season. We conduct a series of numerical simulations as an attempt to illustrate different scenarios. The framework has been validated by the so-called multi-agent simulation (MAS) approach.

The impact of information spreading on epidemic vaccination game dynamics in a heterogeneous complex network-A theoretical approach

KM Ariful Kabir, Kazuki Kuga, Jun Tanimoto

Abstract

A modified susceptible-vaccinated-infected-recovered (SIR/V) with unaware-aware (UA) epidemic model in heterogeneous networks is presented to study the effect of information spreading in the spatial structure of the vaccination game on epidemic dynamics. Two layers SIR/V epidemic model is considered to elucidate information spreading, where the fraction of susceptible, vaccinated and infected individuals are parted as unaware and aware state as each susceptible and vaccinated persons are allied with their infected neighbors by a spatial structure, say, an underlying network. The context deduces epidemic vaccination game with awareness influence dynamics in one single season followed by a strategy update process that refer an individual to take imperfect vaccination or not. We considered two different strategy updating rules: individual based risk assessment (IB-RA) and strategy-based risk assessment (SB-RA) to explore how different underlying network topologies, say, random graph and scale free networks, subsequently giving impact on the final epidemic size, vaccination coverage and average social payoff through the effect of information spreading on epidemic. Thus, it can be seen that, awareness can enhance the epidemic threshold effectiveness and lessen the spreading of infection in a scale free network other than random graph and homogeneous network.

Abstract

The dynamics of a spreadable disease are largely governed by four factors: proactive vaccination, retroactive treatment, individual decisions, and the prescribing behaviour of physicians. Under the imposed vaccination policy and antiviral treatment in society, complex factors (costs and expected effects of the vaccines and treatments, and fear of being infected) trigger an emulous situation in which individuals avoid infection by the pre-emptive or ex post provision. Aside from the established voluntary vaccination game, we propose a treatment game model associated with the resistance evolution of antiviral/antibiotic overuse. Moreover, the imperfectness of vaccinations has inevitably led to anti-vaccine behaviour, necessitating a proactive treatment policy. However, under the excessively heavy implementation of treatments such as antiviral medicine, resistant strains emerge. The model explicitly exhibits a dual social dilemma situation, in which the treatment behaviour changes on a local time scale, and the vaccination uptake later evolves on a global time scale. The impact of resistance evolution and the coexistence of dual dilemmas are investigated by the control reproduction number and the social efficiency deficit, respectively. Our investigation might elucidate the substantial impacts of both vaccination and treatment in the framework of epidemic dynamics, and hence suggest the appropriate use of antiviral treatment.

Behavioral incentives in a vaccination-dilemma setting with optional treatment

KM Ariful Kabir, Marko Jusup, Jun Tanimoto

Abstract

Social dilemmas are situations wherein individuals choose between selfish interest and common good. One example of this is the vaccination dilemma, in which an individual who vaccinates at a cost, protects not only themself, but also others by helping maintain a common good called herd immunity. There is, however, a strong incentive to forgo vaccination, thus avoiding the associated cost, all the while enjoying the protection of herd immunity. To analyze behavioral incentives in a vaccination-dilemma setting in which an optional treatment is available to infected individuals, we combined epidemiological and game-theoretic methodologies by coupling a disease spreading model with treatment and an evolutionary decision-making model. Extensive numerical simulations show that vaccine characteristics are more important in controlling the treatment adoption than the cost of treatment itself. The main effect of the latter is that expensive treatment incentivizes vaccination, which somewhat surprisingly comes at a little cost to society. More surprising is that the margin for a true synergy between vaccine and treatment in reducing the final epidemic size is very small. We furthermore find that society-centered decision-making helps protect herd immunity relative to individual-centered decision making, but the latter may be better in establishing a novel vaccine. These results point to useful policy recommendations, as well as to intriguing future research directions.

Abstract

Many recent studies on evolutionary spatial Prisoner’s Dilemma (SPD) games have provided insights into the mechanisms and frameworks that bolster the effect of network reciprocity. In this article, we provide a concise and comprehensive review of previous studies on evolutionary games and network reciprocity. Subsequently, we evaluate and compare the results from such studies in a unified manner to answer an open question in evolutionary SPD games: What are the factors underlying network reciprocity and what effect do these factors have on the emergence and promotion of cooperation? As a first step, we introduce a novel indicator to quantitatively evaluate the effectiveness (contribution) of a final fraction of cooperators via the introduction of the associated mechanisms into a simple evolutionary SPD game. In this game, the players are located on a two-dimensional square lattice with the Moore neighborhood and update their strategies by imitating the strategy of the best performing player among their neighbors, and the dynamics are separated into two periods: the enduring (END) period and the expanding (EXP) period. The initial fraction of cooperators is decreased transiently via the invasion and exploitation of defectors in the END period, and over the period, the fraction of cooperators is increased to expand cooperative clusters in the EXP period. Moreover, we also evaluate the statistical validity of our indicator by performing regression analyses. Our results indicate that two factors bolster the effect of network reciprocity: (1) the shape of the cooperative cluster (C-cluster) formed in the END period and (2) the ability to expand a single “perfect C-cluster,” which is the smallest patch, to increase the opportunity for interactions between cooperators and defectors and reduce exploitation by defectors in the EXP period.

Effect of mass recovery on the performance of solar adsorption cooling system

K.M Arifulkabir, KC Amanul Alam, MMA Sarker, Rifat A Rouf, Bidyut B Saha
Journal Paper Energy Procedia

Abstract

The study investigates the effect of mass recovery process on the performance of a conventional two bed solar adsorption cooling system with direct solar coupling mathematically. In an adsorption refrigeration system, the pressure in adsorber and desorber are different. The mass recovery scheme utilizes this pressure difference to enhance the refrigerant mass circulation. Average Cooling Capacity (ACC) and Coefficient of Performance (COP) were calculated by computer simulation to analyze the influences of operating conditions. The results show that the average cooling capacity of mass recovery system is superior to that of conventional system. It is also seen that mass recovery process enhances the overall performances of solar driven chiller and there is an optimum mass recovery time for an adsorption cooling system with direct solar coupling

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