Navigating the nexus of COVID-19 vaccination strategies: Insights beyond the needle

Fliou, Fayrouz Article Navigating the nexus of COVID-19 vaccination strategies: Insights beyond the needle The European Journal of Comparative Economics (EJCE) Provided in Cooperation with: University Carlo Cattaneo (LIUC), Castellanza Suggested Citation: Fliou, Fayrouz (2024) : Navigating the nexus of COVID-19 vaccination strategies: Insights beyond the needle, The European Journal of Comparative Economics (EJCE), ISSN 1824-2979, University Carlo Cattaneo (LIUC), Castellanza, Vol. 21, Iss. 2, pp. 265-284, https://doi.org/10.25428/1824-2979/033 This Version is available at: https://hdl.handle.net/10419/320201 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by-nd/4.0/ The European Journal of Comparative Economics Vol. 21, no. 2, pp. 265-284 ISSN 1824-2979 http://dx.doi.org/10.25428/1824-2979/033 First published online: 07/02/2025 Navigating the nexus of COVID-19 vaccination strategies: insights beyond the needle Fayrouz Fliou* Abstract: The COVID-19 pandemic has wrought global disruptions, impacting societies and economies significantly, while vaccine hesitancy remains a pressing concern. This paper introduces a framework for analyzing vaccination decision-making, emphasizing the roles of perceived costs and social influences. To craft effective policies, comprehending individuals' cost perceptions is essential. Social imitation also plays a role in vaccination choices, as individuals often emulate their social circles, potentially altering the optimal decision. The established framework demonstrates that COVID-19 policies successfully encouraged vaccination through cost-related strategies. However, similar challenges may emerge in future crises. Therefore, establishing continual information dissemination and educational programs targeting vaccine hesitancy is critical. By consistently addressing this hesitancy, authorities can navigate potential obstacles and bolster their responses to future health emergencies. Keywords: COVID-19 pandemic; Vaccine resistance; Vaccination decision-making; Social influences; Health policies 1. Introduction The global impact of the COVID-19 pandemic has been nothing short of devastating, comparable to the magnitude of a September 11 attack unfolding every 1.5 days (Anderson et al., 2004). This unprecedented crisis has placed an overwhelming burden on healthcare systems worldwide, leading to a significant surge in cases and fatalities (Epidemiology Working Group for NCIP Epidemic Response, 2020). Beyond its immediate health impacts, COVID-19 has exposed vulnerabilities in public health systems and magnified existing economic challenges. Morganti (2023) highlighted the critical need for coordinated policy interventions, especially in times of heightened uncertainty and public health crises. In the fight against the transmission of infectious diseases, vaccination has emerged as a critical and indispensable strategy for intervention and control. It is widely recognized as one of the most effective measures to mitigate the morbidity and mortality associated with such diseases (Lindstrand et al., 2021; Tillett, 1992). However, the issue of vaccination has long been a subject of social dilemma for public health authorities. * University of Turin, department of economics and statistics "Cognetti de Martiis". The authors would like to thank the editor and the anonymous reviewers for their comments and suggestions, which significantly improved the quality of this paper. EJCE, vol. 21, no. 2 (2024) Available online at https://ejce.liuc.it 266 Despite the overwhelming scientific consensus on the safety and efficacy of vaccines, persistent claims questioning their safety continue to circulate (Larson et al., 2021). Furthermore, the outbreak of the COVID-19 pandemic has further intensified the ongoing debate surrounding vaccination regulations and has sparked concerns regarding individual rights. In addition, political fragmentation and health system capacity have been shown to significantly influence countries' responses to the COVID-19 pandemic (Brosio et al., 2022), shaping the speed and efficacy of policy implementation. These factors also intersect with public perception, as they affect trust in government and the healthcare system, both of which are critical determinants of vaccine uptake and broader public health compliance. Throughout the course of several centuries, the field of epidemiological modeling has witnessed remarkable advancements, both in terms of conceptual understanding and technical capabilities. These developments have enabled researchers to analyze the impact of various control strategies on the transmission of diseases (Bacaër, 2011; Xia and Lui, 2013; Buonomo and Lacitignola, 2011; Cai et al., 2014; Eckalbar and Eckalbar, 2011). Mathematical modeling, in particular, has played a pivotal role in the realm of epidemiology, providing valuable insights into infectious diseases and facilitating the assessment of control measures. One crucial aspect of disease control revolves around achieving and sustaining adequate vaccination coverage (Ferguson et al., 2006; Larson et al., 2011; Black and Rappuoli, 2010). Therefore, the effectiveness of a vaccination program hinges upon the proportion of the population that receives the vaccine, as individual choices to either get vaccinated or not significantly influence the collective outcomes of vaccination endeavors (Galvani et al., 2007; Wu et al., 2011). By surpassing the critical threshold for herd immunity, wherein a substantial segment of the population becomes immune, vaccination emerges as a potent tool in thwarting the widespread transmission of the infection (Fine et al., 2011; John and Samuel, 2000). In exploring the decision-making process surrounding vaccination, researchers have employed game-theoretical analyses, which take into account various factors such as perceived costs and benefits, infection risks, vaccine safety, and associated expenses (Bauch et al., 2003). Moreover, the role of social influence is recognized as pivotal, as individuals' decisions are influenced by their interactions with others. By incorporating Navigating the nexus of COVID-19 vaccination strategies: insights beyond the needle Available online at https://ejce.liuc.it 267 social influence into vaccination models, researchers can gain valuable insights into the underlying mechanisms shaping vaccination choices and develop interventions to enhance vaccine uptake19-21. By adopting a dual-perspective approach that considers both costs and social influence, a comprehensive understanding of vaccination decisionmaking can be attained. Such understanding serves as a guide for formulating strategies aimed at improving vaccine acceptance and coverage (Xia and Liu, 2013; Jianwei et al., 2020; Bish et al., 2011). This study is motivated by the recognition of the significant influence of human behavior in the intricate interplay between vaccination, social environments, and public policies. Our primary objective is to examine the repercussions of COVID-19 policies on individuals' decision-making processes regarding vaccination. To offer a comprehensive evaluation of these policies, we construct a theoretical model that incorporates two crucial elements: individuals' perceptions of vaccination costs and the impact of social factors. By taking these aspects into account, our aim is to enhance our understanding of how policies shape individuals' choices regarding vaccination and to generate insights into effective strategies for promoting vaccine acceptance. Model In our study, we direct our attention to a well-mixed population and delve into the context of a singular epidemic outbreak, such as the COVID-19 pandemic. Unlike seasonal diseases, where knowledge and experience can accumulate over time, in this pandemic scenario, vaccination becomes a one-time decision that individuals must make. We assume that costs and probabilities associated with vaccination can be estimated based on individual perceptions, which may vary from person to person. The initial phase of our investigation is centered on conducting a comprehensive cost analysis of vaccination decisions. Divergent Choices, Shared Concerns: Understanding vaccination decision perspectives On a first stage, facing an epidemic outbreak, an individual i initially perceives the costs associated with getting infected as 𝐶𝑖𝑖𝑛𝑓, encompassing healthcare expenses, lost productivity, and potential pain or mortality. Additionally, they assess a probability of contracting the disease, denoted as 𝛽󰆹𝑖. The individual's expected infection cost, based on EJCE, vol. 21, no. 2 (2024) Available online at https://ejce.liuc.it 268 their perception, can be calculated as 𝛽󰆹𝑖𝐶𝑖𝑖𝑛𝑓. The second stage involves the introduction of the possibility to get vaccinated through a voluntary vaccination campaign, where individuals decide whether to get vaccinated or not. Given the available information, an individual, denoted as i, forms an estimation of the costs associated with vaccination, which includes perceived costs denoted as 𝐶𝑖𝑉𝑎𝑐. We define vaccine costs broadly, including both direct costs and anticipated risks. These costs include immediate monetary expenses, opportunity costs related to the time and inconvenience of vaccine administration, and potential adverse health effects as perceived by the individual. To account for the possibility of imperfect vaccination, individuals can still contract the disease after receiving the vaccine, with a probability denoted as 𝛽𝑖𝑣𝑎𝑐. Taking all these factors into consideration, the total perceived costs of getting vaccinated for an individual i can be expressed as: 𝐶𝑖𝑉𝑎𝑐 +𝛽𝑖𝑣𝑎𝑐𝐶𝑖𝑖𝑛𝑓. When making the decision to get vaccinated or not, individuals weigh the relative costs of two options based on their perception. They can either bear the costs associated with refusing the vaccine, which can be represented as 𝛽󰆹𝑖𝐶𝑖𝑖𝑛𝑓 , or choose to get vaccinated, with total perceived costs given by: 𝐶𝑖𝑉𝑎𝑐 +𝛽𝑖𝑣𝑎𝑐𝐶𝑖𝑖𝑛𝑓. Therefore, we express the perceived costs of the individual i’s choice 𝐶𝑖 as follows: 𝐶𝑖={ 𝐶𝑖𝑉𝑎𝑐 +𝛽𝑖𝑣𝑎𝑐𝐶𝑖𝑖𝑛𝑓 𝑎𝑐𝑐𝑒𝑝𝑡𝑎𝑛𝑐𝑒 𝑜𝑓 𝑣𝑎𝑐𝑐𝑖𝑛𝑎𝑡𝑖𝑜𝑛 𝛽󰆹𝑖𝐶𝑖𝑖𝑛𝑓 𝑅𝑒𝑗𝑒𝑐𝑡𝑖𝑜𝑛 𝑜𝑓 𝑣𝑎𝑐𝑐𝑖𝑛𝑎𝑡𝑖𝑜𝑛 To simplify the cost function without losing generality, we introduce the cost ratio between 𝐶𝑖𝑖𝑛𝑓and 𝐶𝑖𝑉𝑎𝑐. This can be denoted as: 𝑟𝑖𝑉= 𝐶𝑖𝑉𝑎𝑐 𝐶𝑖𝑖𝑛𝑓. Thus, the decision to accept vaccination occurs when the cost of getting vaccinated is lower than the cost of not receiving the vaccine, or if the fixed cost ratio of vaccination is lower than the differential of the risk of infection without the vaccines: 𝑟𝑖𝑉<𝛽󰆹𝑖−𝛽𝑖𝑣𝑎𝑐. In this case, the costs of getting vaccinated can be expressed as: 𝐶𝑖=𝐶𝑖𝑉𝑎𝑐 +𝛽𝑖𝑣𝑎𝑐𝐶𝑖𝑖𝑛𝑓. The rejection of vaccination would translate to a cost of getting vaccinated that is higher than the cost of not getting the shot: 𝑟𝑖𝑉>𝛽󰆹𝑖−𝛽𝑖𝑣𝑎𝑐, and a cost of not getting vaccinated of 𝛽󰆹𝑖𝐶𝑖𝑖𝑛𝑓. Navigating the nexus of COVID-19 vaccination strategies: insights beyond the needle Available online at https://ejce.liuc.it 269 In the case where the costs of both options are equal, an individual would be indifferent in choosing either to get vaccinated or not, and is more likely to not get vaccinated due to the omission bias. As a consequence, the decision of not getting vaccinated is taking under the condition: 𝑟𝑖𝑉≥𝛽󰆹𝑖−𝛽𝑖𝑣𝑎𝑐. 𝐶𝑖={ 𝐶𝑖𝑉𝑎𝑐 +𝛽𝑖𝑣𝑎𝑐𝐶𝑖𝑖𝑛𝑓 𝑖𝑓 𝑟𝑖𝐹𝑖𝑥 <𝛽󰆹𝑖−𝛽𝑖𝑣𝑎𝑐 𝛽󰆹𝑖𝐶𝑖𝑖𝑛𝑓 𝑖𝑓 𝑟𝑖𝐹𝑖𝑥 ≥𝛽󰆹𝑖−𝛽𝑖𝑣𝑎𝑐 We introduce the variable 𝛾𝑖 to represent an individual's vaccination options. There are two possible decisions an individual can make: 𝛾𝑖=1 corresponds to accepting vaccination, while 𝛾𝑖=0 represents rejecting it. Taking into consideration this parameter, we can write the costs functions as follows: 𝐶𝑖𝛾𝑖=𝛾𝑖[𝐶𝑖𝑉𝑎𝑐 +𝛽𝑖𝑣𝑎𝑐𝐶𝑖𝑖𝑛𝑓]+(1− 𝛾𝑖)𝛽󰆹𝑖𝐶𝑖𝑖𝑛𝑓, where: 𝐶𝑖1=𝐶𝑖𝑉𝑎𝑐 +𝛽𝑖𝑣𝑎𝑐𝐶𝑖𝑖𝑛𝑓 and 𝐶𝑖0=𝛽󰆹𝑖𝐶𝑖𝑖𝑛𝑓. Based on the perceived costs and probabilities associated with both choices for an individual i, we can express the cost-minimized choice in the following manner: 𝛾𝑖={ 1 𝑖𝑓 𝑟𝑖𝐹𝑖𝑥 <𝛽󰆹𝑖−𝛽𝑖𝑣𝑎𝑐 𝑜𝑟 𝑎𝑐𝑐𝑒𝑝𝑡𝑎𝑛𝑐𝑒 𝑜𝑓 𝑣𝑎𝑐𝑐𝑖𝑛𝑎𝑡𝑖𝑜𝑛 0 𝑖𝑓 𝑟𝑖𝐹𝑖𝑥 ≥𝛽󰆹𝑖−𝛽𝑖𝑣𝑎𝑐 𝑜𝑟 𝑅𝑒𝑗𝑒𝑐𝑡𝑖𝑜𝑛 𝑜𝑓 𝑣𝑎𝑐𝑐𝑖𝑛𝑎𝑡𝑖𝑜𝑛 Figure 1: The vaccination behavior based on the combination of the perceived costs and probabilities of infection for an individual i. The graph a on the left depicts the indifference between the two options of EJCE, vol. 21, no. 2 (2024) Available online at https://ejce.liuc.it 270 getting vaccinated or not. On the right, the graph b illustrates the air of vaccination acceptance: 𝑟𝑖𝑉< 𝛽󰆹𝑖−𝛽𝑖𝑣𝑎𝑐 If all individuals adopt the same strategy of minimizing their cost functions, they will reach a steady state where no individual has an incentive to change their vaccination decision. The graphical representation in Figure-1-a, visually illustrates the highlighted surface where individuals are indifferent between getting vaccinated or not. The figure Figure-1-b depicts the region where the vaccination option becomes the less costly choice. 2. The Ripple Effect: Exploring social influences on vaccination choices In the stage of a voluntary vaccination program, individually centered decisions are constructed through a perceived cost analysis as defined previously, those decisions are influenced by their social association. In fact, whether or not to opt for the vaccination decision depends not only on the individual costs assessment of each choice, but also on the perceived behavior of others (Ndeffo Mbah et al., 2012). In this section, social pressure among the population is considered to clarify its impact on the decision-making process of vaccination. We denote 𝑆𝑖 the social group neighboring of individual i, every individual i find themselves neighboring a number of individuals 𝑁𝑖 in various social settings. Each individual i has 𝑁𝑖 neighbors 𝑘∈𝑁𝑖 in their social group, whose vaccination decisions are represented by 𝛾𝑖,𝑘, where 𝛾𝑖,𝑘 =1 indicates i observes vaccination of member k and 𝛾𝑖,𝑘 =0 indicates i observes refusal of member k. The average vaccination uptake in i's neighborhood, as perceived by the individual i, is: 𝛾𝑖=∑𝛾𝑖,𝑘 𝑁𝑖 𝑘=1 𝑁𝑖 To assess the probability of an individual shifting their decision to that of the majority, we use the Fermi function (Fu et al., 2011). It is a sigmoid function that has been widely used for describing how individuals’ behavioral changes as a response to the discrepancy between two different choices. The parameter 𝜙𝑖 illustrates the sensitivity of individuals to the choice difference from their social neighborhood; therefore, a higher 𝜙𝑖 translates to a higher responsiveness, and an individual being more sensitive to the Navigating the nexus of COVID-19 vaccination strategies: insights beyond the needle Available online at https://ejce.liuc.it 271 difference. In this case, a shift of the initial optimal decision 𝛾𝑖 is more likely to occur, to approach that of majority of the group members. The probability 𝑝𝑖(𝑖←𝑆𝑖) of copying the group’s strategy is given by: 𝑝𝑖(𝑖←𝑆𝑖)=1 1 + exp {−𝜙𝑖|𝛾𝑖− 𝛾𝑖|} Hence, we define 𝑝𝑖(𝑖←𝑆𝑖) as the probability of an individual switching their decision to copy that of the majority made by their neighbors. There will be a shift of the individual optimal decision 𝛾𝑖 with a probability 𝑝𝑖(𝑖←𝑆𝑖), and with a probability (1 − 𝑝𝑖(𝑖←𝑆𝑖)), the individual is going to keep the less costly decision 𝛾𝑖. 𝑝𝑖(𝑖←𝑆𝑖)=0 corresponds to the case of a cost-based decision maker, whereas 𝑝𝑖(𝑖←𝑆𝑖)=1 indicates that the individual is an absolute social follower. Consequently, the costs function would be as follows: 𝐶𝑖𝛾𝑖= 𝑝𝑖(𝑖←𝑆𝑖)𝐶𝑖𝑆𝑜𝑐𝑖𝑎𝑙 +(1−𝑝𝑖(𝑖←𝑆𝑖))𝐶𝑖𝐼𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙 where: 𝐶𝑖𝑆𝑜𝑐𝑖𝑎𝑙 =|𝛾𝑖− 𝛾𝑖| represents the implicit cost of deviating from the group norm. 𝐶𝑖𝐼𝑛𝑑𝑖𝑣𝑖𝑑𝑢𝑎𝑙 is the individual’s cost based on their personal decision (as derived in the previous section). EJCE, vol. 21, no. 2 (2024) Available online at https://ejce.liuc.it 272 Figure 2: The graph depicts the perceived gap between the average social choice of the group and the individual’s optimal choice, and the probability of the individual to shift their decision to that of the majority of their social group. The impact is also influenced by the responsiveness to the choice discrepancy, here we illustrate different levels of 𝜙𝑖. In figure 2, the graph illustrates the relationship between the difference |𝛾𝑖− 𝛾𝑖| and the probability of individuals contemplating a change in their strategy by adopting the option closest to the group's average. As this difference increases, the likelihood of an individual reconsidering their optimal choice 𝛾𝑖 and opting for a strategy closer to the average of the group also rises. The existence of such a discrepancy acts as a catalyst, prompting individuals to reassess their decisions and contemplate adopting an alternative that brings them in line with the collective. Moreover, the probability of individuals opting for the option closest to the group average is additionally influenced by 𝜙𝑖, their level of responsiveness. Individuals with higher responsiveness exhibit a greater inclination to adjust their decisions and align them with the choices made by the group. This means that individuals who are more responsive to the actions and preferences of the group are more likely to adopt strategies that mirror the collective decision-making process. It is clear that plugging into the social pressure works as a “double-edged sword”, which, on the one hand, promotes vaccine uptake in the population when it’s the uptake of taking a shot is Navigating the nexus of COVID-19 vaccination strategies: insights beyond the needle Available online at https://ejce.liuc.it 279 the less costly option. For the vaccination option to be the optimal one, the applied test’s costs should cover the perceived costs of vaccination relatively to the option of not getting the shot, while taking into account how the information is translated from individual to another, and the possibilities of the costs discount during the period of application. These findings emphasize the significance of clear and effective communication from authorities regarding the duration of mandatory testing requirements. It is crucial to provide transparent information about the timeframe during which testing will be necessary. This transparency is vital as if individuals perceive the testing period to be shorter, they may be more inclined to consider frequent testing as a viable alternative to vaccination. This perception can subsequently reduce their willingness to get vaccinated. By ensuring that individuals have a clear understanding of the testing requirements and the potential duration, authorities can assist individuals in more accurately weighing the costs and benefits of vaccination versus testing. Tackling forgery, illicit activities, and vaccination: Another option that we assumed to be available is that of forged documents. The counterfeit certificates have a fixed cost 𝐶𝐹𝑎𝑘𝑒, and a fine 𝑓𝐹𝑎𝑘𝑒 is applicable depending on the probability of detection 𝑝𝑖𝐹𝑎𝑘𝑒: 𝐶𝐹𝑎𝑘𝑒 +𝑝𝑖𝐹𝑎𝑘𝑒𝑓𝐹𝑎𝑘𝑒. We express the costs comparison in terms of ratio relatively to the fine of the test: 𝛽󰆹𝑖𝐶𝑖𝑖𝑛𝑓 +𝐶𝑇𝑒𝑠𝑡[𝑙𝑛(𝑇𝑖)+𝛾]<𝛽󰆹𝑖𝐶𝑖𝑖𝑛𝑓 +𝐶𝐹𝑎𝑘𝑒 +𝑝𝑖𝐹𝑎𝑘𝑒𝑓𝐹𝑎𝑘𝑒 Or: 𝑟𝐹𝑎𝑘𝑒 >𝑟𝑇𝑒𝑠𝑡/𝐹𝑖𝑛𝑒[𝑙𝑛(𝑇𝑖)+𝛾]−𝑝𝑖𝐹𝑎𝑘𝑒 where: 𝑟𝐹𝑎𝑘𝑒 =𝐶𝐹𝑎𝑘𝑒 𝑓𝐹𝑎𝑘𝑒 and 𝑟𝑖𝑇𝑒𝑠𝑡 =𝐶𝑇𝑒𝑠𝑡 𝑓𝐹𝑎𝑘𝑒 EJCE, vol. 21, no. 2 (2024) Available online at https://ejce.liuc.it 280 Figure 4: the area depicted in the graphs is 𝑟𝐹𝑎𝑘𝑒 =𝑟𝑇𝑒𝑠𝑡/𝐹𝑖𝑛𝑒[𝑙𝑛(𝑇𝑖)+𝛾]−𝑝𝑖𝐹𝑎𝑘𝑒. For any combination of costs and probabilities that is higher than the threshold, the individual i will find it less costly to acquire a negative test. It depict the changes that occur if the individual perceived different negative test period from 0 to 20, and three levels of probability of detection of the illicit activity. The presented graphs in Figure 4 illustrate how a change in perception regarding the probability of detection can significantly influence the outcome of the vaccination decision-making process. This emphasizes the crucial role of effective communication regarding measures aimed at curbing the use of forged documents. To address this issue, it is essential to communicate the potential ramifications of acquiring illegal documents, while also considering individuals' tendencies to discount future consequences and their varying perceptions of the timeframe during which negative test results remain valid. Regulators should implement fines that appropriately reflect the different levels of iterations and probabilities perceived by individuals. Furthermore, broadcasting information about the potential legal consequences of utilizing counterfeit certificates can serve as a deterrent to those who might contemplate engaging in such activities. By taking these steps, authorities can work towards mitigating the problem and discouraging individuals from participating in fraudulent practices. 7. Discussion A thorough comprehension of individuals' behavior when it comes to making health decisions plays a pivotal role in anticipating the potential consequences of policies Navigating the nexus of COVID-19 vaccination strategies: insights beyond the needle Available online at https://ejce.liuc.it 281 aimed at improving vaccination acceptance rates. The process of decision making in this context relies on individuals' personal beliefs, which shape their perceived parameters. Consequently, policymakers should effectively communicate the pertinent details that enable individuals to update their information regarding associated costs and timeframes. By doing so, policymakers can facilitate a more informed decision-making process, ultimately fostering greater acceptability of vaccination and enhancing public health outcomes. To prevent divergence that might occur after the application of any policy, the interventions that would encourage vaccination should be communicated clearly to prevent possible temporal discounting, as well as the consequences of any illegal activities discouraged through conveying the appropriate fines. Strengths and Limitations Various mathematical models have employed payoff-based approaches to understand individuals' vaccination decisions, considering perceived costs and benefits (Chen, 2006; Codeço et al., 2007; Vardavas et al., 2007). As an advancement over existing models, we propose considering an individual's vaccination decision as a hybrid process that incorporates both self-initiated cost minimization and the influence of social group’s average decision. Our study introduces a comprehensive modeling framework that incorporates social factors into individuals' decision-making processes, specifically focusing on understanding vaccination policies and their underlying mechanisms of influence. However, it is crucial to acknowledge that the findings of this study may be influenced by the particular social network considered. Like any model, our approach also necessitated making certain simplifying assumptions. Furthermore, it is important to acknowledge that our research assumes individuals to be passive recipients of social influence, and we have not explicitly considered their active behaviors in our analysis. These assumptions provide a foundation for our model but should be recognized as potential limitations in understanding the full complexity of individuals' decision-making processes. 8. Conclusions The policies employed in inciting individuals to getting vaccinated during the COVID-19 pandemic were primarily strategies that impacted the costs. Even though EJCE, vol. 21, no. 2 (2024) Available online at https://ejce.liuc.it 282 increasing the costs of the refusal or reluctance in getting vaccinated might encourage individuals to get the shot, those policies do not aim in changing the perceptions around the rates of infection or the costs of any of the decisions of getting vaccinated or not. The intervention might be effective in reaching head immunity, and stopping the spread of the disease, however, authorities might face the same social reactions in case another health crises might hit in the future. A long-term remedy to vaccination hesitancy might be an establishment of channels of information transmission, that would continuously advise and clarify misconceptions and doubts around vaccines in particular, and health related questions in general. Educational programs might also contribute in the increase of individuals’ confidence in public health management, improve the relationship between policymakers and scientific and technical bodies, and increase transparency over the use of medical data collected within the population. Navigating the nexus of COVID-19 vaccination strategies: insights beyond the needle Available online at https://ejce.liuc.it 283 References Anderson R.N. et al. (2004), ‘Deaths: injuries, 2001’ in Natl Vital Stat Rep., 52(21), 1-86. Bacaër N., Bernoulli D. (2011), ‘D’Alembert and the inoculation of smallpox (1760)’ in A Short History of Mathematical Population Dynamics. Springer. DOI: 10.1007/978-0-85729-115-8_4 Bauch C.T., Galvani A.P., Earn D.J. 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