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This study aims to explore the effect of mental health in terms of depression, anxiety, stress, fear of COVID-19 and quality of life (QoL) on the reluctance to be vaccinated in a population of Palestinian adults living in occupied Palestinian territories and Israel.

The authors recruited 1,122 Palestinian adults who consented to participate in the study; 722 were females, and the mean age of the sample was 40.83 (SD 8.8). Depression, anxiety, and stress scale (DASS), World Health Organization QoL-BREF, FCov-19 and reluctance to the vaccine scale were administered; hierarchical regression analysis was applied to test vaccine reluctance as a dependent variable, and mental health, fear of COVID-19 and QoL as independent variables. This study hypothesized influence of such variables on the vaccine choice with differences due to the participants’ geographical locations.

Findings showed an effect of mental health, particularly depression, QoL and fear of COVID on vaccine reluctance, with depression and fear of COVID in the West Bank and Gaza, while in Israel, QoL played a role in vaccination choices.

The future needs to be comprehended more thoroughly to discover mutations and fluctuations over time in vaccine hesitancy and the increasing role of psychological distress, diminished QoL and fear of Covid-19. Online recruitment might not have allowed the study to include the most disadvantaged strips of the Palestinian population.

Human rights perspectives must be considered in public health and public mental health policies to ensure the QoL and well-being for the Palestinian population during and following the pandemic.

The crumbling of the Palestinian health-care system exacerbated the sense of dread among the population and made them less likely to vaccinate. The pandemic-like spread of Covid-19 prompts a plea for the global community to actively advocate for the urgent re-establishment of equity, autonomy and durability of the medical infrastructure in the occupied territories and equal entitlements for the Palestinians in Israel.

The results demonstrated the importance for public mental health to consider the multiple levels implied in the vaccine refusal in Palestine and Israel among the Palestinian population.

This study aims to analyse the structure of the Indian vaccine supply chain (SC) during the Covid-19 crisis and explore the underlying challenges at each stage in the network. It also brings out the difference in performance of various constituent states.

This study relied on both primary and secondary data for the analyses. For the primary data, the study gathered experts’ opinions to validate the authors’ inferences. For the secondary data, it relies on government data provided in websites.

Based on the quartile analysis and cluster analysis of the secondary data, the authors find that the constituent states responded differently during the first and second waves. This was due to the differences in SC characteristics attributed to varied demographics and administrative efficiency.

This paper’s analyses is primarily limited to secondary information and inferences are based on them. The study has important implications for implementing the large-scale vaccination drives by government and constituent states for better coordination and last-mile delivery.

The contribution is unique in studying the performance of constituent states using statistical techniques, with secondary data from authentic sources. It is also unique in combining this observation with validation from experts.

The increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine procurement and distribution, have brought to the fore the importance of vaccine supply chain (VSC) management in recent years. VSC is the cornerstone of effective vaccination; hence, it is crucial to enhance its performance, particularly in low- and middle-income countries where immunization rates are not satisfactory.

In this paper, the authors focus on VSC performance improvement of India by proposing supply contracts under demand uncertainty. The authors propose three contracts – wholesale price (WSP), cost sharing (CS) and incentive mechanism (IM) for the government-operated immunization program of India.

The authors' findings indicate that IM is capable of coordinating the supply chain, whereas the other two contracts are inefficient for the government. To validate the model, it is applied to a real-world scenario of coronavirus disease 2019 (COVID-19) in India, and the findings show that an IM contract improves the overall efficiency of the system by 23.72%.

Previous studies focused mainly on the influenza VSC industry within developed nations. Nonetheless, there exists a dearth of literature pertaining to the examination of supply contracts and their feasibility for immunization programs that are administered by the government and aimed at optimizing societal benefits. The authors' findings can be beneficial to the immunization program of India to optimize their VSC cost.

Nowadays, in many organizations, products are not delivered instantly. So, the customers should wait to receive their needed products, which will form a queueing-inventory model. Waiting a long time in the queue to receive products may cause dissatisfaction and churn of loyal customers, which can be a significant loss for organizations. Although many studies have been done on queueing-inventory models, more practical models in this area are needed, such as considering customer prioritization. Moreover, in many models, minimizing the total cost for the organization has been overlooked.

This paper will compare several machine learning (ML) algorithms to prioritize customers. Moreover, benefiting from the best ML algorithm, customers will be categorized into different classes based on their value and importance. Finally, a mathematical model will be developed to determine the allocation policy of on-hand products to each group of customers through multi-channel service retailing to minimize the organization’s total costs and increase the loyal customers' satisfaction level.

To investigate the application of the proposed method, a real-life case study on vaccine distribution at Imam Khomeini Hospital in Tehran has been addressed to ensure model validation. The proposed model’s accuracy was assessed as excellent based on the results generated by the ML algorithms, problem modeling and case study.

Prioritizing customers based on their value with the help of ML algorithms and optimizing the waiting queues to reduce customers' waiting time based on a mathematical model could lead to an increase in satisfaction levels among loyal customers and prevent their churn. This study’s uniqueness lies in its focus on determining the policy in which customers receive products based on their value in the queue, which is a relatively rare topic of research in queueing management systems. Additionally, the results obtained from the study provide strong validation for the model’s functionality.

This study proposes strategies for vaccine center allocation for coronavirus disease (COVID) vaccine by determining the number of vaccination stations required for the vaccination drive, location of vaccination station, assignment of demand group to vaccination station, allocation of the scarce medical professional teams to station and number of optimal days a vaccination station to be functional in a week.

The authors propose a mixed-integer nonlinear programming model. However, to handle nonlinearity, the authors devise a heuristic and then propose a two-stage mixed-integer linear programming (MILP) formulation to optimize the allocation of vaccination centers or stations to demand groups in the first stage and the allocation of vaccination centers to cold storage links in the second stage. The first stage optimizes the cost and average distance traveled by people to reach the vaccination center, whereas the second stage optimizes the vaccine’s holding and storage and transportation cost by efficiently allocating cold storage links to the centers.

The model is studied for the real-world case of Chandigarh, India. The results obtained validate that the proposed approach can immensely help government agencies and policymaking body for a successful vaccination drive. The model tries to find a tradeoff between loss due to underutilized medical teams and the distance traveled by a demand group to get the vaccination.

To the best of our knowledge, there are hardly any studies on a vaccination program at such a scale due to sudden outbreaks such as Covid-19.

This study aims to understand the utility of personas and illustrate, through a case study, how a persona-building exercise in a Community Based Prevention Marketing (CBPM) training of community leaders elicited important insights that complemented findings from ongoing formative research on vaccine hesitancy in the Hispanic/Latino population in the USA during COVID-19 pandemic.

An exploratory concurrent parallel qualitative study design compared three personas created by community-based organization members (n = 37) to transcripts from five formative research focus groups (n = 30) from the same project. All participants in this study were recruited by the National COVID-19 Resiliency Network as part of their capacity-building and formative research activities. Grounded theory guided the content analysis.

This study found personas and focus groups to be complementary. A high degree of co-occurrence was observed when investigating the uptake of the COVID-19 vaccine under the categories of barriers, culture and communication. Between the two methods, the authors found strong associations between fear, disruption to the value system, work-related barriers, inaccessibility to health care and information sources and misinformation. Areas of divergence were negligible.

While personas provided background information about the population and sharing “how” to reach the priority population, focus groups provided the “why” behind the behavior, followed by “how”.

A community-driven persona-building process built on cultural community knowledge and existing data can build community capacity, provide rich information to assist in the creation of tailored messages, strategies and overall interventions during a public health crisis and provide user-centered, evidence-based information about a priority population while researchers and practitioners wait on the results from formative research.

This case study provided a unique opportunity to analyze the complementary effectiveness of two methods acting in tandem to understand the priority population: stakeholder-informed persona-building and participant-informed focus group interviews. Understanding their complementary nature addresses a time gap that often exists between researchers and practitioners during times of crises and builds on recommendations associated with bringing rigor into practice, promoting academic contribution to real-world issues and building collaborative partnerships. Finally, it supports the utility of a nimble tool that improves social marketers’ ability to know more about their audience for intervention design when time is of the essence and formative research is ongoing.

This study aims to examine individual behaviours regarding coronavirus disease-2019 vaccine brands.

Firstly, qualitative research identified the reasons for vaccine hesitancy in relation to specific brands using data gathered from 36 semi-structured interviews and processed with Leximancer software. Secondly, a new conceptual model was developed with data from 917 questionnaires and analysed using partial least squares-structural equation modelling. The model integrates health treatment effectiveness, vaccines’ immediate health benefits and individuals’ hope as antecedents of perceived vaccine brand reliability and company reputation and their relationships with choice uncertainty.

The results reveal that vaccine hesitancy can be linked with individual, group and contextual and vaccine brand influences and that brand reliability and company reputation antecedents have variable but statistically significant effects on choice uncertainty.

This research’s contribution lies in its analyses of vaccine acceptance and uncertainty from a vaccine brand perspective. The results can guide brand management policies implemented by public and private organisations.

This study contributes to academic literature by filling in two gaps. The first was that no prior studies have directly addressed vaccine brands’ impact, whereas the second gap was the need for brand management policies that public (e.g. governments and public health agencies) and private organisations (e.g. pharmaceutical laboratories) can apply.

Despite significant progress in Iran's immunization programs, vaccine policymaking in the country still faces various challenges and shortcomings. To address these issues and ensure sustained progress toward achieving comprehensive vaccination policies, it is essential to identify the critical factors influencing vaccine policies in Iran. Our study aims to provide evidence-based insights that can inform the development of effective and equitable vaccine strategies, leading to a more sustainable and efficient approach to vaccination in the country.

This mixed-method study aimed to analyze the factors influencing the future of human vaccine policy using Cross Impact Analysis. Firstly, a scoping review was conducted to identify the factors affecting the future of human vaccine development. Secondly, a semi-structured interview was conducted with experts in this field to add more factors and confirm the identified factors within the Iranian context. Finally, a Cross-Impact Analysis (CIA) approach was applied to comprehend the complex relationships between the identified factors. Thematic analysis was used for the qualitative data, and MICMAC analysis was applied to characterize the relationships between the factors.

Seventeen key driving force factors were identified through comprehensive review and interviews. These factors were assigned weighted values ranging from zero to three and subsequently analyzed using MICMAC software. Employing the Cross-Impact Analysis (CIA) technique, the study characterized the impact of each factor on vaccine policy and elucidated the intricate interactions between them. The findings underscored that robust leadership and governance, an innovative ecosystem, and well-established immunization information systems emerged as pivotal driving forces shaping vaccine policy in Iran.

While this study contributes valuable insights into the driving factors influencing vaccine policy in Iran, it is important to acknowledge several limitations. The results rely on the subjective perceptions of a diverse group of specialists, and future research could delve into additional factors in other countries to identify common themes and differences.

This study provides evidence to assist policymakers in making informed decisions regarding vaccines in Iran. The findings suggest that enhancing access to vaccines, fostering trust in the healthcare system, and prioritizing equity in distribution can contribute to increased vaccination rates and a reduction in vaccine-preventable diseases.

This study provides a unique contribution to the field of vaccine policy by utilizing the cross-impact analysis to examine the complex interactions among various factors. The results of this analysis demonstrate that these interactions can significantly impact the overall system, highlighting the need for policymakers to consider multiple factors when formulating effective strategies. By revealing the significance of these interactions, this research offers valuable insights into the development of successful policies that can shape a desirable future for vaccine policy in Iran. Future studies could ratify the findings from this research by applying other methodological approaches.

The global Covid-19 pandemic is posing considerable challenges for governments throughout the world and has and will have a significant influence on the shape of peoples social and economic life and wellbeing in the short and longer term. This opinion paper discusses the current health policy response adopted in England to control or manage the epidemic and identifies the key sociological and political influences which have shaped these policies. Drawing on the theoretical approach set out in his recent book, which emphasises the interplay of powerful structural and economic interest groups, the author will consider the influence of the key players. Government policy has tied itself to scientific and medical evidence and protecting the NHS so the key roles of the medical profession, public health scientific community and NHS management and their respective and relative powerful influences will be discussed. The government needs the support of the public if their policies are to be successful, so how have the government addressed maintaining public trust in this “crisis” and how much trust do the public have in the government and what has influenced it? The strong emphasis on social distancing and social isolation in the national government policy response to Covid-19 has placed an increasing public reliance on the traditional and social media for sources of information so how the media has framed the policy will be considered. One policy aim is for an effective vaccine and the influence of the drug industry in its development is discussed. Finally, the role of the state will be discussed and what has shaped its social and economic policies.