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This paper aims to analyze the socioeconomic impacts of infectious diseases based on uncertain behaviors of social and effective subsystems in the countries. The economic impacts of infectious diseases in comparison with predicted gross domestic product (GDP) in future years could be beneficial for this aim along with predicted social impacts of infectious diseases in countries.

The proposed uncertain SEIAR (susceptible, exposed, infectious, asymptomatic and removed) model evaluates the impacts of variables on different trends using scenario base analysis. This model considers different subsystems including healthcare systems, transportation, contacts and capacities of food and pharmaceutical networks for sensitivity analysis. Besides, an adaptive neuro-fuzzy inference system (ANFIS) is designed to predict the GDP of countries and determine the economic impacts of infectious diseases. These proposed models can predict the future socioeconomic trends of infectious diseases in each country based on the available information to guide the decisions of government planners and policymakers.

The proposed uncertain SEIAR model predicts social impacts according to uncertain parameters and different coefficients appropriate to the scenarios. It analyzes the sensitivity and the effects of various parameters. A case study is designed in this paper about COVID-19 in a country. Its results show that the effect of transportation on COVID-19 is most sensitive and the contacts have a significant effect on infection. Besides, the future annual costs of COVID-19 are evaluated in different situations. Private transportation, contact behaviors and public transportation have significant impacts on infection, especially in the determined case study, due to its circumstance. Therefore, it is necessary to consider changes in society using flexible behaviors and laws based on the latest status in facing the COVID-19 epidemic.

The proposed methods can be applied to conduct infectious diseases impacts analysis.

In this paper, a proposed uncertain SEIAR system dynamics model, related sensitivity analysis and ANFIS model are utilized to support different programs regarding policymaking and economic issues to face infectious diseases. The results could support the analysis of sensitivities, policies and economic activities.

• A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

• Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

• Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

• An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

• A real case study is considered to evaluate the performances of the proposed models.

A new system dynamics model is proposed in this paper based on an uncertain SEIAR model (Susceptible, Exposed, Infectious, Asymptomatic, and Removed) to model population behaviors;

Different subsystems including healthcare systems, transportation, contacts, and capacities of food and pharmaceutical networks are defined in the proposed system dynamics model to find related sensitivities;

Different scenarios are analyzed using the proposed system dynamics model to predict the effects of policies and related costs. The results guide lawmakers and governments' actions for future years;

An adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the gross domestic product (GDP) in future years and analyze effects of COVID-19 based on them;

A real case study is considered to evaluate the performances of the proposed models.

Health is a human right and a fundamental building block of sustainable development, economic prosperity and poverty reduction. To realize people’s right to health, evaluating the situation of the right and its determinants is necessary. This paper aims to analyze Iran’s conduct in realizing its population’s right to health.

A qualitative case study design involving a structured review of relevant laws, policy documents, reports and academic literature was undertaken. The data were collected from electronic databases and the official Web pages of the United Nations (UN) and Iran’s Government and analyzed by a framework suggested by the UN.

Iran’s law and policies intend to combat health inequalities and to provide an adequate standard of living for everyone, particularly disadvantaged groups and individuals. However, not all laws and policies protecting disadvantaged groups are adequately implemented. There are disparities in health status and access to health care among different socio-economic groups. International economic sanctions and government policies decreased people’s ability to access the necessities of life including health care. Moreover, social determinants of health, such as cultural beliefs regarding women’s rights have not been addressed sufficiently in the country’s laws.

This study includes a broad range of subjects and provides an overview of the health-care system of Iran. However, more detail is needed to describe every aspect of the right to health. It was not feasible to address them all in this paper and needs more research. In addition, as with the majority of qualitative studies, the design of the current study is subject to limitations. Firstly, the research quality of narrative reviews is dependent on the researcher’ skills and more easily can be influenced by his/her personal biases. Second, the rigor is more difficult to maintain, assess and demonstrate. Nevertheless, narrative studies often complement quantitative studies and are informative.

To fulfill the right to health, Iran should improve affordability and quality of care and the situation of the determinants of health. The gaps in people’s access to health care need to be identified, and all necessary means and scarce resources be allocated to remove access barriers and to improve the situation of disadvantaged people. The adoption of relatively low-cost targeted programs, the proper management of resources and the prevention of unnecessary costs are suggested.

Decentralised administrative arrangements and the active function of local government organisations are essential to tackle crisis effectively. Using Bangladesh as a case study, this paper examines the central and local government administrative arrangements during COVID-19 pandemic.

This study applies qualitative content analysis and interviews to explore the local government’s role in Bangladesh’s COVID-19 management by interviews of 18 participants including government officials, experts, non-government organisations (NGOs) representatives, and the general public. This paper also analysed academic papers, policy documents and other publicly available documents, including newspaper reports.

The Constitution of Bangladesh intensified the active participation of local government in each administrative unit through decentralised administrative management. This paper however reveals that the administrative arrangement during the COVID-19 pandemic in Bangladesh was primarily a centrally led system. The local government was not sufficiently involved, nor had it integrated into the planning and coordination process. This indicated the absence of active decentralised administration.

This study fills the research gap of the administrative pattern and local relations in COVID-19 management by exploring the local government’s role during the catastrophic situation and highlights the importance of decentralised administrative actions in managing the crisis.

This study aims to elucidate the dynamics of social media discourse during global health events, specifically investigating how users across different platforms perceive, react to and engage with information concerning such crises.

A mixed-method approach was employed, combining both quantitative and qualitative data collection. Initially, thematic analysis was applied to a data set of social media posts across four major platforms over a 12-month period. This was followed by sentiment analysis to discern the predominant emotions embedded within these communications. Statistical tools were used to validate findings, ensuring robustness in the results.

The results showcased discernible thematic and emotional disparities across platforms. While some platforms leaned toward factual information dissemination, others were rife with user sentiments, anecdotes and personal experiences. Overall, a global sense of concern was evident, but the ways in which this concern manifested varied significantly between platforms.

The primary limitation is the potential non-representativeness of the sample, as only four major social media platforms were considered. Future studies might expand the scope to include emerging platforms or non-English language platforms. Additionally, the rapidly evolving nature of social media discourse implies that findings might be time-bound, necessitating periodic follow-up studies.

Understanding the nature of discourse on various platforms can guide health organizations, policymakers and communicators in tailoring their messages. Recognizing where factual information is required, versus where sentiment and personal stories resonate, can enhance the efficacy of public health communication strategies.

The study underscores the societal reliance on social media for information during crises. Recognizing the different ways in which communities engage with, and are influenced by, platform-specific discourse can help in fostering a more informed and empathetic society, better equipped to handle global challenges.

This research is among the first to offer a comprehensive, cross-platform analysis of social media discourse during a global health event. By comparing user engagement across platforms, it provides unique insights into the multifaceted nature of public sentiment and information dissemination during crises.

This article seeks to discuss trust within the context of public health crises using an autopoietic systems perspective that positions communication as one of its core concepts. This article will explore trust studies conducted during public health crises in this Millennium (from SARS to COVID-19 pandemics), including their problems; briefly summarize Luhmann's concept of Vertrauen; and use this concept to analyze trust issues during the COVID-19 pandemic.

This article will explore trust studies conducted during public health crises from SARS to COVID-19 pandemics, including their problems. The perspective used is an explication of Niklas Luhmann's theory regarding Vertrauen which was derived as a framework for reading empirical facts on trust issues during the COVID-19 pandemic. The research design and exploration stages were inspired by the theory of autopoiesis systems by Niklas Luhmann.

From a systems perspective, the COVID-19 pandemic has highlighted the extraordinary complexity of the linkages between social systems. Trust will continue to evolve dynamically as new variants emerge in society. Consequently, the pandemic has provided the momentum necessary for maximally exploring the concept of trust. Indonesia thus experienced significant obstacles when making and implementing disaster mitigation policies. Owing to the lack of a trust system, greater emphasis was given to control and power. There has been little preparedness to create and reinforce public trust, and this in turn has stifled efforts to stop the spread of COVID-19.

This study of trust, communication and public health crises has provided space to reflect on the development of trust within the social system. This study shows that trust can prove to be a very important factor in resolving a crisis. However, the complexity of the interrelationships of the social system can affect the quality of trust. The context of Indonesia's social system which is very complex due to population density and the dynamics of the development of its social system which is very diverse as an archipelagic country has contributed to the originality of the study of trust in times of crisis in a growing contemporary society.

Strategic orientation is one of the critical principles affecting the marketing and strategy selection of an organization’s activities, reflecting the strategic tendencies implemented by the organization to create behaviours, leading to organizational efficiency and better employee performance. Therefore, this paper aims to study the relationship between strategic orientation and performance in Qazvin teaching hospitals through green supply chain management (SCM) to improve employees' performance.

This was a descriptive– analytical and cross-sectional study. The total number of employees in medical centres was 2,256 people. According to Morgan’s table, the required number of samples was 328, including 10% of the sample loss. The questionnaire was given to 365 staff in different hospitals in proportion to the number of staff. Two statistical software, SPSS24 and AMOS23, were used to evaluate the results.

All three variables were relatively moderate in the hospitals. The results of evaluating the structural model of the research showed that all the studied hypotheses were significant, except for the relationship between organizational performance and strategic orientation hypothesis. The results also show that this model had a good fit.

The findings can lead to saving the environment, creating a better social image and reducing costs and profitability, allowing managers to know the strategic orientations rather than depending on institutional pressure issues and monitoring guidelines.

Considering the significant relationship between the dimensions of green SCM and the hospitals’ performance, the authors suggest: establishing multilateral co-operation in environmental issues, improving the environmental status of hospitals, reducing waste rates and paying attention to social responsibility of hospitals. In addition, the findings help hospital management to comprehensively understand the strategies for implementing green SCM procedures.

This purpose of this study was to investigate the role of nurses’ resilience as an indicator of their mental health on sick leave absenteeism during the COVID-19 pandemic.

This descriptive-analytical study was conducted in 2020 to identify the predictors of absenteeism among 260 nurses working in two training hospitals delivering specialized services in the treatment of COVID-19 patients. Data was collected through the use of standard questionnaires including demographic information, nurses’ resilience, intention for job turnover and absenteeism from the workplace. To predict sick leave absenteeism, regression analyses were implemented.

Study results revealed that the most influencing features for predicting the probability of taking sick leave among nurses were marital status, tenacity, age, work experience and optimism. Logistic regression also depicted that nurses who had less faith in God or less self-control were more likely to take sick leave.

The resilience of nurses working in the COVID-19 pandemic was relatively low, which needs careful consideration to apply for organizational support. Main challenge that most of the health systems face include an inadequate supply of nurses which consequently lead to reduced efficiency, poor quality of care and decreased job performance. Thus, hospital managers need to put appropriate managerial interventions into practice, such as building a pleasant and healthy work environment, to improve nurses’ resilience in response to heavy workloads and stressful conditions.

To the best of the authors’ knowledge, this is the first study to examine such a relationship, thus contributing findings will provide a clear contribution to nursing management and decision-making processes. Resilience is an important factor for nurses who constantly face challenging situations in a multifaceted health-care system.

Population ageing is a demographic transition and burdens every country’s health sector. A lack of social security combined with low government health-sector spending has made health-care utilisation difficult among elderly in many developing countries like India. This makes population ageing a global phenomenon for policymakers, researchers and stakeholders to discuss and debate in 21st century. The purpose of this paper is to examine the behavioural determinants of health-care utilisation among elderly population in Punjab.

This study examines health-care utilisation among the elderly population in Punjab. A structured questionnaire was used to collect the data in the state of Punjab, with a multi-stage stratified random sample of 385 respondents. Logit regression was used to analyse the association between several behavioural factors like age, gender, place of residence, source of livelihood, education and frequency of visits with health-care utilisation among elderly aged 60 and above.

This study revealed that gender, age, place of residence, source of livelihood, education and frequency of visits were significant determinants of health-care utilisation among elderly population.

This study directs the need to improve health-care utilisation in a country, reducing inequalities that exist among the elderly population with respect to socio-economic and demographic differences.

The COVID-19 pandemic has caused significant mortality and morbidity worldwide. However, the role of dietary patterns as a potential risk factor for COVID-19 has not been well established, especially in studies with large samples. Therefore, this study aims to identify and evaluate the association between major dietary patterns and COVID-19 among adults from Iran.

In this cross-sectional study, the authors included 9,189 participants aged 20–70 who participated in the Yazd Health Study (YaHS) and Taghzieh Mardom-e-Yazd study (TAMIZ). They used factor analysis to extract dietary patterns based on a food frequency questionnaire (FFQ). Then, they assessed the relationship between these dietary patterns and the odds of COVID-19.

This study identified two major dietary patterns: “high protein and high fiber” and “transitional”. Participants in the highest tertile of the “high protein and high fiber” dietary pattern, which included vegetables, fruits, dairy and various kinds of meats such as red meat, fish and poultry, had a lower odds of COVID-19 compared with those in the lowest tertile. However, the “transitional” dietary pattern did not affect the risk of COVID-19.

In conclusion, a “high protein, high fiber” diet may lower the odds of COVID-19. This study suggests that dietary patterns may influence the severity and spread of future similar pandemics.

This study aims to measure whether admittance in the quarantine ward due to COVID-19 can affect one’s mental health. Nowadays, many countries worldwide are battling with the threat of the COVID-19 contagion, and it is difficult to understand how the pandemic leaves psychological impacts on one’s well-being.

This research used qualitative and quantitative approaches to assess the psychological impacts of quarantine due to COVID-19. Population of the present study were 250 patients who were admitted in quarantine centres of Pakistan. The data analysis was conducted through univariate analysis using (ANVOVA) software.

This study found that patients who were quarantined due to the COVID-19 infection displayed multiple psychological symptoms such as a lack of self-control, anxiety, low general health and vitality, depression and negative well-being.

There is an urgency to provide psychological treatments to each afflicted person and their family members to establish a healthy community.

This research investigates whether admittance in the quarantine ward due to COVID-19 can affect mental health in Pakistan.