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This study aims to facilitate access to vascular disease screening for low-income individuals living in remote and conflict areas based on the results of a pilot trial in Colombia. Also, to increase the amount of diagnosis training of vascular surgery (VS) in civilians.

The operation method includes five stages: strategy development and adjustment; translation of the strategy into a real-world setting; operation logistics planning; strategy analysis and adoption. The operation plan worked efficiently in this study’s sample. It demonstrated high sensibility, efficiency and safety in a real-world setting.

The authors developed and implemented a flow model operating plan for screening vascular pathologies in low-income patients pro bono without proper access to vascular health care. A total of 140 patients from rural areas in Colombia were recruited to a controlled screening session where they underwent serial noninvasive ultrasound assessments conducted by health professionals of different training stages in VS.

The plan was designed to be implemented in remote, conflict areas with limited access to VS care. Vascular injuries are critically important and common among civilians and military forces in regions with active armed conflicts. As this strategy can be modified and adapted to different medical specialties and geographic areas, the authors recommend checking the related legislation and legal aspects of the intended areas where we will implement this tool.

Different sub-specialties can implement the described method to be translated into significant areas of medicine, as the authors can adjust the deployment and execution for the assessment in peripheral areas, conflict zones and other public health crises that require a faster response. This is necessary, as the amount of training to which VS trainees are exposed is low. A simulated exercise offers a novel opportunity to enhance their current diagnostic skills using ultrasound in a controlled environment.

Evaluating and assessing patients with limited access to vascular medicine and other specialties can decrease the burden of vascular disease and related complications and increase the number of treatments available for remote communities.

It is essential to assess the most significant number of patients and treat them according to their triage designation. This management is similar to assessment in remote areas without access to a proper VS consult. The authors were able to determine, classify and redirect to therapeutic interventions the patients with positive findings in remote areas with a fast deployment methodology in VS.

Access to health care is limited due to multiple barriers and the assessment and response, especially in peripheral areas that require a highly skilled team of medical professionals and related equipment. The authors tested a novel mobile assessment tool for remote and conflict areas in a rural zone of Colombia.

Globally, hepatitis C treatment uptake is lower among people who are homeless or unstably housed compared to those who are housed. Understanding and addressing this is essential to ensure no one is left behind in hepatitis C elimination efforts. This study aims to explore peoples’ experiences of unstable housing and health care, and how these experiences influenced engagement in hepatitis C treatment.

Purposive sampling was used to recruit people with lived experience of injection drug use, hepatitis C and unstable housing in Melbourne, Australia. In-depth semistructured interviews were conducted and a case study approach with interpretative phenomenological analysis was used to identify personal experiential themes and group experiential themes.

Four people were interviewed. The precarious nature of housing for women who inject drugs was a group experiential theme, however, this did not appear to be a direct barrier to hepatitis C treatment. Rather, competing priorities, including caregiving, were personal experiential themes and these created barriers to treatment. Another group experiential theme was “right place, right time, right people” with these three elements required to facilitate hepatitis C treatment.

There is limited research providing in-depth insight into how personal experiences with unstable housing and health care shape engagement with hepatitis C treatment. The analyses indicate there is a need to move beyond a “one size fits-all” approach to hepatitis C care. Instead, care should be tailored to the needs of individuals and their personal circumstances and regularly facilitated. This includes giving greater attention to gender in intervention design and evaluation, and research more broadly.

The purpose of this study is to develop a domain independent, cost-effective, time-saving and semi-automated ontology generation framework that could extract taxonomic concepts from unstructured text corpus. In the human disease domain, ontologies are found to be extremely useful for managing the diversity of technical expressions in favour of information retrieval objectives. The boundaries of these domains are expanding so fast that it is essential to continuously develop new ontologies or upgrade available ones.

This paper proposes a semi-automated approach that extracts entities/relations via text mining of scientific publications. Text mining-based ontology (TmbOnt)-named code is generated to assist a user in capturing, processing and establishing ontology elements. This code takes a pile of unstructured text files as input and projects them into high-valued entities or relations as output. As a semi-automated approach, a user supervises the process, filters meaningful predecessor/successor phrases and finalizes the demanded ontology-taxonomy. To verify the practical capabilities of the scheme, a case study was performed to drive glaucoma ontology-taxonomy. For this purpose, text files containing 10,000 records were collected from PubMed.

The proposed approach processed over 3.8 million tokenized terms of those records and yielded the resultant glaucoma ontology-taxonomy. Compared with two famous disease ontologies, TmbOnt-driven taxonomy demonstrated a 60%–100% coverage ratio against famous medical thesauruses and ontology taxonomies, such as Human Disease Ontology, Medical Subject Headings and National Cancer Institute Thesaurus, with an average of 70% additional terms recommended for ontology development.

According to the literature, the proposed scheme demonstrated novel capability in expanding the ontology-taxonomy structure with a semi-automated text mining approach, aiming for future fully-automated approaches.

This survey explores the application of real options theory to the field of health economics. The integration of options theory offers a valuable framework to address these challenges, providing insights into healthcare investments, policy analysis and patient care pathways.

This research employs the real options theory, a financial concept, to delve into health economics challenges. Through a systematic approach, three distinct models rooted in this theory are crafted and analyzed. Firstly, the study examines the value of investing in emerging health technology, factoring in future advantages, associated costs and unpredictability. The second model is patient-centric, evaluating the choice between immediate treatment switch and waiting for more clarity, while also weighing the associated risks. Lastly, the research assesses pandemic-related government policies, emphasizing the importance of delaying decisions in the face of uncertainties, thereby promoting data-driven policymaking.

Three different real options models are presented in this study to illustrate their applicability and value in aiding decision-makers. (1) The first evaluates investments in new technology, analyzing future benefits, discount rates and benefit volatility to determine investment value. (2) In the second model, a patient has the option of switching treatments now or waiting for more information before optimally switching treatments. However, waiting has its risks, such as disease progression. By modeling the potential benefits and risks of both options, and factoring in the time value, this model aids doctors and patients in making informed decisions based on a quantified assessment of potential outcomes. (3) The third model concerns pandemic policy: governments can end or prolong lockdowns. While awaiting more data on the virus might lead to economic and societal strain, the model emphasizes the economic value of deferring decisions under uncertainty.

This research provides a quantified perspective on various decisions in healthcare, from investments in new technology to treatment choices for patients to government decisions regarding pandemics. By applying real options theory, stakeholders can make more evidence-driven decisions.

Decisions about patient care pathways and pandemic policies have direct societal implications. For instance, choices regarding the prolongation or ending of lockdowns can lead to economic and societal strain.

The originality of this study lies in its application of real options theory, a concept from finance, to the realm of health economics, offering novel insights and analytical tools for decision-makers in the healthcare sector.

Healthcare workers’ (HCWs’) job-related high exposure to Covid-19 virus arouses fear of Covid-19 among them. Based on the Theory of Mind (ToM), the study predicts that fears will lead to negative psychological (psychological distress) and behavioral (withdrawal intentions) outcomes. ToM is also used to identify social intelligence as a means to counter fear of Covid-19 on heightened psychological distress and increased withdrawal intentions.

To investigate the study design, a sample of 262 HCWs, including doctors, nurses and technicians, were surveyed using standardized questionnaires.

As predicted, Covid-19 fear led to increased withdrawal intentions with heightened psychological distress partially mediating the relationship. The alleviating role of social intelligence on the effects of Covid-19 was supported as high social intelligence reduced HCWs’ turnover intentions, with decreased psychological distress partially mediating the relationship.

Given the universality of the Theory of Mind (ToM), the findings of this study are likely to be generalizable to all pandemics. The study results support the increased application of ToM in organizational settings and have both theoretical and practical implications for health administrators. Based on study results, health administrators are exhorted to develop ToM-based mental models to understand and deal with the fear of contagious diseases. Health administrators can also increase HCWs’ social intelligence to deal with the negative perceptual and behavioral outcomes arising from the emotions aroused by the nature of their work.

The COVID-19 pandemic has posed many challenges in almost all sectors around the globe. Because of the pandemic, government entities responsible for managing health-care resources face challenges in managing and distributing their limited and valuable health resources. In addition, severe outbreaks may occur in a small or large geographical area. Therefore, county-level preparation is crucial for officials and organizations who manage such disease outbreaks. However, most COVID-19-related research projects have focused on either state- or country-level. Only a few studies have considered county-level preparations, such as identifying high-risk counties of a particular state to fight against the COVID-19 pandemic. Therefore, the purpose of this research is to prioritize counties in a state based on their COVID-19-related risks to manage the COVID outbreak effectively.

In this research, the authors use a systematic hybrid approach that uses a clustering technique to group counties that share similar COVID conditions and use a multi-criteria decision-making approach – the analytic hierarchy process – to rank clusters with respect to the severity of the pandemic. The clustering was performed using two methods, k-means and fuzzy c-means, but only one of them was used at a time during the experiment.

The results of this study indicate that the proposed approach can effectively identify and rank the most vulnerable counties in a particular state. Hence, state health resources managing entities can identify counties in desperate need of more attention before they allocate their resources and better prepare those counties before another surge.

To the best of the authors’ knowledge, this study is the first to use both an unsupervised learning approach and the analytic hierarchy process to identify and rank state counties in accordance with the severity of COVID-19.

Global brands have become increasingly vulnerable to external disruptions that have negative spillover effects on consumers, business and brands. This research area has recently garnered interest post-pandemic yet remains fragmented. The purpose of this paper is to recognize the most impactful exogenous brand crisis (EBC) and its affective and behavioural impact on consumers.

In Study 1, we applied repertory grid technique (RGT), photo elicitation method and ANOVA comparisons, to identify the most significant EBC, in terms of repercussions on consumer purchases. In Study 2, we performed collage construction and content analysis to ascertain the impact of the identified significant crisis (from Study 1) on consumer behaviour in terms of affective and behavioural changes.

Study 1 results reveal Spread-of-diseases and Natural disaster to be the most impactful EBC based on consumer’s purchase decisions. Study 2 findings uncover three distinct themes, namely, deviant demand, emotional upheaval and community bonding that throws light on the affective and behavioural changes in consumer behaviour during the two significant EBC events.

The collated results of the two studies draw insights towards understanding the largely unexplored conceptualisation of EBC from a multi-level (micro-meso-macro) perspective. The integrated framework drawn, highlight the roles and influences of different players in exogenous brand crisis management and suggests future research agendas based on theoretical underpinnings.

To the best of our knowledge, this is the first study which identifies the most important EBC and explicates its profound impact on consumer purchase behaviour, providing critical insights to brand managers and practitioners to take an inclusive approach towards exogenous crises.

We study five exogenous shocks: climate, violence, price hikes, spoilage and the COVID-19 lockdown. We analyze the association between these shocks and trader characteristics, reflecting trader vulnerability.

Using primary survey data on 1,100 Nigerian maize traders for 2021 (controlling for shocks in 2017), we use probit models to estimate the probabilities of experiencing climate, violence, disease and cost shocks associated with trader characteristics (gender, size and region) and to estimate the probability of vulnerability (experiencing severe impacts).

Traders are prone to experiencing more than one shock, which increases the intensity of the shocks. Price shocks are often accompanied by violence, climate and COVID-19 shocks. The poorer northern region is disproportionately affected by shocks. Northern traders experience more price shocks while Southern traders are more affected by violence shocks given their dependence on long supply chains from the north for their maize. Female traders are more likely to experience violent events than men who tend to be more exposed to climate shocks.

The data only permit analysis of the general degree of impact of a shock rather than quantifying lost income.

This paper is the first to analyze the incidence of multiple shocks on grain traders and the unequal distribution of negative impacts. It is the first such in Africa based on a large sample of grain traders from a primary survey.