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This study aimed to propose a performance-oriented approach of automatically generative design and optimization of hospital building layouts in consideration of public health emergency, which intended to conduct reasonable layout design of hospital building to meet different performance requirements for both high efficiency during normal periods and low risk in the pandemic.

The research design follows a sequential mixed methodology. First, key points and parameters of hospital building layout design (HBLD) are analyzed. Then, to meet the requirements of high efficiency and low risk, adjacent preference score and infection risk coefficient are constructed as constraints. On this basis, automatic generative design is conducted to generate building layout schemes. Finally, multi-objective deviation analysis is carried out to obtain the optimal scheme of hospital building layouts.

Automatic generative design of building layouts that integrates adjacent preferences and infection risks enables hospitals to achieve rapid transitions between normal (high efficiency) and pandemic (low risk) periods, which can effectively respond to public health emergencies. The proposed approach has been verified in an actual project, which can help systematically explore the solution for better decision-making.

The form of building layouts is limited to rectangles, and future work can explore conducting irregular layouts into optimization for the framework of generative design.

The contribution of this paper is the developed approach that can quickly and effectively generate more hospital layout alternatives satisfying high operational efficiency and low infection risk by formulating space design rules, which is of great significance in response to public health emergency.

The COVID-19 pandemic is not a foodborne infectious disease, but it has dramatically impacted food safety practices worldwide due to its potential for transmission through contaminated surfaces and food. Accordingly, the Omicron variant seems to have affected food-related activities and behaviours and disturbed food supply networks since its appearance in November 2021. Hence, this paper aims to assess how the Omicron variant impacted food safety knowledge, attitudes and practices amongst adult consumers in five countries: Bosnia and Herzegovina, North Macedonia, Serbia, Montenegro and Russia.

The study is based on an online survey. The questionnaire was developed and revised based on previous research on the impact of previous COVID-19 waves on food-related activities in several countries. The questionnaire was distributed through the SurveyMonkey platform from January 15 to February 25, 2022. It consisted of 29 multiple-choice and one-option questions organised into three sections. A total of 6,483 valid responses were received. Statistical Package for Social Sciences (SPSS) version 25.0 was used to analyse the survey results.

According to the survey findings, food safety practices evolved during the Omicron wave in the studied countries. Firstly, less than half of the sample used a face mask whilst purchasing food. Secondly, regarding food safety knowledge, the survey results suggest that there is still a lack of knowledge in the studied countries. Thirdly, the survey indicates a lack of knowledge amongst the respondents regarding food safety attitudes. For instance, more than a third of the sample (34.4%) are unsure whether the COVID-19 virus can be transmitted through food. These results are surprising and alarming, especially considering that our sample has a higher education than the population of the studied countries.

The main limitation of this research is the sample bias. Survey participants were randomly chosen, enrolled voluntarily and not rewarded. As a result, the questionnaire was self-administered and completed exclusively by people motivated by an interest in the topic. Consequently, our survey does not represent the general population of the studied countries. People with a high degree of education and women, for example, were overrepresented in our sample.

This study is unique in that it is the first to gather information and analyse people’s perceptions of the effects of the Omicron variant on food safety. As a result, the findings of this survey offer a solid basis for future investigations into the impact of the pandemic on food safety in the Balkan region and Russia. This study can help further understand the changes during the COVID-19 pandemic. It provides crucial insights that can be used to guide future decision-making and policy development regarding improving food safety practices. This and other future studies will be a foundation for organisational and government readiness for future shocks, crises and pandemics. The effects of the present Ukrainian conflict on agricultural systems and supply chains throughout the globe (e.g. increased food prices) show that this is timely, urgent and highly required.

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.

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.

This study aims to examine how the theory of planned behaviour and technology acceptance theory can be used to understand the adoption of non-pharmaceutical interventions (NPIs). The relationships between attitudes, behavioural intentions towards using NPIs, actual use of NPIs and word-of-mouth (WOM) were examined and compared between early and late adopters.

A survey was conducted to test the hypotheses with partial least squares structural equation modelling (n = 278).

The results indicate that relationships between attitudes, intentions and behavioural intentions were positive and significant in the whole data set – and that there were differences between the early and late adopters. WOM had no substantial relationship with actual usage and early adopters’ behavioural intentions.

This research gives a better sense of how WOM impacts attitudes, behavioural intentions and actual usage among early and late adopters of NPIs and highlights the effectiveness of WOM, especially among late adopters of NPIs. Furthermore, using the TAM allows us to make specific recommendations regarding encouraging the use of NPIs. A new three-stage communications model is introduced that uses early adopters as influencers to reduce the NPI adoption time by late adopters.