This study investigated changes in lifestyles and psychological anxiety among Koreans during the Coronavirus Disease 2019 (COVID-19) pandemic using the 2020 data from the nationwide Korean Community Health Survey. The study outcomes were psychological anxiety about the infection and death, due to COVID-19. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the relationship between psychological anxiety and lifestyle changes. During the COVID-19 pandemic, people who practiced healthy behaviors and followed social distancing and quarantine regulations experienced increased psychological anxiety for infection and death. Daily life changes during the COVID-19 pandemic were not associated with psychological anxiety. The result of this study can provide baseline measures for further study on psychological anxiety during re-infection of COVID-19 and future pandemics in Korea.

The urgency of urban health in Indonesia is very worrying because most of Indonesia’s population now lives in urban areas with minimal supporting infrastructure. That prompted this study to analyze the government’s response to the healthy city development plan in the new capital city. This study uses a qualitative approach that focuses on thematic analysis. It helps check official government documents related to healthy city development plans. The relevant documents that were found were in the form of regulations. This regulation is Law of the Republic of Indonesia Number 3 of 2022 concerning the National Capital (Ibu Kota Negara, IKN). This official document was coded by maximizing the analysis tool, namely NVivo 12 Plus. This study succeeded in mapping several bare references in the healthy city development plan for the new capital city by the Indonesian government. Some of these primary references include the healthy city model (World Health Organization, WHO), the healthy city strategy (Cardiff), and (Vancouver). All of these primary references aim to improve the quality of life of residents in cities through city development that focuses on health. However, there are several challenges that the Indonesian government may face in the future, including problems with air pollution, environmentally friendly transportation, and the provision of green public spaces, health facilities, universal health services, and other infrastructure. This all requires adequate capacity and budget plans, including ensuring transparency in budget management. This study also encourages collaboration between the government, the private sector, and civil society to support the development of healthy cities that run well and sustainably.

Adequate sanitation is crucial for human health and well-being, yet billions worldwide lack access to basic facilities. This comprehensive review examines the emerging field of intelligent sanitation systems, which leverage Internet of Things (IoT) and advanced Artificial Intelligence (AI) technologies to address global sanitation challenges. The existing intelligent sanitation systems and applications is still in their early stages, marked by inconsistencies and gaps. The paper consolidates fragmented research from both academic and industrial perspectives based on PRISMA protocol, exploring the historical development, current state, and future potential of intelligent sanitation solutions. The assessment of existing intelligent sanitation systems focuses on system detection, health monitoring, and AI enhancement. The paper examines how IoT-enabled data collection and AI-driven analytics can optimize sanitation facility performance, predict system failures, detect health risks, and inform decision-making for sanitation improvements. By synthesizing existing research, identifying knowledge gaps, and discussing opportunities and challenges, this review provides valuable insights for practitioners, academics, engineers, policymakers, and other stakeholders. It offers a foundation for understanding how advanced IoT and AI techniques can enhance the efficiency, sustainability, and safety of the sanitation industry.

E-cigarettes pose a significant public health concern, particularly for youth and young adults. Policymaking in this area is complicated by changing consumption patterns, diverse user demographics, and dynamic online and offline communities. This study uses social network analytics to examine the social dynamics and communication patterns related to e-cigarette use. We analyzed data from various social media platforms, forums, and online communities, which included both advocacy for e-cigarettes as a safer smoking alternative and opposition due to health risks. Our findings inform targeted healthcare policy interventions, such as educational campaigns tailored to specific network clusters, regulations based on user interaction and influence patterns, and collaborations with key influencers to spread accurate health information.

The failure to achieve sustainable development in South Africa is due to the inability to deliver quality and adequate health services that would lead to the achievement of sustainable human security. As we live in an era of digital technology, Machine Learning (ML) has not yet permeated the healthcare sector in South Africa. Its effects on promoting quality health services for sustainable human security have not attracted much academic attention in South Africa and across the African continent. Hospitals still face numerous challenges that have hindered achieving adequate health services. For this reason, the healthcare sector in South Africa continues to suffer from numerous challenges, including inadequate finances, poor governance, long waiting times, shortages of medical staff, and poor medical record keeping. These challenges have affected health services provision and thus pose threats to the achievement of sustainable security. The paper found that ML technology enables adequate health services that alleviate disease burden and thus lead to sustainable human security. It speeds up medical treatment, enabling medical workers to deliver health services accurately and reducing the financial cost of medical treatments. ML assists in the prevention of pandemic outbreaks and as well as monitoring their potential epidemic outbreaks. It protects and keeps medical records and makes them readily available when patients visit any hospital. The paper used a qualitative research design that used an exploratory approach to collect and analyse data.

Hazards are the primary cause of occupational accidents, as well as occupational safety and health issues. Therefore, identifying potential hazards is critical to reducing the consequences of accidents. Risk assessment is a widely employed hazard analysis method that mitigates and monitors potential hazards in our everyday lives and occupational environments. Risk assessment and hazard analysis are observing, collecting data, and generating a written report. During this process, safety engineers manually and periodically control, identify, and assess potential hazards and risks. Utilizing a mobile application as a tool might significantly decrease the time and paperwork involved in this process. This paper explains the sequential processes involved in developing a mobile application designed for hazard analysis for safety engineers. This study comprehensively discusses creating and integrating mobile application features for hazard analysis, adhering to the Unified Modeling Language (UML) approach. The mobile application was developed by implementing a 10-step approach. Safety engineers from the region were interviewed to extract the knowledge and opinions of experts regarding the application’s effectiveness, requirements, and features. These interview results are used during the requirement gathering phase of the mobile application design and development. Data collection was facilitated by utilizing voice notes, photos, and videos, enabling users to engage in a more convenient alternative to manual note-taking with this mobile application. The mobile application will automatically generate a report once the safety engineer completes the risk assessment.