In the history of public health, space has evolved through several stages driven by shifts in concepts of disease control. The history of public health is summarized by George Rosen in six phases: Origins (before 500 CE), Middle Ages (500–1500), Mercantilism and Absolutism (1500–1750), Enlightenment and Revolution (1750–1830), Industrialism and the Sanitary Movement (1830–1875), and the Bacteriological Era (1875–present). By integrating architectural sociology—a temporal lens examining the interplay between architecture, individuals, and society—this study investigates how architects historically responded to public health challenges, offering critical insights for contemporary healthy habitat design. Architecture not only addresses survival needs but also materializes societal consciousness. The progression of health-related cognition (e.g., germ theory), behavioural norms (e.g., hygiene practices), infrastructure systems (e.g., sanitation networks), and scientific advancements collectively redefined spatial paradigms. Architects constructed temples, thermae, lazarettos, Beitian Yangbingfang (charitable infirmaries), anatomical theaters, quarantine hospitals, tenements, mass housing, and biosafety laboratories. These cases exemplify the co-evolution of “Concept” (disease control ideologies), “Technology” (construction methods), and “Space” (built environments). By synthesizing centuries of public health spatial practices, this research deciphers the dynamic interplay among “Concept, Technology, and Space”. Leveraging historical patterns, we propose a predictive framework to refine future spatial strategies in anticipation of emerging health crises.

Low enrollment intention threatens the funding pools of rural insurance schemes in developing countries. The purpose of this study is to investigate how social capital enhances the enrollment of health insurance among rural middle-aged and elderly. We propose that social capital directly increases health insurance enrollment, while indirectly influences health insurance through health risk avoidance. We used data from the China Health and Retirement Longitudinal Study (wave 4) dating the year of 2018, instrumental variable estimation was introduced to deal with the endogeneity problem, and the mediation analysis was used to examine the mechanism of social capital on insurance enrollment. The results show that social capital is positively related to social health insurance enrollment, and the relationship between social capital and social health insurance enrollment is mediated by health risk avoidance.

There are diverse effects in consequence of exposure to radiofrequency electromagnetic fields (RF-EMF). The interactions of fields and the exposed body tissues are related to the nature of exposure, tissue comportment, field strength and signal frequency. These interactions can crop different effects.

Universal Health Coverage is a health insurance system that ensures every citizen in the population has equitable access to quality and effective promotive, preventive, curative, and rehabilitative health services. Meanwhile, the Medan City Government of Indonesia is trying to improve health services through the Medan Berkah Health Insurance Program by adopting Universal Health Coverage, which aims to provide Universal Health Coverage to the entire community. This study aims to explain the implementation and projection of the development of health services of the Medan City Government with the Universal Health Coverage System in the Medan Berkah Health Insurance Program which is intended as a step in providing opportunities for all people to get equal opportunities in health services, especially for the poor. This research uses qualitative research by using the literacy study method by studying related documents and conducting in-depth observations. Data analysis included data reduction, presentation, and conclusion drawing. The Medan City Government implemented the Universal Health Coverage Program in Jaminan Kesehatan Medan Berkah, which aims to improve health services in the city. The government is committed to simplifying the bureaucracy, managing the medical workforce, and collaborating with stakeholders and the community. However, challenges include low community participation, limited resources, lack of coordination, and limited access to information, which hinder the successful implementation of the program.

The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant interest in modern agriculture. The appeal of AI arises from its ability to rapidly and precisely analyze extensive and complex information, allowing farmers and agricultural experts to quickly identify plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has gained significant attention in the world of agriculture and agronomy. By harnessing the power of AI to identify and diagnose plant diseases, it is expected that farmers and agricultural experts will have improved capabilities to tackle the challenges posed by these diseases. This will lead to increased effectiveness and efficiency, ultimately resulting in higher agricultural productivity and reduced losses caused by plant diseases. The use of artificial intelligence (AI) in the detection and diagnosis of plant diseases has resulted in significant benefits in the field of agriculture. By using AI technology, farmers and agricultural professionals can quickly and accurately identify illnesses affecting their crops. This allows for the prompt adoption of appropriate preventative and corrective actions, therefore reducing losses caused by plant diseases.