This paper explores the correlation between emotional intelligence (EI) and transformational leadership behavior, highlighting how leaders with high EI tend to excel in fostering positive change and motivating their teams. Emotional intelligence, which includes self-awareness, empathy, and emotional regulation, plays a crucial role in transformational leadership by enabling leaders to inspire, influence, and connect with their followers on a deeper level. Through a review of existing research and case studies, the paper demonstrates how emotionally intelligent leaders are more effective in driving innovation, fostering commitment, and creating a supportive organizational culture. The findings suggest that developing EI can enhance transformational leadership capabilities, ultimately leading to improved organizational performance and employee satisfaction. This study provides valuable insights for leadership development programs and underscores the importance of emotional intelligence in achieving leadership success.

Introduction: Various changes in technologies have impacted the public health monitoring systems especially in the United States. AI and IoT, Big Data, block chains have enhanced the ways that diseases are monitored, vaccinations are administered and emergency responses are coordinated. Issues like the infrastructure constraints, privacy issues and variability in technological implementation graduality’s limit the extent to which these technologies can be scaled up in U.S. public health systems.

Objective: The aim of this study is to evaluate the impact of technological improvement on the improvement of the public health monitoring systems in United States. It assesses the utilization of superior technologies and considers the observed enhancement of general health status together with the problems identified in the application of technologies.

Methods: A quantitative cross-sectional survey was filled by 400 participants from the PH and technology workers working throughout the USA in the public health sector. Community and purposive sampling techniques were used and data were self-administered from the participants through an online structured questionnaire. The survey included questions about participants’ degrees of awareness of AI, IoTs, Big Data and blockchain, concerning their applicability to public health surveillance and the potential challenges to their application. Descriptive statistics, chi-square, independent sample t test, one way analysis of variance, Pearson correlation analysis and multiple regression analysis were conducted in SPSS V 26.

Results: The current study revealed that the use of AI, IoT, Big Data and blockchain technologies has accelerated the enhancement of public health surveillance, including disease detection and vaccination management. Awareness of these technologies was directly related to perceived impact on public health to the extent of r = 0.75, p < 0.001. Other issues like lack of funding, lack of technical knowledge and issues surrounding privacy were cited as major reasons for inadequate scaling up.

Conclusion: The results point out that new technology has a potential for advancing the system for monitor public health in the United States but there are some barriers. Challenges that prevent expansion and growth of these technologies include inadequate infrastructure, funding and data protection must be overcome in order to enhance the efficiency of the technologies to deliver on their intended health benefits. More work is necessary to expand understanding of longevity of these phenomena and ways of preventing these challenges.

This paper explores the critical factors in evaluating service quality within the public sector, focusing on the unique challenges faced by government agencies and public institutions. It examines various metrics used to assess service quality, including efficiency, accessibility, transparency, responsiveness, and citizen satisfaction. The study also highlights the difficulties in applying private-sector evaluation models to public services due to differing goals, resource constraints, and stakeholder expectations. Additionally, best practices for enhancing service quality are discussed, with an emphasis on the need for continuous improvement, stakeholder engagement, and adopting technology-driven solutions. The paper aims to provide a comprehensive understanding of how public sector organizations can measure and improve service delivery to better serve citizens.