Convergence model of AI and IoT for virus disease control system.

Recently, virus diseases, such as SARS-CoV, MERS-CoV, and COVID-19, continue to emerge and pose a severe public health problem. These diseases threaten the lives of many people and cause serious social and economic losses. Recent developments in information technology (IT) and connectivity have led to the emergence of Internet of Things (IoT) and Artificial Intelligence (AI) applications in many industries. These industries, where IoT and AI together are making significant impacts, are the healthcare and the diagnosis department. In addition, by actively communicating with smart devices and various biometric sensors, it is expanding its application fields to telemedicine, healthcare, and disease prevention. Even though existing IoT and AI technologies can enhance disease detection, monitoring, and quarantine, their impact is very limited because they are not integrated or applied rapidly to the emergence of a sudden epidemic. Especially in the situation where infectious diseases are rapidly spreading, the conventional methods fail to prevent large-scale infections and block global spreads through prediction, resulting in great loss of lives. Therefore, in this paper, various sources of infection information with local limitations are collected through virus disease information collector, and AI analysis and severity matching are performed through AI broker. Finally, through the Integrated Disease Control Center, risk alerts are issued, proliferation block letters are sent, and post-response services are provided quickly. Suppose we further develop the proposed integrated virus disease control model. In that case, it will be possible to proactively detect and warn of risk factors in response to infectious diseases that are rapidly spreading worldwide and strengthen measures to prevent spreading of infection in no time.

Urban Public Epidemic Prevention and Control Model Based on Nonlinear Differential Equations

This paper proposes a new epidemiological mathematical model based on the dynamics of urban public epidemic prevention and control model. Then, the nonlinear differential equation of epidemic propagation dynamics is deduced. Secondly, this paper uses the exponential equation to fit the curve, takes three days as the optimal window time, and estimates the turning point of the urban public epidemic. Again, this paper establishes a dynamic model of dynamic experience transfer. Finally, this paper uses the COVID19 example to verify the public epidemic prevention and control problems described in the text. Experimental simulations show that the algorithm can better grasp important epidemiological dynamics.

Role of Religious Leaders in COVID-19 Prevention: A Community-Level Prevention Model in Sri Lanka.

The COVID-19 pandemic has affected all countries irrespective of their state of development. In countries with traditional societies, religious leaders have been acknowledged as key stakeholders in community engagement activities, including disease prevention. A community-level prevention model was established in 2020 by the Health Promotion Bureau (HPB), Sri Lanka, which incorporated mobilisation of the clergy to support the prevention and response schemes to COVID-19 with non-governmental stakeholders. This model was part of a more extensive community engagement network established by the HPB in cooperation with the country offices for WHO and UNICEF. Building trust, empowering behavioural traits applicable to minimise risks from COVID-19, leadership and coordination, message dissemination, addressing stigma and discrimination, supporting testing procedures, contact tracing activities and vaccination, building community resilience, spiritual and psychosocial support, and welfare provision are some of the useful factors that were identified in the model. Furthermore, a much broader and holistic approach is needed to focus on health behaviours and social and cultural aspects in a multi-faceted nature. This paper highlights a novel COVID-19 prevention model with active involvement of religious leaders that can be implemented in low resource settings. Our experience from Sri Lanka demonstrates the feasibility of implementing this model to mitigate the disastrous situation following the COVID-19 outbreak.

Workplace Interventions in Response to COVID-19: an Occupational Health Psychology Perspective.

The outbreak of COVID-19 has imposed significant threats to individuals' physical health and has substantially changed the socioeconomic order and the nature of our work and life all over the world. To guide organizations to design effective workplace interventions to mitigate the negative impacts of COVID-19, we take the occupational health psychology (OHP) perspective to propose a framework that highlights important areas for organizations to intervene in order to better protect workers' physical health and safety and to promote workers' psychological well-being. Specifically, we integrate the prevention-based public health model with the Total Worker Health (TWH) and OHP-based approaches to propose a comprehensive set of primary, secondary, and tertiary interventions that target different groups of employees with varied exposure risks to the new coronavirus. We believe these proposed interventions can contribute positively to the development of healthy and safe work. Implications of these proposed interventions for workers, organizations, and policy makers are also discussed.