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PurposeThe authors investigated the effect of basic human values in the prediction of COVID-19 vaccination behavior amongst public security agents in Brazil.Design/methodology/approachA sample of 15,313 Brazilian public security agents responded to the portrait values questionnaire and a COVID vaccination behavior measure. Multidimensional scaling analysis (MDS) was used to observe the order of the predicted by the theory. For hypotheses, the authors ran a series of Structural equation modeling (SEM) with direct effects between values and vaccination rate.FindingsResults suggest that the values of conservation and self-transcendence positively predicted vaccination. A nonsignificative negative prediction was obtained for openness to change and self-enhancement values on vaccination behavior.Research limitations/implicationsData were collected using self-report questionnaires.Practical implicationsInstitutional management should encourage capacitation campaigns aimed at public security agents, enabling a significant increase in vaccine protection for the public security institutions.Social implicationsThe reinforcement of conservation and self-transcendence values lead to the perception of the vaccine as a measure of caring for people in general and for the members of the ingroup, hence motivating the vaccination behavior.Originality/valueThe findings confirm that values encourage individuals to be vaccinated, due to their intrinsic motivation. This relationship did not appear to be clearly tested by previous empirical studies.
ABSTRACT
It is important for social public security and urban management to explore the spread of infectious diseases. A city-level structured prediction and simulation model for COVID-19 is proposed. This model is consisted of SEIR and social network model on the basis of latest infectious disease dynamics theory and real geographic networks. The prediction region is divided into multiple levels. Specifically, a bipartite network is applied to simulate the relationship between public facilities and community nodes at the macro level, and a modified SEIR is applied to simulate the infection within nodes at the micro level. Besides, intelligent agent is applied to track the individual transmission process. The contrast experimental results based on the confirmed and cursed cases of Wuhan and Beijing in 2020 published by National Health Commission, show that the proposed model has better flexibility and higher accuracy, and reflects the distribution and movement of people more directly. © 2022 Institute of Computing Technology. All rights reserved.
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This article analyzes the principal events of 2021-the second year of the coalition government led by Luis Lacalle Pou-which was signed by two main issues. In the first place, the second year of the COVID-19 pandemic in which the government manages to deploy a successful vaccination campaign;and, secondly, the initiative of a direct democracy mechanism led by the political and social opposition to derogate 135 articles of the Urgent Consideration Bill (LUC, for its initials in spanish) approved in 2020. It is argued that the combination of both issues put a (transitory) brake to the urgency and deployment of the government's agenda. To do this, first the economic and social situation is briefly described, and then the political scenario configured between government and opposition. Third, prolonged presidential approval is analyzed from a twofold perspective: the honeymoon effect and the "rally round the flag" effect. Then, one of the central issues of the LUC and of the public agenda is addressed: security and its relationship with government and public opinion. Finally, we analyze the referendum process and its relevance as a new beginning for the coalition government.
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The information and knowledge society of the 21st century, characterized by the massive and docile improvement of ICTs, demanded reasoning that generated educational models, which were adapted to the moment. A fact that moved us in the research, to analyze pedagogy in the context of technological curriculum using computer and telematics means, for the progress of educational training in the period of Covid-19. Typologically, the research was of an applied nature and, from the point of view of its objectives, it was characterized as exploratory and descriptive, where a hybrid method between qualitative and quantitative, had its roots in the bibliographic review and in the campus work characterized in the interview and questionnaire to the constituted participants. by teachers, scientific researchers and students of the degree and master's degree courses in police science at the Academy of Police Sciences. Qualitative data, discourses and contents, including quantitative ones, were basically analyzed using philological and statistical techniques. The participants unanimously affirmed that the impact of ICTs was positive in the development of educational and corporate training at ACIPOL. The majority justified that the distance study organized in computer resources in the calculation of the tools configured in a digital way, facilitated the acquisition of more experiences in the practice of the teaching-learning process. Consecutively, it was possible to bet that the study contributed a lot to the dissemination of the importance of computer resources for the maintenance of educational acts during Covid-19. And, the continuous training of personnel in the handling and improvement of cybernetic instruments constitutes the biggest challenge for the academic environment.
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In recent years, public security emergencies such as COVID-19, rainstorm and waterlogging have occurred frequently, posing a great threat to personal and property safety. At the same time, the panic buying behaviour induced by public security incidents, i.e., synchronous buying behaviour, further strengthens the harm caused by the event. For example, simultaneous panic buying of face masks amid the pandemic has sparked fears of a shortage. The food rush after the rainstorm caused food shortage in some groups and the price soared, which easily led to the extreme behaviour of the people. Based on this, this paper constructs a game model of synchronous buying under public emergencies, analyses the psychological incentive of synchronous buying behaviour and the formation mechanism of synchronous panic buying behaviour, and puts forward effective measures to alleviate synchronous buying behaviour. Finally, we verify the model and its application through an actual case. Copyright © 2021 Inderscience Enterprises Ltd.
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During the development of COVID-19 virus's global epidemic, the fundamental research and various applications of crowd dynamics-oriented observation theories have attracted much attention from many researchers and people all over the world within some related disciplines, such as public health, clinical medicine, geography, public management, etc. Researchers conducted many interdisciplinary explorations in theories and methods of monitoring epidemic dynamics scientifically, preventing and controlling spatial transmission precisely, predicting accurately, and responding effectively. However, no crowd dynamics-oriented observation theories have been proposed in literature so far. This paper revisits the concept and introduces a theory framework of crowd dynamics-oriented observation, which tries to include the core theories of observation from geospatial big data and to support diverse potential developments. Firstly, this article introduces the research background of crowd dynamics-oriented observation, and then summarizes its three core questions (how to observe its change, how to analyze its change, and how to control its change). From the interdiscipline view of geographic information science, surveying and mapping science, this paper explains the research significance and disciplinary value of crowd dynamics-oriented observation theories. Secondly, this paper introduces a framework of crowd dynamics-oriented observation and its spatiotemporal application, and then elaborates on the bottleneck problems of the key observation theories of crowd dynamics, such as fundamental space-time framework theory, space-time quantification and comprehensive observation theory, spatiotemporal process optimization theory, etc. Thirdly, this paper preliminarily introduces some changes of crowd dynamics-oriented observation theories, for example, refined observation driven by the application needs of digital society governance and public safety/health emergency, personal privacy protection and personalized observations by balancing the public interest and personal privacies, the development of integrated observation theories for human-oriented observation and earth-oriented observation, and the theory of crowd dynamicsoriented observation for high-level management and service. Finally, this article points out the potential directions of crowd dynamics-oriented observation theory and methods, such as, the development of big datadriven crowd perception, multi-space refined crowd dynamics observation, and human-land systematical interaction modeling, so as to realize some differentiated, integrated, and hierarchical crowd dynamics-oriented observations. All potential theories are helpful to the scientific decision-making of public management and public service. The crowd dynamics-oriented observation theory should focus on the fundamental research questions related to studying, analyzing, and servicing human beings, which has become a research frontier in geospatial information science, and could play very important roles in supporting national development strategies, such as "New urbanization", "beautiful China", "artificial intelligence", and "new infrastructure", so as to contribute to a green, efficient, smart, and sustainable regional and urban development. © 2021, Science Press. All right reserved.
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The outbreak of COVID-19 in 2020 has had a serious impact on society and drawn the attention of all sectors of society to major emergency public security incidents. So this study focused on the social distance which is one of the most effective methods to reduce the transmission rate of the epidemic to conduct research. In order to visually describe the effect of social distance obedience behavior, we use Anylogic to simulate the subway station with high pedestrian traffic in daily life and visualize the process and rate of transmission. Social distance was introduced as a primary variable, mask-wearing rate as a secondary variable, and the simulation set the movement trajectory of pedestrians and used the "controlled variable method"to analyze their effects on infection. The results show that both maintaining a social distance of more than 1.25 meters and wearing a mask rate of more than 70% can effectively inhibit the spread of the epidemic, and the combined effect of both is more effective in infection control. © 2021 ACM.