Insight into the Epidemiology Knowledge Transfer
Authors: Davtalab Esmaeili Elham , Dastgiri Saeed 
Published: April 2023

knowledge is a fluid mixed of experiences, existing information, values, and expert insight, which is acquired by education and experience. Knowledge is classified into two major types, namely explicit and tacit. Unlike explicit knowledge, the tacit knowledge is intuitive and exists in the human brain, and cannot be simply codified and transferred.1Epidemiology is the scientific and systematic study of the occurrence, dispersion, and determinants of health-related conditions in a specific population at a point or period of time in order to manage health issues. The most important goals of epidemiology are: 1. planning for health services, 2. reducing the rate of morbidity and mortality, 3. determining the natural history of diseases, 4. applying different types of prevention, and 5. evaluating health programs. 2 Knowledge is useful when its results are used for decisions-making. Knowledge transfer mediates between knowledge production and its utilization. Indeed, a successful transfer is an essential factor contributing to the conversion of knowledge into practice.3 Knowledge transfer is defined as the process of conveyance of knowledge to individuals, groups, and organizations to facilitate decision-making and activities. Effective knowledge transfer of epidemiology means changing the information, attitude, and behavior of health service providers, individuals, patients, and managers. 4 Knowledge transfer consists of two key components, including sender and receiver. Performing an efficient knowledge transfer requires producing standardized information based on the target group's demands. Knowledge translation is often confused with knowledge transfer. The field of knowledge translation was created to ensure the optimal communication between people using knowledge and those producing it. Advanced epidemiological methods such as structural equation modeling and social network analysis are used for effective knowledge transfer. Analysis of Social Networks Social networks refer to a group of organizations or people who are tied through social relationships such as friendship, cooperation, or information exchange. Social network analysis such as graph analysis methods is a powerful diagnostic method for investigating the pattern of relationship linking members of a group.5 In this method, transferring certain knowledge is possible by identifying influential people. Influential person is someone who is skilled to persuade other individuals in socio network. Social network analysis can be used in decision-making and policy-making, and it plays a significant role in knowledge transfer and improves the novelty of knowledge. For example, sharing knowledge between individual leads to the creation of a new knowledge that is greater than the total knowledge of each person. Relationship among individuals in the social network can be facilitate knowledge transference. Given that knowledge is embedded in the relationship, stronger relationships not only improve knowledge transference but also generate considerable knowledge. Structural Equation Modeling Structural equation modeling (SEM) is a comprehensive statistical model for exploring the correlation between latent and observed variables. SEM has several analytic techniques including analysis of variance, regression analysis, and factor analysis. Factor analysis is used to estimate latent variables based on the observed variables. The data extracted from observational, nonexperimental, and experimental studies can be analyzed by SEM. Although SEM is employed in many fields, it has not been extensively used in epidemiology yet.6Given the above discussion, effective knowledge transfer of epidemiology means changing the information, attitude, and behavior of health service providers, individuals, patients, and managers. Generating standardized information based on the target group's demands is essential to perform efficient knowledge transfer. Advanced epidemiological methods such as structural equation modeling and social network analysis are used for effective knowledge transfer.