scholarly journals Descriptive analysis of a tuberculosis outbreak from a northern Saskatchewan First Nations community—December 2018 to May 2019

2021 ◽  
Vol 47 (11) ◽  
pp. 479-484
Author(s):  
Nnamdi Ndubuka ◽  
Braeden Klaver ◽  
Sabyasachi Gupta ◽  
Shree Lamichhane ◽  
Leslie Brooks ◽  
...  
Keyword(s):  
Risk Factors ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
First Nations ◽  
Descriptive Analysis ◽  
Outbreak Investigation ◽  
Active Case ◽  
Contact Investigation ◽  
Northern Saskatchewan

Background: The tuberculosis (TB) incidence rate for northern Saskatchewan First Nations on-reserve is 1.5 higher than the national average. In December 2018 a member of one of these communities was diagnosed with 4+ smear-positive TB, spurring an outbreak investigation. Objectives: To describe the public health response to TB outbreak investigation and highlight the risk factors associated with TB transmission in northern Saskatchewan; and to highlight the relevance of social network contact investigation tool in outbreak management. Methods: Descriptive analysis included active TB cases and latent TB infection (LTBI) cases linked by contact investigation to the index case. Data were collected from active TB case files. Statistical analyses were performed and social network analysis conducted using household locations as points of contact between cases. Results: A total of eight active TB cases and 41 LTBI cases were identified as part of the outbreak between December 2018 and May 2019. Half of the cases (4/8) were 25 to 34 years old, and five were smear negative. One-third of the people with LTBI were 15 to 24 years old, and about a half tested positive to the new tuberculin skin test (TST). The commonly reported risk factors for TB and LTBI cases were alcohol use, cigarette use, marijuana use, previous TB infection and homelessness. Social network analysis indicated a relationship between increased node centrality and becoming an active case. Conclusion: Real-time social network contact investigation used in active-case finding was very successful in identifying cases, and enhanced nursing support, mobile clinics and mobile X-ray worked well as a means of confirming cases and offering treatment. TB outbreaks in northern Saskatchewan First Nations on-reserve communities are facilitated by population-specific factors. Efforts to implement context-specific interventions are paramount in managing TB outbreaks and preventing future transmission.

Network Analysis for Economics and Management Studies

2016 ◽  
pp. 1-60 ◽  
Author(s):  
Lucio Biggiero
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Formation ◽  
Competitive Equilibrium ◽  
Group Structure ◽  
Network Modeling ◽  
Descriptive Analysis ◽  
Economic Networks ◽  
Main Research

Sociology and other social sciences have employed network analysis earlier than management and organization sciences, and much earlier than economics, which has been the last one to systematically adopt it. Nevertheless, the development of network economics during last 15 years has been massive, alongside three main research streams: strategic formation network modeling, (mostly descriptive) analysis of real economic networks, and optimization methods of economic networks. The main reason why this enthusiastic and rapidly diffused interest of economists came so late is that the most essential network properties, like externalities, endogenous change processes, and nonlinear propagation processes, definitely prevent the possibility to build a general – and indeed even partial – competitive equilibrium theory. For this paradigm has dominated economics in the last century, this incompatibility operated as a hard brake, and presented network analysis as an inappropriate epistemology. Further, being intrinsically (and often, until recent times, also radically) structuralist, social network analysis was also antithetic to radical methodological individualism, which was – and still is – economics dominant methodology. Though culturally and scientifically influenced by economists in some fields, like finance, banking and industry studies, scholars in management and organization sciences were free from “neoclassical economics chains”, and therefore more ready and open to adopt the methodology and epistemology of social network analysis. The main and early field through which its methods were channeled was the sociology of organizations, and in particular group structure and communication, because this is a research area largely overlapped between sociology and management studies. Currently, network analysis is becoming more and more diffused within management and organization sciences. Mostly descriptive until 15 years ago, all the fields of social network analysis have a great opportunity of enriching and developing its methods of investigation through statistical network modeling, which offers the possibility to develop, respectively, network formation and network dynamics models. They are a good compromise between the much more powerful agent-based simulation models and the usually descriptive (or poorly analytical) methods.

scholarly journals Toward a Stakeholder Perspective on Safety Risk Factors of Metro Construction: A Social Network Analysis

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ying Lu ◽  
Yu Zhang
Keyword(s):  
Risk Factors ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Government Regulation ◽  
Rapid Development ◽  
Construction Site ◽  
Safety Risk ◽  
Stakeholder Perspective ◽  
Bad Weather

The rapid development of the metro has greatly relieved the traffic pressure on the urban ground system, but the frequency of metro construction accidents is also increasing year by year. Due to the complex construction process of the metro, once an accident occurs, casualties and property damage are extremely serious. The safety risk factors triggered by different stakeholders were the primary cause of accidents during the metro construction phase. This paper builts a social analysis network of safety risk factors in metro construction from a stakeholder’s perspective. Based on 42 accident cases and related literature, 6 stakeholders and 25 safety risk factors were identified and the relationships between stakeholders and safety risk factors were also determined. Through the application of social network analysis, a social network of safety risk factors in metro construction was constructed, and quantitative analysis was carried out based on density, degree centrality, betweenness centrality, and cohesive subgroup. The results showed that the key safety risk factors in the construction phase of the metro were in action of the contractor’s construction site managers, lack of safety protection at the construction site, insufficient detailed survey and design information provided by the designer, unfavorable government regulation, and bad weather. Moreover, the results of 20 cohesive subgroups illustrated the interrelationship between safety risk factors. S1H2 (“violations by operatives” related to contractor) and S1H4 (“lack of safety precautions” related to contractor) and S5H5 (“ineffective supervision” related to supervisor) both belonged to subgroup G1, which means that there is a high probability that these three safety risk factors would occur simultaneously. This paper provided a basis to improve the level of safety risk management and control from the stakeholder’s perspective.

Can social network analysis assist in the prioritisation of contacts in a tuberculosis contact investigation?

2015 ◽  
Vol 19 (11) ◽  
pp. 1293-1299 ◽  
Author(s):  
L. Kawatsu ◽  
K. Izumi ◽  
K. Uchimura ◽  
M. Urakawa ◽  
A. Ohkado ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Contact Investigation

scholarly journals Risk factors for Clonorchis sinensis infection transmission in humans in northern Vietnam: A descriptive and social network analysis study

2017 ◽  
Vol 66 (2) ◽  
pp. 74-82 ◽  
Author(s):  
Hoang Quang Vinh ◽  
Waraphon Phimpraphai ◽  
Sirikachorn Tangkawattana ◽  
John F. Smith ◽  
Sasithorn Kaewkes ◽  
...  
Keyword(s):  
Risk Factors ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Clonorchis Sinensis ◽  
Infection Transmission ◽  
Analysis Study ◽  
Northern Vietnam

scholarly journals Stakeholder-Associated Risks and Their Interactions in PPP Projects: Social Network Analysis of a Water Purification and Sewage Treatment Project in China

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Mingzhu Yang ◽  
Haitao Chen ◽  
Yongshun Xu
Keyword(s):  
Risk Factors ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Local Governments ◽  
Risk Sharing ◽  
Sewage Treatment ◽  
Project Managers ◽  
Individual Level ◽  
The Individual

As a result of complex contractual relationships, multiple stakeholders with different interests are involved in public-private partnership (PPP) projects. Compared to traditional models, PPP projects have more uncertainty. This study integrated stakeholders and risk factors in PPP projects from a network perspective to better determine how to control risks. Using social network analysis (SNA), a case study was conducted to identify the critical risk factors, and mitigation actions are proposed. The results indicated that, compared to other stakeholders, local governments play the most important role in PPP projects. Managers should therefore pay more attention to political and legal risk factors and develop reasonable risk-sharing plans. This study expands PPP risk research from the individual level to the network level and provides a visualized, innovative research paradigm for PPP risk analysis. The results can also be used by project managers for decision-making, risk management, and other processes, thus helping to achieve the sustainable management of PPP projects.

Network Analysis for Economics and Management Studies

2020 ◽  
pp. 269-328
Author(s):  
Lucio Biggiero
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Formation ◽  
Competitive Equilibrium ◽  
Group Structure ◽  
Network Modeling ◽  
Descriptive Analysis ◽  
Economic Networks ◽  
Main Research

Sociology and other social sciences have employed network analysis earlier than management and organization sciences, and much earlier than economics, which has been the last one to systematically adopt it. Nevertheless, the development of network economics during last 15 years has been massive, alongside three main research streams: strategic formation network modeling, (mostly descriptive) analysis of real economic networks, and optimization methods of economic networks. The main reason why this enthusiastic and rapidly diffused interest of economists came so late is that the most essential network properties, like externalities, endogenous change processes, and nonlinear propagation processes, definitely prevent the possibility to build a general – and indeed even partial – competitive equilibrium theory. For this paradigm has dominated economics in the last century, this incompatibility operated as a hard brake, and presented network analysis as an inappropriate epistemology. Further, being intrinsically (and often, until recent times, also radically) structuralist, social network analysis was also antithetic to radical methodological individualism, which was – and still is – economics dominant methodology. Though culturally and scientifically influenced by economists in some fields, like finance, banking and industry studies, scholars in management and organization sciences were free from “neoclassical economics chains”, and therefore more ready and open to adopt the methodology and epistemology of social network analysis. The main and early field through which its methods were channeled was the sociology of organizations, and in particular group structure and communication, because this is a research area largely overlapped between sociology and management studies. Currently, network analysis is becoming more and more diffused within management and organization sciences. Mostly descriptive until 15 years ago, all the fields of social network analysis have a great opportunity of enriching and developing its methods of investigation through statistical network modeling, which offers the possibility to develop, respectively, network formation and network dynamics models. They are a good compromise between the much more powerful agent-based simulation models and the usually descriptive (or poorly analytical) methods.

scholarly journals Trends in distance education research: A content analysis of journals 2009-2013

2015 ◽  
Vol 16 (1) ◽  
Author(s):  
Aras Bozkurt ◽  
Ela Akgun-Ozbek ◽  
Sibel Yilmazel ◽  
Erdem Erdogdu ◽  
Hasan Ucar ◽  
...  
Keyword(s):  
Distance Education ◽  
Education Research ◽  
Content Analysis ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Descriptive Analysis ◽  
Research Areas ◽  
Current Trends ◽  
E Learning

<p>This study intends to explore the current trends in the field of distance education research during the period of 2009-2013. The trends were identified by an extensive review of seven peer reviewed scholarly journals: <em>The American Journal of Distance Education</em> (AJDE), <em>Distance Education</em> (DE), <em>The European Journal of Open, Distance and e-Learning</em> (EURODL), <em>The Journal of Distance Education</em> (JDE), <em>The Journal of Online Learning and Technology</em> (JOLT), <em>Open Learning: The Journal of Open, Distance and e-Learning</em> (OL) and <em>The International Review of Research in Open and Distributed Learning</em> (IRRODL). A total of 861 research articles was reviewed. Mainly content analysis was employed to be able to analyze the current research. Also, a social network analysis (SNA) was used to interpret the interrelationship between keywords indicated in these articles. Themes were developed and the content of the articles in the selected journals were coded according to categories derived from earlier studies. The results were interpreted using descriptive analysis (frequencies) and social network analysis. The reporting of the results were organized into the following categories: research areas, theoretical and conceptual frameworks, variables, methods, models, strategies, data collection and analysis methods, and the participants. The study also identified the most commonly used keywords, and the most frequently cited authors and studies in distance education. The findings obtained in this study may be useful in the exploration of potential research areas and identification of neglected areas in the field of distance education.  </p>

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