scholarly journals Impact of Stratified Interventions in University Reopenings

2021 ◽  
Author(s):  
Yiwei Zhang ◽  
Zhuoting Yu ◽  
Akane Fujimoto ◽  
Pinar Keskinocak ◽  
Julie L Swann
Keyword(s):  
Infectious Disease ◽  
Diagnostic Testing ◽  
Group Living ◽  
Governance Structure ◽  
Colleges And Universities ◽  
Disease Spread ◽  
State Universities ◽  
Large State ◽  
Hybrid Classes ◽  
The U.S

More than 4,000 colleges and universities in the U.S. are scheduled to start a new semester in August or September, 2021. Many colleges require Covid-19 vaccination, as well as some combination of face coverings or diagnostic testing, while others do not (in some cases due to governance structure). Large state universities may especially have limitations and are not requiring vaccination, testing, or indoor face coverings, nor offering hybrid classes (to promote physical distancing). Group living quarters or classrooms with densely packed students are among the riskiest settings for infectious disease spread.

CORPORATE GOVERNANCE IN THE 19TH CENTURY: EVIDENCE FROM THE CHESAPEAKE AND OHIO CANAL COMPANY

2009 ◽  
Vol 36 (2) ◽  
pp. 113-137 ◽  
Author(s):  
Robert W. Russ ◽  
Gary John Previts ◽  
Edward N. Coffman
Keyword(s):  
Corporate Governance ◽  
19Th Century ◽  
Annual Report ◽  
Governance Structure ◽  
Review Committee ◽  
Corporate Governance Structure ◽  
Theoretical Structure ◽  
The 19Th Century ◽  
The U.S

Presenting evidence from a 19th century corporation, the Chesapeake and Ohio Canal Company (C&O), the paper shows that issues of corporate governance have existed since the first corporations were established in the U.S. The C&O used a stockholder review committee to review the annual report of the president and directors. The paper shows how the C&O stockholders used this committee to supplement the corporate governance structure. The corporate governance structure of the C&O is also viewed from a theoretical structure as espoused by Hart [1995].

scholarly journals A comparative study of COVID-19 responses in South Korea and Japan: political nexus triad and policy responses

2021 ◽  
pp. 002085232199755
Author(s):  
M. Jae Moon ◽  
Kohei Suzuki ◽  
Tae In Park ◽  
Kentaro Sakuwa
Keyword(s):  
Northeast Asia ◽  
Governance Structure ◽  
Disease Spread ◽  
Policy Outcomes ◽  
Governance Structures ◽  
Government Officials ◽  
Policy Responses ◽  
Government Capacity ◽  
Institutional Contexts ◽  
Policy Problems

Korea and Japan, neighboring democratic countries in Northeast Asia, announced their first COVID-19 cases in January 2020 and witnessed similar patterns of disease spread but adopted different policy approaches to address the pandemic (agile and proactive approach versus cautious and restraint-based approach). Applying the political nexus triad model, this study analyzes and compares institutional contexts and governance structures of Korea and Japan, then examines the differences in policy responses of the two Asian countries. This study first reviews the state of COVID-19 and examines changes in the conventional president-led political nexus triad in Korea and the bureaucracy-led political nexus triad in Japan. Then, this study examines how the differences in institutional contexts and governance structures shaped policy responses and policy outcomes of the two countries in managing the COVID-19 crisis. Points for practitioners •  Institutional and governance structure in a society are likely to affect policymaking processes as well as selection of policies among various policy alternatives. •  Government officials often need to refer to government capacity as well as citizens’ voluntary participation in resolving wicked policy problems like COVID-19. •  Policy decisions made by government officials affect policy outcomes while political environment and political leadership are equally important to policy effectiveness.

scholarly journals How Does a COVID mRNA vaccine really work?

Ubiquity ◽  
2021 ◽  
Vol 2021 (July) ◽  
pp. 1-12
Author(s):  
Walter Tichy
Keyword(s):  
Infectious Disease ◽  
Immune System ◽  
Messenger Rna ◽  
Spike Protein ◽  
Foreign Protein ◽  
The Real ◽  
Virus Rna ◽  
German Company ◽  
The Media ◽  
The U.S

The most potent weapon against COVID-19 is a vaccine based on messenger RNA (mRNA). The first of these vaccines authorized for use was developed by the German company BioNTech in cooperation with Pfizer, closely followed by the (U.S.-produced) Moderna vaccine. These vaccines send a piece of mRNA into cells of a host. The mRNA instructs the cells to produce masses of the same spike protein that also occurs on the shell of the real coronavirus. The immune system responds by learning to destroy anything showing that protein: if the real virus arrives, the immune system will attack it immediately. This much has been reported widely by the media. But important questions remain. How is mRNA actually synthesized as a transcription of the spike-producing segment of the virus' RNA? How is the selection and replication done? How does mRNA enter a host cell, and how long will it stay there? Will it produce the spike protein forever? Is it perhaps dangerous? And the biggest question of all: How does the immune system record the structure of the foreign protein, how does it recognize the invader, and how is the immune response cranked up? To answer these questions, we bring you a conversation between Ubiquity editor Walter Tichy and his daughter Dr. Evelyn Tichy, an infectious disease expert.

scholarly journals Persuasion Tactics in the Implementation of Large-Scale EHR Suites in Public Healthcare

2021 ◽  
Author(s):  
Gunnar Ellingsen ◽  
Bente Christensen ◽  
Morten Hertzum
Keyword(s):  
Large Scale ◽  
Healthcare Services ◽  
Governance Structure ◽  
Public Healthcare ◽  
Technical Literature ◽  
Health Authorities ◽  
To Come ◽  
Regional Health Authorities ◽  
Entrepreneurial Role ◽  
The U.S

Large-scale electronic health record (EHR) suites have the potential to cover a broad range of use needs across various healthcare domains. However, a challenge that must be solved is the distributed governance structure of public healthcare: Regional health authorities regulate hospitals, municipalities are responsible for first-line healthcare services, and general practitioners (GPs) have an independent entrepreneurial role. In such settings, EHR program owners cannot enforce municipalities and GPs to come on board. Thus, we examine what tactics owners of large-scale EHR suite programs apply to persuade municipalities to participate, how strongly these tactics are enforced, and the consequences. Empirically, we focus on the Health Platform program in Central Norway where the goal is to implement the U.S. Epic EHR suite in 2022. Theoretically, the paper is positioned in the socio-technical literature.

scholarly journals Successive Approximation, Variational Iteration, and Multistage-Analytical Methods for a SEIR Model of Infectious Disease Involving Vaccination Strategy

2021 ◽  
Vol 3 (2) ◽  
pp. 114-126
Author(s):  
Sudi Mungkasi
Keyword(s):  
Infectious Disease ◽  
Successive Approximation ◽  
Time Domain ◽  
Analytical Method ◽  
Vaccination Strategy ◽  
Approximate Solutions ◽  
Disease Spread ◽  
Seir Model ◽  
Variational Iteration ◽  
Iteration Methods

We consider a SEIR model for the spread (transmission) of an infectious disease. The model has played an important role due to world pandemic disease spread cases. Our contributions in this paper are three folds. Our first contribution is to provide successive approximation and variational iteration methods to obtain analytical approximate solutions to the SEIR model. Our second contribution is to prove that for solving the SEIR model, the variational iteration and successive approximation methods are identical when we have some particular values of Lagrange multipliers in the variational iteration formulation. Third, we propose a new multistage-analytical method for solving the SEIR model. Computational experiments show that the successive approximation and variational iteration methods are accurate for small size of time domain. In contrast, our proposed multistage-analytical method is successful to solve the SEIR model very accurately for large size of time domain. Furthermore, the order of accuracy of the multistage-analytical method can be made higher simply by taking more number of successive iterations in the multistage evolution.

Employing Agent-based Modeling to Mitigate Infectious Disease Spread

2021 ◽  
Vol 65 (1) ◽  
pp. 390-394
Author(s):  
Michael Schwartz ◽  
Paul Oppold ◽  
Boniface Noyongoyo ◽  
Peter Hancock
Keyword(s):  
Infectious Disease ◽  
Viral Infections ◽  
Agent Based Modeling ◽  
Disease Spread ◽  
Effective Measure ◽  
Agent Based ◽  
Personal Learning ◽  
Business Operations ◽  
Interpersonal Factors ◽  
Reduce Risk

The current pandemic has tested systems in place as to how to fight infectious diseases in many countries. COVID-19 spreads quickly and is deadly. However, it can be controlled through different measures such as physical distancing. The current project examines through simulation model of the UCF Global building the potential spread of an infectious disease via AnyLogic Personal Learning Edition (PLE) 8.7.0 on a laptop running Windows 10. The goal is to determine the environmental and interpersonal factors that could be modified to reduce risk of illness while maintaining typical business operations. Multiple experiments were ran to see when there is a potential change in infection and spread rate. Results show that increases occur with density between 400 and 500. To curtail the spread it is therefore important to limit contact through physical distancing for it has been proven an effective measure for reducing the spread of viral infections.

Tracking self-reported symptoms and medical conditions on social media during the COVID-19 pandemic (Preprint)

2021 ◽  
Author(s):  
Qinglan Ding ◽  
Daisy Massey ◽  
Chenxi Huang ◽  
Connor Grady ◽  
Yuan Lu ◽  
...  
Keyword(s):  
Mental Health ◽  
Infectious Disease ◽  
Social Media ◽  
Positive Predictive Value ◽  
Medical Condition ◽  
Medical Conditions ◽  
Health Related ◽  
The U.S ◽  
Over Time

BACKGROUND Harnessing health-related data posted on social media in real-time has the potential to offer insights into how the pandemic impacts the mental health and general well-being of individuals and populations over time. OBJECTIVE The aim of this study was to obtain information on symptoms and medical conditions self-reported by non-Twitter social media users during the coronavirus disease 2019 (COVID-19) pandemic, and to determine how discussion of these symptoms and medical conditions on social media changed over time. METHODS We used natural language processing (NLP) algorithms to identify symptom and medical condition topics being discussed on social media between June 14 and December 13, 2020. The sample social media posts were geotagged by NetBase, a third-party data provider. We calculated the positive predictive value and sensitivity to validate the classification of the posts. We also assessed the frequency of different health-related discussions on social media over time during the study period, and compared the changes in the frequency of each symptom/medical condition discussion to the fluctuation of U.S. daily new COVID-19 cases during the study period. Additionally, we compared the trends of the 5 most commonly mentioned symptoms and medical conditions from June 14 to August 31 (when the U.S. passed 6 million COVID-19 cases) to the trends observed from September 1 to December 13, 2020. RESULTS Within a total of 9,807,813 posts (nearly 70% were sourced from the U.S.), we identified discussion of 120 symptom topics and 1,542 medical condition topics. Our classification of the health-related posts had a positive predictive value of over 80% and an average classification rate of 92% sensitivity. The 5 most commonly mentioned symptoms on social media during the study period were: anxiety (in 201,303 posts or 12.2% of the total posts mentioning symptoms), generalized pain (189,673, 11.5%), weight loss (95,793, 5.8%), fatigue (91,252, 5.5%), and coughing (86,235, 5.2%). The 5 most discussed medical conditions were: COVID-19 (in 5,420,276 posts or 66.4% of the total posts mentioning medical conditions), unspecified infectious disease (469,356, 5.8%), influenza (270,166, 3.3%), unspecified disorders of the central nervous system (253,407, 3.1%), and depression (151,752, 1.9%). The changes in the frequency of 2 medical conditions, COVID-19 and unspecified infectious disease, were similar to the fluctuation of daily new confirmed cases of COVID-19 in the U.S. CONCLUSIONS COVID-19 and symptoms of anxiety were the two most commonly discussed health-related topics on social media from June 14 to December 13, 2020. Real-time monitoring of social media posts on symptoms and medical conditions may help assess the population's mental health status and enhance public health surveillance for infectious disease.

Sign in / Sign up

Export Citation Format

Share Document