Internationalization of Science and Diplomacy, Concepts and Practices: Lessons for Developing Countries

The current rapid progress of science and technology has been made possible through the extensive and increasing practice of international scientific collaboration in its multiple forms. Acknowledging the latter's importance, most countries make it part of their internationalization policies. With development demands to further science capacities, and global problems becoming more complex, the science–foreign policy nexus has deepened in its conceptual and practical approaches, giving rise to the evolving concept and prominence of science diplomacy. Though science has been "used for years for international relations purposes around the world, science diplomacy has become a new term for an old concept”, today it is a key tool to promote closer relations between nations, define common global goals, and as support to the internationalization of science and foreign policies. With the COVID-19 crisis, science diplomacy has gained renewed importance and calls for new approaches like the further development of "science of science diplomacy” or the inclusion of new policy support tools such as foresight. Developing countries formulating their science and foreign policies can benefit from an overview of internationalization, scientific collaboration, the existing science diplomacy concepts and practices, and the development of new approaches contributing to a better understanding of the science–foreign policy nexus. © 2023, The Centre for Science and Technology of the Non-Aligned and Other Developing Countries.

Healthcare-associated infections: a threat to the survival of patients with COVID-19 in intensive care units.

BACKGROUND: Wide variation in mortality rates among critically ill patients with coronavirus disease 2019 (COVID-19) has been reported. This study evaluated whether healthcare-associated infections (HAI) are a risk factor for death among patients with severe COVID-19 in the intensive care unit (ICU). METHODS: This retrospective cohort study included patients with severe COVID-19 hospitalized in the ICU of four hospitals in the city of Curitiba, Brazil. Patients with COVID-19 who died during ICU hospitalization were compared with those who were discharged. A second analysis compared patients who developed HAI in the ICU with those who did not. Multiple logistic regression models were used to control for confounders. RESULTS: In total, 400 patients were included, and 123 (31%) patients developed HAI. The most common HAI was lower respiratory tract infection (67%). Independent risk factors for death were: age [odds ratio (OR) 1.75, 95% confidence interval (CI) 1.43-2.15; P<0.0001]; clinical severity score (OR 2.21, 95% CI 1.70-2.87; P<0.0001); renal replacement therapy (OR 12.8, 95% CI 5.78-28.6; P<0.0001); and HAI (OR 5.9, 95% CI 3.31-10.5; P<0.0001). A longer interval between symptom onset and hospital admission was protective against death (OR 0.93, 95% CI 0.88-0.98; P=0.017). The only independent factors associated with HAI were high C-reactive protein and low PaO2/FiO2 ratio. CONCLUSIONS: No factors that could point to a high-risk group for HAI acquisition were identified. However, age, dialysis and HAI increased the risk of death in ICU patients with severe COVID-19; of these, HAI is the only preventable risk factor.

Managing the COVID-19 pandemic in a Portuguese School of Nursing: an experience report

Introduction: The COVID-19 pandemic, decreed by the WHO in March 2020, created enormous challenges. Our Institution was faced with the need to take measures to control the spread of the disease and keep the academic community safe, for which a comprehensive contingency plan was created so that the entire community felt involved and able to follow the proposed measures. Objectives: (I) Describe the process of building a contingency plan to respond to the COVID-19 pandemic situation in a Nursing School;(II) Describe the implementation of the contingency plan and its adequacy, depending on the evolution of the pandemic situation and (III) Describe the main challenges encountered and the corrective strategies adopted. Methodology: Experience report of the construction and implementation of the Institution's contingency plan. A Contingency Plan Team was appointed that created a plan following the guidelines of the various health regulatory authorities, structured in four topics: 1) organization of structures;2) training;3) organization of academic and work activities;4) follow-up and monitoring. In addition, several guiding documents for safe practices were also prepared, aimed at readjusting the teaching-learning process and the safety of employees. Results: 1) organization of structures: An isolation room was established in each building, Spaces were reorganized to ensure safe distances;antiseptics were distributed;Signals was adopted to make the path;internal dynamics and specific procedures changed. 2) training: Clarification sessions were organized with teachers and online training for students and non-teaching staff, and face-to-face training for cleaning staff and support teams. 3) organization of academic and work activities: plan the beginning and breaks according to the maximum amount of people in the same room, fixed the capacity of each classroom. 4) follow-up and monitoring: a case notification/registration process was created and spread the message for all community on the website and by email. Conclusions: The contingency plan has responded to the Institution's needs. It was dynamic and flexible, always be adjusted according to national norms/guidelines and in partnership with Local Health Authorities. The implemented changes proved to be effective and supported the entire school community, which started to integrate the new rules into their daily lives. The very low cases report of covid-19 with the beginning in our institution, seems to reveal the success of the implemented measures.

Machine learning applied in SARS-CoV-2 COVID 19 screening using clinical analysis parameters

COVID-19 was considered a pandemic by the World Health Organization. Since then, world governments have coordinated information flows and issued guidelines to contain the overwhelming effects of this disease. At the same time, the scientific community is continually seeking information about transmission mechanisms, the clinical spectrum of the disease, new diagnoses, and strategies for prevention and treatment. One of the challenges is performing the tests for the diagnosis of the disease, whose technique adopted for the detection of the genetic material of COVID-19 requires equipment and specialized human resources, making it an expensive procedure. We hypothesize that machine learning techniques can be used to classify the test results for COVID-19 through the joint analysis of popular laboratory tests' clinical parameters. Machine learning techniques, such as Random Forest, Multi-Layer Perceptron, and Support Vector Machines Regression, enable the creation of disease prediction models and artificial intelligence techniques to analyze clinical parameters. Thus, we evaluated the existing correlations between laboratory parameters and the result of the COVID-19 test, and developed two classification models: the first classifies the test results for patients with suspected COVID-19, and the second classifies the hospitalization units of patients with COVID-19, both according to the laboratory parameters. The models achieved an accuracy above 96%, showing that they are promising to the classification of tests for COVID-19 and screen patients by hospitalization unit.

The Role of Telehealth in the Covid-19 Pandemic: A Brazilian Experience

SARS-CoV-2, the virus that causes Covid-19, is the third coronavirus to cause severe disease in humans and to spread globally in the past two decades. In this context, several national public health departments, including the Brazilian Ministry of Health, highlighted what was, until then, considered a support service to the health system: telehealth and telemedicine. We intend to present the actions carried out by a national telehealth service in Brazil, both as a Primary Health Care (PHC) support service to professionals and to patients, as well as discussing the potential to reorganize a health system. This is a prevalence study that summarizes the measures adopted by Brazilian Telehealth Center from the 9th to the 27th epidemiological weeks of 2020 to support the health services of the Brazilian Unified Health System (SUS). There was an increase of 76.8% in the demand for telephone teleconsultations during the evaluated period compared to the same period in 2019, with 28.8% of the entire demand arising from doubts related to Covid-19. The Covid-19 pandemic demanded a quick response, with the organization of materials about the disease, a new team to carry out telemonitoring and teleconsultation activities, in addition to the creation of a manual for teleconsultations in Primary Health Care.