Tailoring of neurosurgical practice during COVID-19 in a developing country: Insights gained and a way forward.

Background: The coronavirus disease-19 pandemic has aggravated the already neglected neurosurgical specialty in developing countries with a mounting shortage of specialists, long queues of operative patients, and a lack of adequate critical care units. Methods: We have reviewed the innovative strategies adopted for maintaining an optimal surgical practice while ensuring team safety at the Aga Khan University Hospital, Karachi Pakistan. Results: There is already a scarcity of resources in developing countries. The international guidelines had to be tailored to the context of the developing world. A multimodal strategy that focused on infection control, continuum of care, and the well-being of staff was adopted at Aga Khan University. Patients were screened and seen either in person or through telemedicine, depending on the severity of the disease. All educational activities for residents were shifted online, and this helped in preventing overcrowding. Conclusion: Optimal surgical practice while ensuring team safety can be achieved through a multimodal strategy focusing on infection control, continuum of care, and the well-being of staff.

Prevalence and Factors Associated with Mental Health Problems among Essential and Nonessential Workers during the COVID-19 Pandemic, June 2021, in an Unstable and Developing Country: A Cross-Sectional Study

The two main goals of this research were to assess workers' mental health (anxiety, depression, and job burnout syndrome) and examine factors related to mental health burdens in two groups of workers. The study was conducted as an online cross-sectional study. The target population consists of workers in essential activities who worked during the pandemic (health, defense, trade, finance, and media), as well as a group of workers who were particularly impacted by the protection measures and either worked under a different regime or were unable to work (caterers, musicians). A questionnaire was constructed for the needs of this research and the scales for anxiety, depression, and burnout syndrome were used. In total, 42.2% of non-essential workers and 39.5% of essential workers reported anxiety symptoms, circa 20% of non-essential activity workers and essential activity workers reported depression, and 28.9% of non-essential activity workers and 33.7% of essential activity workers reported burnout. A significant association has been found between certain sociodemographic and health characteristics of respondents, as well as financial stress (worry about losing a job), social stress, media stress, and respondents' trust in competent authorities and COVID-19 prevention measures, and symptoms of anxiety, depression, and burnout syndrome. The findings of this study pointed to mental health issues in other activities and highlighted the need for and importance of examining mental health in the population of non-essential activities. It is indicative of significant points that can be investigated in the future for prevention. © 2023 by the authors.

Public Debt Sustainability in Indonesia after Financial Crisis and During COVID-19 Pandemic

The Developing countries are particularly vulnerable to shocks, such as the global financial crisis and the COVID-19 pandemic. The economic crisis increased external public debt to stabilize the economy and improve people's welfare. High external debt puts the debt in an unsustainable condition. This study aims to measure the debt sustainability of external public debt in Indonesia from 2008-2020. We used the Threshold Value of The Debt Sustainability Framework for Low-Income Countries (LIC-DSF) and the Solvency Rate of External Debt (SRED) as a better combination for measuring debt sustainability in Indonesia. The results showed external public debt was at a low-risk threshold after the global financial crisis. However, the impact of COVID-19 has caused the ratio of external public debt interest payment to tax revenue to be within a high-risk threshold value. The SRED value shows a minus number from 2012-2020 caused by the worsening current account balance and net capital account values. The analysis of debt sustainability may be able to encourage a prudent and sustainable the Indonesian budget management policy. © 2023 WITPress. All rights reserved.

Components of Existing National Surgical Site Infection Surveillance Programs Based on a Case Series of Low- and Middle-Income Countries: Building Blocks for Success and Opportunities for Improvement.

Background: Surgical site infection (SSI) surveillance programs are recommended to be included in national infection prevention and control (IPC) programs, yet few exist in low- or middle-income countries (LMICs). Our goal was to identify components of surveillance in existing programs that could be replicated elsewhere and note opportunities for improvement to build awareness for other countries in the process of developing their own national surgical site infection surveillance (nSSIS) programs. Methods: We administered a survey built upon the U.S. Centers for Disease Control and Prevention's framework for surveillance system evaluation to systematically deconstruct logistical infrastructure of existing nSSIS programs in LMICs. Qualitative analyses of survey responses by thematic elements were used to identify successful surveillance system components and recognize opportunities for improvement. Results: Three respondents representing countries in Europe and Central Asia, sub-Saharan Africa, and South Asia designated as upper middle-income, lower middle-income, and low-income responded. Notable strengths described by respondents included use of local paper documentation, staggered data entry, and limited data entry fields. Opportunities for improvement included outpatient data capture, broader coverage of healthcare centers within a nation, improved audit processes, defining the denominator of number of surgical procedures, and presence of an easily accessible, free SSI surveillance training program for healthcare workers. Conclusions: Outpatient post-surgery surveillance, national coverage of healthcare facilities, and training on how to take local SSI surveillance data and integrate it within a broader nSSIS program at the national level remain areas of opportunities for countries looking to implement a nSSIS program.

Application of machine learning approaches to predict the impact of ambient air pollution on outpatient visits for acute respiratory infections

With a remarkable increase in industrialization among fast-developing countries, air pollution is rising at an alarming rate and has become a public health concern. The study aims to examine the effect of air pollution on patient's hospital visits for respiratory diseases, particularly Acute Respiratory Infections (ARI). Outpatient hospital visits, air pollution and meteorological parameters were collected from March 2018 to October 2021. Eight machine learning algorithms (Random Forest model, K-Nearest Neighbors regression model, Linear regression model, LASSO regression model, Decision Tree Regressor, Support Vector Regression, X.G. Boost and Deep Neural Network with 5-layers) were applied for the analysis of daily air pollutants and outpatient visits for ARI. The evaluation was done by using 5-cross-fold confirmations. The data was randomly divided into test and training data sets at a scale of 1:2, respectively. Results show that among the studied eight machine learning models, the Random Forest model has given the best performance with R2 = 0.606, 0.608 without lag and 1-day lag respectively on ARI patients and R2 = 0.872, 0.871 without lag and 1-day lag respectively on total patients. All eight models did not perform well with the lag effect on the ARI patient dataset but performed better on the total patient dataset. Thus, the study did not find any significant association between ARI patients and ambient air pollution due to the intermittent availability of data during the COVID-19 period. This study gives insight into developing machine learning programs for risk prediction that can be used to predict analytics for several other diseases apart from ARI, such as heart disease and other respiratory diseases. © 2022 Elsevier B.V.

Does economic power or leadership matter? The difference between male and female world leaders in managing pandemics

Factors that are typically associated with better disease prevention and control, such as the health care expenses and the wealth of a nation, are no longer reliable predictors of disease parameters during the Covid-19 pandemic. In fact, we see many developed nations suffering from more widespread infection, a higher mortality rate, and longer pandemic duration. We analyse the performance outcomes of female-led vs. male-led countries in response to the Covid-19 pandemic. We employ regression analysis based on the full sample as well as a propensity score matched sample emphasizing women's roles in society. In general, we provide some evidence that female-led countries exhibit lower numbers of total population-weighted cases and shorter pandemic duration. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

Are government bonds still safe havens in the context of COVID-19?

This study analyzes whether government bonds can act as safe havens in the context of COVID-19. Using a panel fixed effect model, data were collected for both advanced and emerging market economies from March 11, 2020, to June 30, 2021. Robustness tests were used to add to the credibility of the findings. Our evidence supports that government bonds maintained their safe haven status during the COVID-19 pandemic. Hence, investors can still use government bonds to hedge financial market risks in the uncertain environment associated with this pandemic. Additionally, the negative effects of the COVID-19 pandemic on government bond yields in emerging economies are larger than in advanced economies. Therefore, policymakers' measures should focus on reducing COVID-19 cases to alleviate panic and diminish economic fluctuations, especially for emerging economies. Regulators can also use short-term interest rates to guide market capital flow to avoid a liquidity crisis, reducing financial stress and market uncertainty. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

Remittances, Household Welfare, and the COVID-19 Pandemic in Tajikistan

Remittance inflows are now the largest source of external financing to developing countries, but little research has yet firmly established the effect of remittances on household welfare. We investigate the case of Tajikistan, one of the most heavily remittance-dependent countries in the world. We use a panel dataset collected nationwide and employ an instrumental variable estimation to confirm a positive relationship between receiving remittances and household welfare after correcting for endogeneity. Moreover, we find that the effect of remittances on household spending is more pronounced in households whose head is male, older, and/or less educated. Then, we combine our estimated coefficients with the projected decline of remittance inflows as a result of the coronavirus disease (COVID-19) outbreak and show the pandemic's adverse effect on household spending per capita. © 2022 Asian Development Bank.

Transition Modelling of Land Use Land Cover Dynamics in Bardez Taluka of Goa-India (1991-2021)

In the age of global climate change, land use and land cover mapping help us to understand the vital modifications taking place in our environment. LULC mapping assumes great significance in planning, management of resources and keeping track of various programmes at different levels. The data acquired from the land use and land cover investigations are vital for policy formulation and sustainable development of our towns, cities and villages and also to track the disorganized growth of urban areas. Tourism is a tool for economic development in many developing countries of the world. The unplanned tourism growth has led to many ecological problems. This study makes an earnest effort to examine the LULC change using the transition model in the Bardez taluka, which is a well-known global tourist destination in Goa, India. The study has been investigated by using satellite imageries and GIS technologies have been used to analyse the changes occurring in LULC patterns for the years 1991, 2001 and 2021. The result indicates that the area under the built-up class has increased substantially by 11.12 sq. km. as a result of the rise in commercialization, tourism growth and tourism-related activities. Bardez taluka is known for some of the most breath-taking beaches in the world. During 2019-20, just before Covid-19, about 25, 33,234 domestic and 2, 74,840 foreign tourists visited the enchanting beaches of Bardez taluka. Land use classes such as residential, commercial and services, industrial, transportation and utilities also witnessed the growth in their land use and land cover classes whereas classes like agricultural land, coconut plantation, cashew plantation, barren land, DM and FDM forest land, open scrub and fairly dense scrub witnessed a negative change in their class values. © 2023, World Research Association. All rights reserved.

'SciComPt 2022': stop, listen and act - reflect on the past to build the future

During the Covid-19 pandemic the world faced enormous challenges demanding immediate responses. As a result, public communication of science assumed unprecedented prominence. Now, we need to stop, listen and act. This was the motto of the 10th Annual Congress of Science Communication in Portugal ??? SciComPt 2022. The meeting provided participants with exactly that ??? an opportunity to reflect on the past and help build the future of science communication in Portugal.

Increasingly polarised or finding common ground? Exploring pro and anti-vaccine rhetoric on two South African Facebook pages

We investigated pro and anti-vaccine rhetoric on two South African Facebook pages to identify the nature, sources and justifications of the vaccine-related claims published on these pages. Our dataset consisted of 440 Facebook posts made by page administrators during 2019. Statements related to the safety and necessity of vaccines dominated the pro-vaccine page, while the anti-vaccine page focussed primarily on claims about the dangers of vaccines. Posts on both pages frequently contained content shared from within Facebook, with much of the content originating from the United States. Both pages made equal use of scientific justifications (i.e. published journal articles) to support claims, and most of these articles were published in accredited journals. The authors hope that a better understanding of the nature, sources and justifications of pro and anti-vaccine rhetoric may lead to more constructive dialogue about vaccines, including the ongoing debate about COVID-19 vaccines © The Author(s). This article is licensed under the terms of the Creative Commons Attribution — NonCommercial — NoDerivativeWorks 4.0 License

African fictions to boost the scientific culture in Africa.

We popularize scientific topics through the 26-episode film series Science in the City, which depicts the perception of science in Africa. We campaign in African schools, universities and public events to initiate debates on science, inviting actors and scientists to engage with audiences.

The Main Trends and Challenges in the Development of the Different Industries during the COVID-19 Pandemic

The purpose of the research in this article is to investigate the main trends in the development of the different industries during the COVID-19 pandemic, to identify the main problems facing the different industries in the context of the global crisis, as well as to form the basic concepts necessary for a real recovery of the global industry. The authors identify the main problems facing the aviation industry in the developing world crisis and possible ways to solve them. As a working hypothesis, it is proposed to form the basic concepts necessary for preparing and implementing operational measures to restore passenger and cargo aviation. Considering the main threats facing the aviation industry during COVID-19, the article proposes the organizational and economic mechanisms to restore the industry. Furthermore, several recovery scenarios are considered, considering the relevant factors that have a particular impact. Next, a novel mathematical model for pharmaceutical products, which are the most important in COVID-19 pandemics, is proposed. Moreover, the model considers the uncertainty, and a robust optimization approach is applied. The study is based on a comprehensive analysis of documentary data provided by government agencies in several European countries. An analysis of global and Russian passenger traffic for Q1-Q4 (quartile) of 2020 and a development forecast for Q1-Q2 of 2021 is provided. The scenario problems facing the aviation industry in the context of the COVID-19 crisis are identified. There are key concepts necessary to prepare and implement effective measures to restore the aviation industry. © 2022 Alexey I. Tikhonov et al., published by Sciendo.