Fit for purpose? The patents regime, the Fourth Industrial Revolution, and sustainable development

This article uses data from several publicly available databases to show that the distribution of intellectual property for frontier technologies, including those useful for sustainable development, is very highly skewed in favor of a handful of developed countries. The intellectual property rights (IPR) regime as it exists does not optimize the global flow of technology and know-how for the attainment of the sustainable development goals and is in need of updating. Some features of the Fourth Industrial Revolution imply that the current system of patents is even more in need of reform than before. COVID-19 vaccines and therapies and the vast inequality in access to these has highlighted the costs of inaction. We recommend several policy changes for the international IPR regime. Broadly, these fall into three categories: allowing greater flexibility for developing countries, reassessing the appropriateness of patents for technologies that may be considered public goods, and closing loopholes that allow for unreasonable intellectual property protections.

Exploring outliers in global economic dataset having the impact of COVID-19 pandemic

Outlier is a value that lies outside most of the other values in a dataset. Outlier exploration has a huge importance in almost all the industry applications like medical diagnosis, credit card fraudulence and intrusion detection systems. Similarly, in economic domain, it can be applied to analyse many unexpected events to harvest new knowledge like sudden crash of stock market, mismatch between country's per capita incomes and overall development, abrupt change in unemployment rate and steep falling of bank interest. These situations can arise due to several reasons, out of which the present COVID-19 pandemic is a leading one. This motivates the present researchers to identify a few such vulnerable areas in the economic sphere and ferret out the most affected countries for each of them. Two well-known machine-learning techniques DBSCAN and Z-score are utilised to get these insights, which can serve as a guideline towards improving the overall scenario subsequently. Copyright © 2023 Inderscience Enterprises Ltd.

The Consequences of COVID-19 Disruption on Sustainable Economy in the Top 30 High-Tech Innovative Countries.

This study aims to investigate the effects of the COVID-19 pandemic on the innovation index, Gross Domestic Product (GDP), high technology exports, and human development (HDI) in the world's leading 30 high-tech innovative countries. Using grey relational analysis models, the association between COVID-19 and other economic development indices was investigated. The model selects the country least affected by the pandemic from the top 30 innovative countries through a conservative (maximin) method based on grey association values. Data was collected from World Bank databases and analyzed to compare pre- and post-COVID-19 periods (2019, 2020). The outcomes of this study provide essential recommendations for industries and decision-makers with suitable action plans to preserve economic systems from further harm caused by the global COVID-19 outbreak. The ultimate goal is to boost the innovation index, GDP, high-tech exports, and HDI of high-tech economies and pave the way for a sustainable economy. To the author's knowledge, this is the first study to develop a multidimensional framework to assess COVID-19's impact on the sustainable economy of top 30 high-tech innovative countries, and to conduct a comparative analysis to identify the strong and weak effects of COVID-19 on sustainable economic growth.

Roles and Impact of ASHA Workers in Combating COVID-19: Case Study Bhubaneswar

The present COVID attack has significantly accentuated vulnerability of infections at community level where their basic healthcare and immunization program are being implemented by the ICDS scheme launched in 1975 through a slew of AWCs scattered all over the country. The AWC acts as a primary health center that provides supplementary nutrition to children (between 0 and 6 years of age) and pregnant and lactating mothers besides providing preschool education to children in the age group of 4–6 years. The ASHA workers associated with AWC under then NRHM are the first hand health workers available to them at the community level who act as a bridge between the dispensaries and the community members. With the outbreak of COVID-19, the role of ASHA workers has assumed increased salience as the governments are relying on them for community level combating of this outbreak. This paper takes a close look at fund allocations to the public healthcare sector among the developing and developed countries and also the interstate allocations and allocations for major schemes and the resultant impact on HDI. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

COVID-19 and Water Variables: Review and Scientometric Analysis.

COVID-19 has changed the world since 2020, and the field of water specifically, boosting scientific productivity (in terms of published articles). This paper focuses on the influence of COVID-19 on scientific productivity with respect to four water variables: (i) wastewater, (ii) renewable water resources, (iii) freshwater withdrawal, and (iv) access to improved and safe drinking water. The field's literature was firstly reviewed, and then the maps were built, emphasizing the strong connections between COVID-19 and water-related variables. A total of 94 countries with publications that assess COVID-19 vs. water were considered and evaluated for how they clustered. The final step of the research shows that, on average, scientific productivity on the water topic was mostly conducted in countries with lower COVID-19 infection rates but higher development levels as represented by gross domestic product (GDP) per capita and the human development index (HDI). According to the statistical analysis, the water-related variables are highly significant, with positive coefficients. This validates that countries with higher water-related values conducted more research on the relationship with COVID-19. Wastewater and freshwater withdrawal had the highest impact on the scientific productivity with respect to COVID-19. Access to safe drinking water becomes insignificant in the presence of the development parameters.

Effect of Population Density and Economic Indicators on COVID-19 Death Rates in the Community of Latin American and Caribbean States.

OBJECTIVE: The countries of the Community of Latin American and Caribbean States (CELAC, by its initials in Spanish) have been some of the most affected by COVID-19. This paper analyzes whether, in the 33 CELAC countries, population density, together with other economic variables, such as gross domestic product (GDP) at purchasing power parity (PPP) values or the Human Development Index (HDI), were significantly associated with the coronavirus mortality rate. METHODS: A correlation analysis and an ordinary least squares regression model were used to analyze the effects of different variables on the COVID-19 mortality rate. RESULTS: The results showed that countries with higher numbers of inhabitants per square kilometer had lower death rates. Gross domestic product was not associated with the number of deaths, while the HDI had a positive impact on that number. CONCLUSION: Countries with high population density are not more vulnerable to COVID-19, as population density allows for economic development and better-designed institutions.

Influence of Population Size, the Human Development Index and the Gross Domestic Product on Mortality by COVID-19 in the Southeast Region of Brazil.

We evaluated the influence of population size (POP), HDI (Human Development Index) and GDP (gross domestic product) on the COVID-19 pandemic in the Southeast region of Brazil, between February 2020 and May 2021. METHODS: Cases, deaths, incidence coefficient, mortality rate and lethality rate were compared among states. The cities were divided into strata according to POP, GDP, and HDI. Data were compared by Welch's ANOVA, nonlinear polynomial regression, and Spearman's correlation test (rS). RESULTS: The highest incidence coefficient (p < 0.0001) and mortality rate (p < 0.05) were observed in the states of Espírito Santo and Rio de Janeiro, respectively. Until the 45th week, the higher the POP, the higher the mortality rate (p < 0.01), with no differences in the remaining period (p > 0.05). There was a strong positive correlation between POP size and the number of cases (rS = 0.92, p < 0.0001) and deaths (rS = 0.88, p < 0.0001). The incidence coefficient and mortality rate were lower (p < 0.0001) for low GDP cities. Both coefficients were higher in high- and very high HDI cities (p < 0.0001). The lethality rate was higher in the state of Rio de Janeiro (p < 0.0001), in large cities (p < 0.0001), in cities with medium GDP (p < 0.0001), and in those with high HDI (p < 0.05). CONCLUSIONS: Both incidence and mortality were affected by time, with minimal influence of POP, GDP and HDI.

Influencing Factors and Clustering Characteristics of COVID-19: A Global Analysis

The unprecedented coronavirus disease 2019 (COVID-19) pandemic is still raging (in year 2021) in many countries worldwide. Various response strategies to study the characteristics and distributions of the virus in various regions of the world have been developed to assist in the prevention and control of this epidemic. Descriptive statistics and regression analysis on COVID-19 data from different countries were conducted in this study to compare and evaluate various regression models. Results showed that the extreme random forest regression (ERFR) model had the best performance, and factors such as population density, ozone, median age, life expectancy, and Human Development Index (HDI) were relatively influential on the spread and diffusion of COVID-19 in the ERFR model. In addition, the epidemic clustering characteristics were analyzed through the spectral clustering algorithm. The visualization results of spectral clustering showed that the geographical distribution of global COVID-19 pandemic spread formation was highly clustered, and its clustering characteristics and influencing factors also exhibited some consistency in distribution. This study aims to deepen the understanding of the international community regarding the global COVID-19 pandemic to develop measures for countries worldwide to mitigate potential large-scale outbreaks and improve the ability to respond to such public health emergencies. © 2018 Tsinghua University Press.

Machine Learning Techniques to Analyze Pandemic-Induced Economic Outliers

Outliers, or outlying observations, are values in data, which appear unusual. It is quite essential to analyze various unexpected events or anomalies in economic domain like sudden crash of stock market, mismatch between country’s per capita incomes and overall development, abrupt change in unemployment rate and steep falling of bank interest to find the insights for the benefit of humankind. These situations can arise due to several reasons, out of which pandemic is a major one. The present COVID-19 pandemic also disrupted the global economy largely as various countries faced various types of difficulties. This motivates the present researchers to identify a few such difficult areas in economic domain, arises due to the pandemic situation and identify the countries, which are affected most under each bucket. Two well-known machine-learning techniques DBSCAN (density based clustering approach) and Z-score (statistical technique) are utilized in this analysis. The results can be used as suggestive measures to the administrative bodies, which show the effectiveness of the study. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

The association between the initial outcomes of COVID-19 and the human development index: An ecological study

BACKGROUND & OBJECTIVE: Outcomes of the pandemic COVID-19 varied from one country to another. We aimed to describe the association between the global recovery and mortality rates of COVID-19 cases in different countries and the Human Development Index (HDI) as a socioeconomic indicator. METHODS: A correlational (ecological) study design is used. The analysis used data from 173 countries. Poisson regression models were applied to study the relationship between HDI and pandemic recovery and mortality rates, adjusting for country median age and country male to female sex ratio. RESULTS: During the first three months, the global pooled recovery rate was 32.4% (95% CI 32.3% - 32.5%), and the pooled mortality rate was 6.95% (95% CI 6.94% - 6.99%). Regression models revealed that HDI was positively associated with recovery beta = 1.37, p = 0.016. HDI was also positively associated with the mortality outcome beta = 1.79, p = 0.016. CONCLUSIONS: Our findings imply that the positive association between the HDI and recovery rates is reflective of the pandemics' preparedness. The positive association between the HDI and mortality rates points to vulnerabilities in approaches to tackle health crises. It is critical to better understand the connection between nations' socioeconomic factors and their readiness for future pandemics in order to strengthen public health policies.

Understanding Community Mobility through Life Satisfaction, Human Development, and ICT Development: A Data Mining Approach

Prior studies have investigated community mobility to understand the spread of Covid-19 cases, especially during the early months. The goal of this study was to explain community mobility through social measures. Three composite measures, namely the social life satisfaction index, human development index, and ICT development index, were selected as social-related measures to explain community mobility. The data mining approach was adopted using the Knime Analytical Platform as the software and the Cross-Industry Standard Process for Data Mining as a process framework. The analysis covered the mobility fluctuation among 34 provinces in Indonesia using the data from Google Mobility Report from July 2020 to August 2021. Cluster analysis with the k-medoids algorithm grouped provinces into higher and lower mobility provinces. The findings indicated an association between mobility fluctuation among provinces and the social life satisfaction index, human development index, and ICT development index. Four provinces, namely Bali, Yogyakarta, Jakarta, and Riau Islands, had higher mobility, human development index, and ICT development index. The study provides evidence of factors explaining human mobility and thus enriches the literature on human mobility and the social impact of the Covid-19 pandemic. The finding also enhances the literature on applying data mining to social research at a country level. However, the generalization of this finding is limited as the analysis covers Indonesian data only. This study could be extended to other countries to arrive at more generalizable results across countries. © 2021 IEEE.

How do digital capabilities affect firm performance? The mediating role of technological capabilities in the “new normal”

This study proposes a model to explain the effect of digital capabilities on firm performance in the “new normal” context from a firm-level perspective. Moreover, it analyzes the mediating role of technological capabilities and the Human Development Index (HDI) in explaining firm performance. Our study used data from the World Bank's Enterprise Surveys 2020, which included 999 firms from 27 countries. We applied the methodological approach, partial least square structural equation modeling (PLS-SEM), to test the hypothetical model. The results show that digital capabilities positively influence firm performance only through technological capabilities. We also empirically demonstrate that digital skills in low HDI economies have a more significant indirect effect on firm performance than in high HDI countries. Finally, some promising avenues for future research and implications for managers and policymakers are suggested based on these findings.

The COVID-19 vaccination acceptance/hesitancy rate and its determinants among healthcare workers of 91 Countries: A multicenter cross-sectional study.

The aim of this study was to investigate the COVID-19 vaccination acceptance rate and its determinants among healthcare workers in a multicenter study. This was a cross-sectional multi-center survey conducted from February 5 to April 29, 2021. The questionnaire consisted of 26 items in 6 subscales. The English version of the questionnaire was translated into seven languages and distributed through Google Forms using snowball sampling; a colleague in each country was responsible for the forward and backward translation, and also the distribution of the questionnaire. A forward stepwise logistic regression was utilized to explore the variables and questionnaire factors tied to the intention to COVID-19 vaccination. 4630 participants from 91 countries completed the questionnaire. According to the United Nations Development Program 2020, 43.6 % of participants were from low Human Development Index (HDI) regions, 48.3 % high and very high, and 8.1 % from medium. The overall vaccination hesitancy rate was 37 %. Three out of six factors of the questionnaire were significantly related to intention to the vaccination. While 'Perceived benefits of the COVID-19 vaccination' (OR: 3.82, p-value<0.001) and 'Prosocial norms' (OR: 5.18, p-value<0.001) were associated with vaccination acceptance, 'The vaccine safety/cost concerns' with OR: 3.52, p-value<0.001 was tied to vaccination hesitancy. Medical doctors and pharmacists were more willing to take the vaccine in comparison to others. Importantly, HDI with OR: 12.28, 95 % CI: 6.10-24.72 was a strong positive determinant of COVID-19 vaccination acceptance. This study highlighted the vaccination hesitancy rate of 37 % in our sample among HCWs. Increasing awareness regarding vaccination benefits, confronting the misinformation, and strengthening the prosocial norms would be the primary domains for maximizing the vaccination coverage. The study also showed that the HDI is strongly associated with the vaccination acceptance/hesitancy, in a way that those living in low HDI contexts are more hesitant to receive the vaccine.

The Change of Socio-Economic Correlation due to COVID-19 Pandemic in Indonesia

The COVID-19 pandemic has been going on for over one year until today. The government of Indonesia has issued various policies to break the chain of transmission of COVID-19, including the imposition of Large-Scale Social Restrictions and the Enforcement of Restrictions on Micro-scale Community Activities. However, in socio-economics dimension, especially on Economic Growth Rate (EGR), Human Development Index (HDI) and Poverty Percentage (PP), this pandemic has changed how they interact each other. This study presents anomaly correlation regarding those three socio-economics dimensions. The data for analysis was taken from Statistics Indonesia that consists of monthly report data in socio-economics fluctuation during two years period (2019-2020). For year 2019, the results of the Bivariate correlation test showed that the increasing of the Economic Growth Rate (EGR) would increase the Human Development Index (HDI) and decrease the Poverty Percentage (PP) in Indonesia. This correlation did not happen in 2020, because when the Economic Growth Rate (EGR) was increased, the Human Development Index (HDI) level was decreased and Poverty Percentage (PP) was increased. The 2020 result behaviour showed an opposite condition compared to normal correlation term. Some analysis has been discussed on the paper regarding this anomaly condition. The worst impact due to the COVID-19 pandemic in this analysis were shown in Bali-Nusa Tenggara region, where the Economic Growth Rate (EGR), Human Development Index (HDI) and Poverty Percentage (PP) values are below the national value. © 2021 IEEE.

Influence of the Human Development Index on the Maternal-Perinatal Morbidity and Mortality of Pregnant Women with SARS-CoV-2 Infection: Importance for Personalized Medical Care.

Coronavirus disease-19 (COVID-19) is perhaps the most worrisome pandemic in the 21st century, having entailed devastating consequences for the whole society during the last year. Different studies have displayed an existing association between pregnancy and COVID-19 severity due to the various physiological changes that occur during gestation. Recent data identified maternal country of origin as an important determinant of COVID-19 presentation in pregnant women. However, the explanation of this fact remains to be fully elucidated. Therefore, the purpose of this work is to analyze the possible relationship between Human Development Index (HDI) of maternal country of origin with the morbimortality of pregnant women and their newborns. Here, we conducted a multicentric, ambispective, observational case-control study (1:1 ratio) and compare with the HDI of each country (group 1-very high HDI, group 2-high HDI, group 3-medium HDI, and group 4-low HDI). In total, 1347 pregnant women with confirmed SARV-CoV-2 infection (cases) were enrolled, and each was paired with one control to give a total number of 2694 participants from 81 tertiary care centers. Among the women with SARS-CoV-2 infection, more cases were produced of perinatal mortality, overall maternal morbidity, COVID-19 maternal morbidity, C-sections, hypertensive maternal morbidity, and perinatal morbidity. Our results described an inverse association between HDI and maternofetal morbidity and mortality. Moreover, the countries with an HDI lower than 1 showed higher rates of patients with maternal COVID-19-related morbidity (6.0% vs. 2.4%, p < 0.001), a need for oxygen therapy (4.7% vs. 1.8%, p < 0.001), and maternal ICU admission (2.6% vs. 1.0%, p = 0.007). Compared to other risk factors such as overweight, obesity, preexisting and obstetric comorbidities, HDI emerged as an independent risk factor explaining much of the increased maternal-perinatal morbidity and mortality detected in our group of cases. Further research is needed to establish to confirm the real impact of this factor and its components on pregnancy outcomes.

Majority world successes and European and American failure to contain COVID-19: Cultural collectivism and global leadership.

United Nations and World Health Organization data show a positive correlation, r = .53, p < .0001, N = 189, between COVID-19 infection rates and the human development index (HDI). Less wealthy, less educated countries with lower life spans were also more successful in maintaining lower fatality rates, r = .46, p < .0001, N = 189 whereas 9 of the top-10 countries in the world in per capita fatalities due to COVID-19 were Western societies high in HDI. Similar positive correlations were found between COVID-19 infection and fatality rates and a smaller sample of 76 countries measured on Schwartz intellectual autonomy (or individualism), and negative correlations of similar magnitude were found for embeddedness (or collectivism). East Asia was a global leader in preventing the spread of COVID-19 because of a vigilant public concerned for public safety and compliant with public safety measures. African Union leaders coordinated their responses, and bought into a continent-wide African Medical Supplies Platform that prevented panicked competition for scare supplies. Western global media and scholars have not paid attention to the successes of East Asia, Africa, and the South Pacific in fighting the pandemic. It is worth asking why this should be the case; understand the weaknesses of extreme individualism in fighting a pandemic requiring coordinated and unified public response, and consider the lessons for global scholars from the pandemic for doing research in the future.

Are child and youth population at lower risk of COVID-19 fatalities? Evidences from South-East Asian and European countries.

BACKGROUND: The coronavirus disease (COVID-19) pandemic has revealed many lacunas of public health preparedness, especially in lower and middle-income countries and fatality differentials between European and South-East Asian countries. The case fatality rate (CFR) in most of the South-East Asian countries is much lower than the European countries. The percentages of child and youth population are more in South-East countries. OBJECTIVE: The study aims to show the impacts of age composition on fatality differentials in European and South-East Asian countries by age-structure, especially the percentage share of child and youth population. DATA AND METHODS: This study has been done based on data provided by UNDP, WHO and worldometers. The case fatality rate (CFR) has been calculated to find out the mortality differentials of countries, and the higher fatality risk countries have been identified by the composite Z score technique. RESULTS: It is revealed that the COVID-19 case fatality rates are substantially high in highly developed countries of the European countries compared to the South-East Asian countries. Our study shows that there is an issue of child and youth population which affects the lower CFR in SE Asian countries. In France, the CFR was 16.72% which was nearly 7 times more than India (2.31%). The COVID-19 fatality risk ratio was highest in Germany (0.77) while the lowest risk ratio was observed in Bangladesh (-0.71). CONCLUSION: Despite of having a very high level of human development and preparedness, the current pandemic COVID-19 has revealed that there exist significant differentials among fatality status of European and South-East Asian countries. The CFR is lower in the SE Asian countries where the child and youth population are more than the older population.