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This paper aims to assess the economic impact of uniform COVID-controlling policies that were implemented by the US government in 2020 and compare it with hypothetical targeted policies that consider the heterogenous effect of COVID-19 on different age groups.

The author began by showing that the adjusted SEQIHR model is a good fit to the US COVID-induced daily death data in that it can capture the nonlinearities of the data very well. Then, he used this model with extra parameters to evaluate the economic effects of COVID-19 through its impact on the job market.

The results show that targeted COVID-controlling policies could reduce the US death rate and GDP loss to 0.03% and 2%, respectively. By comparing these results with uniform COVID-controlling policies, which led to a 0.1% death rate and 3.5% GDP loss, we could conclude that the death rate reduction is 0.07%. Approximately 378,000 Americans died because of COVID-19 during 2020, therefore, reducing the death rate to 0.03% means saving a significant proportion of the COVID-19 casualties, around 280,000 lives.

To the best of the author's knowledge, this paper is the first study to assess the economic impacts of COVID-controlling policies by using the multirisk SEQIHR model.

This study aims to analyze the pattern of deaths in detention in Northern Tunisia as well as the causes of death.

The authors conducted a cross-sectional retrospective study including all the casualties of death in detention examined in the legal medicine Department in the main teaching hospital from 2005 to 2019. The department covers 10 out of the 11 governorates of Northern Tunisia and 13 prisons.

Of a total of 197 casualties, only 2 were females. The mean age was 45.39 ± 14.43 years. A known medical history was reported in 63.5%, mainly cardiovascular disease, mental health disorders and diabetes. Half of the deaths occurred at the hospital. A total of 53 victims spent less than one year in custody before their death. Most deaths occurred due to disease-related causes (78.7%; n = 155); among these, 69 victims died from cardiovascular disease. Suicide accounted for 3.6% of the casualties and homicides for four cases.

Several missing data regarding the details of the detention circumstances as well as the absence in some cases of the toxicological and histopathology analysis results, which could bias the study findings.

Death in detention in Northern Tunisia involved mainly males between their 30s and their 50s who died mainly from cardiovascular or pulmonary disease. These results underscore the importance of empowering the penitentiary health system.

To the best of the authors’ knowledge, this study is one of largest studies with regard to the number of decedents and the number of prisons from the Arab countries allowing to draw a pattern of casualties of death in prison.

The COVID-19 pandemic has recently had an impact on the stock market all over the globe. A thorough review of the literature that included the most cited articles and articles from well-known databases revealed that earlier research in the field had not specifically addressed how the BRIC stock markets responded to the COVID-19 pandemic. The data regarding COVID-19 were collected from the World Health Organization (WHO) website, and the stock market data were collected from Yahoo Finance and the respective country’s stock exchange. A random forest regression algorithm takes the closing price of respective stock indices as target variables and COVID-19 variables as input variables. Using this algorithm, a model is fit to the data and is visualised using line plots. This study’s findings highlight a relationship between the COVID-19 variables and stock market indices. In addition, the stock market of BRIC countries showed a high correlation, especially with the Shanghai Composite Stock Index with a correlation value of 0.7 and above. Brazil took the worst hit in the studied duration by declining approximately 45.99%, followed by India by 37.76%. Finally, the data set’s model fit, which employed the random forest machine learning method, produced R² values of 0.972, 0.005, 0.997, and 0.983 and mean percentage errors of 1.4, 0.8, 0.9, and 0.8 for Brazil, Russia, India, and China (BRIC), respectively. Even now, two years after the coronavirus pandemic started, the Brazilian stock index has not yet returned to its pre-pandemic level.

This chapter aims to study the impact of the COVID-19 pandemic on the inequality in countries, define it as a new conflict for sustainable development, and determine the prospects of conflict management. This chapter is based on the Theory of Conflicts and such methods as analysis of variations, trend and regression analysis, and simplex method. It is found that the variation of the COVID-19 case rate in the developed (by the example of G7) and developing (by the example of BRICS) countries was very high (140.99%). The variation of the COVID-19 death rate is lower, but it remains rather high (63.29%). The economic growth rate for the whole sample of countries under the influence of the COVID-19 pandemic reduced by 404.16% in 2021, while the quality of life reduced by 1.86% on average. The COVID-19 pandemic increased the inequality in countries, thus creating a new conflict of sustainable development. The perspectives of conflict management of sustainable development are connected to the improvement of the practice of using digital technologies, which helps to reduce the inequality in countries. By the example of the COVID-19 pandemic in 2020, the offered recommendations would have allowed reducing the decline of economic growth rate by 95.01% and preventing the decline in quality of life.

Suicide prevention and intervention in prisons is a challenge. Prisons were not designed to be clinical facilities, yet with the growing numbers of people who face mental health challenges in prisons, staff require knowledge and skills to adequately address mental health crises, especially suicide. This study aims to: describe trends in suicide attempts and completions within one state’s prison system and measure staff knowledge and preparedness to address suicide.

This research uses a nonexperimental research design and two data sources. Administrative data from 2000 to 2017 on serious suicide attempts and completions were analyzed, and all correctional staff employed in the state’s Department of Corrections were surveyed at one point in time. Univariate and bivariate analyses were conducted.

The number of serious suicide attempts trended up but completed suicides decreased. Correctional staff demonstrated high suicide knowledge of risk factors and warning signs of suicide. Staff who viewed a media-based suicide training displayed significantly more knowledge of suicide and perceived greater preparedness compared to staff who did not or did not recall viewing the training.

Corrections staff play a key role in preventing suicides in prison. Innovative intervention is needed to increase suicide awareness, improve communication and enhance prevention skills.

South Africa is in the last stage of the first demographic transition (FDT) – yet already depicts aspects of the second transition. The last stage of the FDT is characterized by lower levels of fertility closer to or at the replacement level of the average of 2.1 children per woman, and improvements in mortality displayed by declining infant and childhood mortality leading to increasing life expectancy at birth. The second demographic transition (SDT) is driven by lifestyle changes that are determinants of demographic patterns. Such lifestyle changes are declining marriage rates, increasing attention on human development, and thus changing family formation patterns. South Africa’s youth are at the centre of this transition. The population census of 2011 shows an age structure of South Africa that is characterized by a larger proportion of 20-35-year-olds. This resulted from a long period of declining fertility and to some extent improvements in mortality at all ages. This age structure, with adequate investments - is expected to yield a period of economic growth resulting from a reduced dependency ratio. However, improved health care, investments in human development, and higher employment opportunities are required to harness the benefit. This chapter aims to explore the national and provincial preparedness of South African youth to contribute to economic growth of the country. In particular, the chapter will focus on demographic factors such as sex ratio; youth mortality and morbidity; and youth fertility levels as these factors are highly correlated with human development.

This study aims to examine the multiscale predictability power of COVID-19 deaths and confirmed cases on the S&P 500 index (USA), CAC30 index (France), BSE index (India), two strategic commodity futures (West Texas intermediate [WTI] crude oil and Gold) and five main uncertainty indices Equity Market Volatility Ticker (EMV), CBOE Volatility Index (VIX), US Economic Policy Uncertainty (EPU), CBOE Crude Oil Volatility Index (OVX) and CBOE ETF Gold Volatility Index (GVZ). Furthermore, the authors analyze the impact of uncertainty indices and COVID-19 deaths and confirmed cases on the price returns of stocks (S&P500, CAC300 and BSE), crude oil and gold.

The authors used the wavelet coherency method and quantile regression approach to achieve the objectives.

The results show strong multiscale comovements between the variables under investigation. Lead-lag relationships vary across frequencies. Finally, COVID-19 news is a powerful predictor of the uncertainty indices at intermediate (4–16 days) and low (32–64 days) frequencies for EPU and at low frequency for EMV, VIX, OVX and GVZ indices from January to April 2020. The S&P500, CAC30 and BSE indexes and gold prices comove with COVID-19 news at low frequencies during the sample period. By contrast, COVID-19 news and WTI oil moderately correlated at low frequencies. Finally, the returns on equity and commodity assets are influenced by uncertainty indices and are sensitive to market conditions.

This study contributes to the literature by exploring the time and frequency dependence between COVID-19 news (confirmed and death cases) on the returns of financial and commodity markets and uncertainty indexes. The findings can assist market participants and policymakers in considering the predictability of future prices and uncertainty over time and across frequencies when setting up regulations that aim to enhance market efficiency.

The COVID-19 pandemic has posed many challenges in almost all sectors around the globe. Because of the pandemic, government entities responsible for managing health-care resources face challenges in managing and distributing their limited and valuable health resources. In addition, severe outbreaks may occur in a small or large geographical area. Therefore, county-level preparation is crucial for officials and organizations who manage such disease outbreaks. However, most COVID-19-related research projects have focused on either state- or country-level. Only a few studies have considered county-level preparations, such as identifying high-risk counties of a particular state to fight against the COVID-19 pandemic. Therefore, the purpose of this research is to prioritize counties in a state based on their COVID-19-related risks to manage the COVID outbreak effectively.

In this research, the authors use a systematic hybrid approach that uses a clustering technique to group counties that share similar COVID conditions and use a multi-criteria decision-making approach – the analytic hierarchy process – to rank clusters with respect to the severity of the pandemic. The clustering was performed using two methods, k-means and fuzzy c-means, but only one of them was used at a time during the experiment.

The results of this study indicate that the proposed approach can effectively identify and rank the most vulnerable counties in a particular state. Hence, state health resources managing entities can identify counties in desperate need of more attention before they allocate their resources and better prepare those counties before another surge.

To the best of the authors’ knowledge, this study is the first to use both an unsupervised learning approach and the analytic hierarchy process to identify and rank state counties in accordance with the severity of COVID-19.

This chapter provides a comprehensive exploration of global demographic trends and challenges, specifically focusing on Asian countries and the demographic landscape of Bangladesh. This chapter highlights the implications of rapid population growth, aging populations, and urbanization, analyzing their socioeconomic impacts on education, healthcare, and employment. By contextualizing these trends within the broader framework of sustainable development, this chapter sets the stage for understanding the intricate relationship between population dynamics and the empowerment of marginalized communities through family planning strategies.

The paper sets out to understand the key issues that the various functions and optimal allocation of NGOs (non-governmental organizations) in the circular economy that provide public services depend not only on external quantities or densities but also on their internal size of human resources.

The paper uses different data samples and models to study the influence mechanism of optimal NGO size of human resources and its differentiated effects on governance quality of entrepreneurship.

The authors find that a reduction in transaction costs and an increase in the aggregation degree of public demand lead to increased human capital and lower financial capital intensity. In addition, the authors find that NGO size of human resources has a relationship that is approximately U-shaped (or inverse U-shaped) with the governance quality of entrepreneurship.

The paper discusses the implications for programs that encourage NGOs to optimally determine their internal size of human resources and further improve the governance quality of entrepreneurship in the circular economy.

The paper reveals the significant nonmonotonic relationship between local governance quality and NGO financial size, even after controlling for other NGO, city and provincial characteristics.