Digital Interventions for Managing Medication and Health Care Service Delivery in West Africa: Systematic Review.

BACKGROUND: As a result of the recent advancements in technology, the incorporation of digital interventions into the health care system has gained a lot of attention and adoption globally. However, these interventions have not been fully adopted, thereby limiting their impact on health care delivery in West Africa. OBJECTIVE: This review primarily aims at evaluating the current digital interventions for medication and health care delivery in West Africa. Its secondary aim is to assess the impacts of digital interventions in managing medication and health care service delivery with the intent of providing vital recommendations that would contribute to an excellent adoption of digital intervention tools in the health care space in West Africa. METHODS: In line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), a comprehensive search through various databases yielded 529 results. After a rigorous screening, 29 articles that provided information on 3 broad digital health intervention tools were found eligible for this review. RESULTS: Out of 29 studies, 16 (55%) studies examined phone-based interventions, 9 (31%) studies focused on tele- and e-based interventions, and 4 (14%) studies evaluated digital interventions. These interventions were used for diverse purposes, some of which are monitoring adverse drug reactions, general health, sexual and reproductive health, and training of health care practitioners. The phone-based intervention appears to be the most known and impactful of all the interventions, followed by tele- and e-based, while digital interventions were scarcely used. CONCLUSIONS: Digital interventions have had a considerable level of impact on medication and health care delivery across West Africa. However, the overall impact is limited. Therefore, strategies must be developed to address the challenges limiting the use of digital intervention tools so that these tools can be fully incorporated into the health care space in West Africa.

Firm-level pollution and membership of emission trading schemes.

Several firms have joined emission trading schemes in response to the call for corporate climate action. Using a comprehensive international data set on corporate membership of emission trading schemes (ETSs), we find that members of the scheme emit more CO2 than non-participants. This result also holds when exploring the corporate discharge of sulphur and volatile organic compounds (VOCs). The magnitude of this relationship persists even in the long run showing little evidence of a reduction from the firms in polluting the environment. We also find that firms that select to exit the scheme continue to pollute at a higher rate in the following years. Firms that enter the scheme for the first time increase their pollution in the following years. Although we identify significant differences at a country and continental level on the effectiveness of ETSs, our results raise some concerns about ETSs' role.

The effects of air transportation, energy, ICT and FDI on economic growth in the industry 4.0 era: Evidence from the United States.

This study analyses the causal and long-run linkage between air transport and economic growth. It was conducted to validate the tourism-led growth hypothesis for the United States (US) during the period 1981-2017 and includes Information and Communication Technologies (ICTs) alongside coal rents in the tourism-led growth hypothesis. This study presents a new direction for future studies by considering the relevance of the fourth industrial revolution (Industry 4.0), particularly in the US. To achieve the stated claim, this study considers as additional explanatory variables how ICTs moderate the impact of Foreign Direct Investment (FDI) on GDP. The empirical result confirms a connection between the Industry 4.0 era and the role of ICTs, which promotes substantial changes in the way of life and productivity. This has led to a vast technological advancement, which is in line with but at a faster pace than the technological advancement of previous revolutions. From empirical results, the study provides relevant policy recommendations related to the role of natural resources, new technologies and tourism on US GDP, while it also provides evidence of the positive effect of ICTs over FDI under the Industry 4.0 era.

Co-Designing Digital Health Intervention for Monitoring Medication and Consultation Among Transgender People in Underserved Communities: Collaborative Approach.

BACKGROUND: In many parts of the world, men who have sex with men and transgender individuals face criminalization and discrimination. As a result, they are less likely to seek medical help, despite experiencing higher rates of HIV/AIDS, mental health issues, and other health problems. Reaching key populations (KPs) with essential testing, care, and treatment services can be challenging, as they often have a higher likelihood of contracting and spreading the virus. They have limited access to antiretroviral (ARV) therapy (ART) services, which means that KPs may continue to serve as reservoirs for new HIV infections if they do not receive effective HIV programming. This ongoing issue complicates efforts to control the epidemic. Therefore, modeling a digital health system to track ARV medication access and use is crucial. This paper advocates for the use of digital interventions to manage the health of KPs in underserved regions, using Nigeria as a case study. OBJECTIVE: This study aims to assess digital health interventions for monitoring medication and consultations among transgender people in underserved communities. It also sought to determine whether a system exists that could support ART adherence in Nigeria. Additionally, the study evaluated design strategies to address privacy and confidentiality concerns, aiming to reduce nonadherence to ARV medications among KPs in Nigeria. METHODS: A qualitative approach was adopted for this research, involving a thematic analysis of information collected from interviews with clinicians and other health practitioners who work directly with these communities, as well as from an interactive (virtual) workshop. RESULTS: The findings from the thematic analysis indicate a need to increase attendance at ART therapy sessions through the implementation of an intensive care web app. Unlike previous solutions, this study highlights the importance of incorporating a reminder feature that integrates with an in-app telemedicine consultancy platform. This platform would facilitate discussions about client challenges, such as adverse drug effects, counseling sessions with clinical psychologists, and the impact of identity discrimination on mental health. Other data-driven health needs identified in the study are unique drug request nodes, client-led viral load calculators, remote requests, and drug delivery features within the web app. Participants also emphasized the importance of monitoring medication compliance and incorporating user feedback mechanisms, such as ratings and encouragement symbols (eg, stars, checkmarks), to motivate adherence. CONCLUSIONS: The study concludes that technology-driven solutions could enhance ART adherence and reduce HIV transmission among transgender people. It also recommends that local governments and international organizations collaborate and invest in health management services that prioritize health needs over identity.

The role of economic policy uncertainty and social welfare in the view of ecological footprint: evidence from the traditional and novel platform in panel ARDL approaches.

In the contemporary world, environmental degradation has become a concern for human beings. Accordingly, the impact of social welfare, economic policy uncertainty, natural resource rents, life expectancy, and trade openness are examined on ecological footprint (the most comprehensive proxy of environmental degradation) in 19 energy-intensive countries from 1997 to 2018. With this in mind, this study used the traditional panel ARDL and CS-ARDL approaches to evaluate how the study's variables influence ecological footprint. Notably, the results of the CS-ARDL approach are more robust due to cross-sectional dependence and slope heterogeneity problems. The outcomes revealed that economic policy uncertainty and trade openness affect the ecological footprint negatively in the short run and positively in the long run. Moreover, social welfare degrades the environment in the long run, and natural resource rents improve environmental quality by mitigating the ecological footprint in the short run and harming the environment in the long run. Besides, life expectancy does not significantly affect ecological footprint in the long or short run. Meanwhile, the results confirmed the bi-directional causal relationship between the study's variable and ecological footprint. Based on the outcomes, the way to adopt effective policies to improve the quality of the environment has been paved. Furthermore, a comprehensive policy framework for stricter environmental regulation is expected to be developed using the outcomes derived from this study.

An empirical assessment of electricity consumption and environmental degradation in the presence of economic complexities.

To a large extent, the theories and concepts behind the effect of ecological footprint have been the paramount concern of the recent literature. Since the rising and falling of environmental degradation have been a continuous issue since the first phase of development, determinants such as economic complexity may play a critical role in achieving long-term sustainable development in the framework of environmental Kuznets curve (EKC) paradigm. Therefore, this research expands on the notion of an EKC paradigm for the world's top ten most complex economies by considering four variables, such as real GDP per capita, electricity consumption, trade openness, and a new putative factor of environmental obstacle, the economic complexity index (ECI). This is one of the first studies to look at the impact of ECI on the ecological footprint of a specific sample from 1998 to 2017. The findings demonstrate a continuous inverted U-shaped link between real GDP per capita, the square of real GDP per capita, and ecological footprint. The EKC hypothesis is found to be valid in the long term in the examined complex economies. The findings of the panel autoregressive distributed lag (ARDL) of the pooled mean group (PMG) and fully modified ordinary least squares (FMOLS) estimations demonstrate that in the long term, electric power usage contributed to the carbon footprints. Furthermore, the economic complexity index and trade openness increase environmental performance over time. To determine if there is causation between the variables, we employ the panel vector error correction model (VECM) framework. Particularly, the results show unidirectional causality running from electric power consumption to ecological footprint and bidirectional causal relationship between (1) economic growth and ecological footprint; (2) square of economic growth and ecological footprint; (3) economic complexity index and ecological footprint; and (4) trade openness and ecological footprint.

Sign and Human Action Detection Using Deep Learning.

Human beings usually rely on communication to express their feeling and ideas and to solve disputes among themselves. A major component required for effective communication is language. Language can occur in different forms, including written symbols, gestures, and vocalizations. It is usually essential for all of the communicating parties to be fully conversant with a common language. However, to date this has not been the case between speech-impaired people who use sign language and people who use spoken languages. A number of different studies have pointed out a significant gaps between these two groups which can limit the ease of communication. Therefore, this study aims to develop an efficient deep learning model that can be used to predict British sign language in an attempt to narrow this communication gap between speech-impaired and non-speech-impaired people in the community. Two models were developed in this research, CNN and LSTM, and their performance was evaluated using a multi-class confusion matrix. The CNN model emerged with the highest performance, attaining training and testing accuracies of 98.8% and 97.4%, respectively. In addition, the model achieved average weighted precession and recall of 97% and 96%, respectively. On the other hand, the LSTM model's performance was quite poor, with the maximum training and testing performance accuracies achieved being 49.4% and 48.7%, respectively. Our research concluded that the CNN model was the best for recognizing and determining British sign language.

The anthropogenic consequences of energy consumption in the presence of uncertainties and complexities: evidence from World Bank income clusters.

In environmental management, many studies have examined the energy consumption-emission nexus in detail. However, for the first time in the literature, this study considers how the Economic Complexity Index (ECI) and economic policy uncertainty (EPU) moderate the contribution of energy consumption to emissions for the four World Bank Income clusters. The system generalised methods of moments are applied to data for 109 countries from 1996 to 2016. Based on the main model (grouped clusters) estimations, the result revealed the existence of the environmental Kuznets curve (EKC) hypothesis. Also, an increase in air transport and consumption of energy releases more carbon emissions to the climate. Interestingly, ECI decreases carbon emission significantly while EPU does not have a significant impact. Moreover, the study revealed that ECI moderated the impact of other variables on emission, but EPU is not a significant moderator. Furthermore, a comparative analysis among the four incomes suggests that the EKC hypothesis holds only in the high-income clusters; ECI is a significant predictor of carbon emission in the four clusters, but it only decreases the emission in high-income clusters. This corroborates the debate on climate change and the productive capacity of high-income countries. Given the foregoing, several policy measures were recommended.

On the nexus between globalization, tourism, economic growth, and biocapacity: evidence from top tourism destinations.

Several studies have investigated the relationship between tourism, consumption of energy, globalization, and ecological footprint. However, the role of biocapacity alongside tourism development in environmental sustainability is yet to be documented in the extant literature. No doubt, the biocapacity of a country, its level of tourist's arrival, as well as globalization all contribute immensely to ecological footprint. Consequently, this study looks at long-run and causality connections with a special focus on bio-capacity. The study uses the pooled mean group-autoregressive distributed lag model (PMG-ARDL) methodology to test the causality relationship during 2016 international tourists' receipt from world tourism organization data files for 10 tourism destinations. Empirical result based on the panel PMG-ARDL confirms the environmental Kuznets curve (EKC) hypothesis for the 10 tourism destinations countries investigated. Furthermore, the panel ARDL estimator was used to estimate the short-run and long-run relationships simultaneously between biocapacity, tourist arrivals, GDP per capita, globalization, and ecological footprints. While the Dumitrescu and Hurlin panel causality test was used to establish causality relationships among the highlighted variables. The trade-off between economic growth and environmental quality suggests that tourist arrival dampens environmental quality. In addition, the study finds that growing biocapacity affects ecological footprints negatively. Furthermore, an increase in tourism-related activities, globalization, and economic production has the potential to damage the quality of the environment. To this end, given the study results, there is a need to pursue green tourism which can reduce environmental degradation and destruction of land caused by multiple tourism-related transportation and construction of tourist facilities respectively in the top ten tourist destination countries.

Designing policy framework for sustainable development in Next-5 largest economies amidst energy consumption and key macroeconomic indicators.

Global travel and tourism have enjoyed a significant boost due to the progress in air transport. However, the debate on air transport and the influx of foreign investments and global energy demand on economic development remains questionable. Therefore, this study is an attempt to contribute to the body of knowledge in the energy-tourism-led growth hypothesis literature. For this purpose, a novel approach to the effects of international tourism on economic growth is introduced for the Next-5 largest economies, namely (China, India, Indonesia, Turkey and the USA) between 1990 and 2018. Empirical results reveal a positive connection between foreign direct investment and income levels, electricity production and income levels, as well as between urbanization and economic growth. Moreover, the validation of the environmental Kuznets curve and the halo effect of foreign direct investment on the environmental degradation process provides a shred of more substantial evidence and fitting environmental instruments for policymakers. The empirical results encourage sustainable economic growth in these countries, mainly through the attraction of clean and high-technology foreign investment, the increase of the share of renewable energy sources in the energy mix and the regulation in the tourism industry. The novel contribution of this study to the empirical literature is the unification in the same research of the TLGH and the EKC for the Next-5 largest economies, establishing recommendations for tourism, energy efficiency and environmental correction process.

Do economic policy uncertainty and geopolitical risk surge CO2 emissions? New insights from panel quantile regression approach.

In recent times, economic policy uncertainty (EPU) and geopolitical risk (GPR) are increasing significantly where the economy and environment are affected by these factors. Therefore, the goal of this paper is to investigate whether EPU and GPR impede CO2 emissions in BRICST countries. We employ second-generation panel data methods, AMG and CCEMG estimator, and panel quantile regression model. The conclusions document that most of the variables are integrated at I (1), and there exists co-integration among considered variables of the study. Moreover, we note that EPU and GPR have a heterogeneous effect on CO2 emissions across different quantiles. EPU adversely affects CO2 emissions at lower and middle quantiles, while it surges the CO2 emissions at higher quantiles. On the contrary, geopolitical risk surges CO2 emissions at lower quartiles, and it plunges CO2 emissions at middle and higher quantiles. Furthermore, GDP per capita, renewable energy, non-renewable energy, and urbanization also have a heterogeneous impact on CO2 emissions in the conditional distribution of CO2 emissions. Based on the results, we discuss the policy direction.

An investigation into the anthropogenic nexus among consumption of energy, tourism, and economic growth: do economic policy uncertainties matter?

Global warming has been a pressing issue for the past decade as various economic activities have been flagged and are expected to reduce emissions. While previous studies have examined the energy consumption-emissions-economic growth nexus in significant detail, attention is yet to be given to the role of economic policy uncertainties and human activities such as tourism in a carbon function. Thus, this study aims to investigate the long-run relationship between energy consumption, tourists' arrivals, economic policy uncertainty, and ecological footprint in the top ten earners from international tourism over the period 1995 to 2015. The fully modified ordinary least square and dynamic ordinary least square estimation techniques and the Dumitrescu and Hurlin causality tests were used in the study. Empirical results suggest that economic policy uncertainties in addition to tourism and energy consumption are drivers of environmental degradation. However, the contribution of energy consumption to ecological footprint is significantly moderated by economic policy uncertainties such that a 1% increase in the latter reduces environmental damage by 0.71%. This study suggests that policy uncertainties matter a great deal for energy and environmental policies. Also, green economic growth is possible if the proper implementation of environmental protection policies can restrict the harmful impact of economic activities on the quality of the environment. Based on the empirical findings, vital energy policy recommendations are suggested.

Determinants of green growth in developed and developing countries.

Considering the need for environmental sustainability while ensuring economic growth and development by 2030, this study uses data on 123 developed and developing countries to examine factors that influence green growth. The empirical results show that economic development positively influences green growth. However, trade openness is detrimental to green growth. Regarding energy-related factors, we find energy consumption negatively affecting green growth, but renewable energy consumption significantly improves green growth. In further analysis, we find that the influence of these factors differs between developed and developing countries. The result implies that countries at a different development level will require different strategies in achieving the Sustainable Development Goals in 2030. The results are robust to alternative identification strategies such as the System Generalised Method of Movement, which accounts for potential endogeneity.

The effect of energy consumption on the environment in the OECD countries: economic policy uncertainty perspectives.

In this paper, we investigate the impact of energy use and economic policy uncertainties on the environment. To achieve this objective, we use the pooled mean group-autoregressive distributed lag methodology (PMG-ARDL) and Dumitrescu and Hurlin causality test on 22 Organisation for Economic Co-operation and Development (OECD) countries between 1985 and 2017. The PMG-ARDL estimation shows that energy use and economic policy uncertainties have a positive relationship with carbon dioxide emission (CO2) emission, while a negative relationship is confirmed between renewable and CO2 emissions in the long run. The short-run estimation shows a positive relationship between energy use, real gross domestic product, and per capita on CO2 emissions. The Dumitrescu and Hurlin causality results highlight a unidirectional running from real GDP and GDP per capita square to CO2 emissions. Furthermore, one-way causality exists between CO2 emissions to economic policy uncertainties. These results have policy implications on the macroeconomy which are discussed in detail in the concluding section.

Toward a sustainable environment: nexus between consumption-based carbon emissions, economic growth, renewable energy and technological innovation in Brazil.

This research investigates the drivers of consumption-based carbon emissions in Brazil by using a dataset covering the period between 1990 and 2018. These dynamics were examined by employing the ARDL bounds, DOLS, and gradual shift causality tests. The ARDL long- and short-run estimation outcomes reveal that: (a) renewable energy use stimulates the sustainability of the environment; (b) economic growth increases environmental degradation; and (c) technological innovation enhances the quality of the environment. In addition, the gradual shift causality test results disclosed that renewable energy consumption, economic growth, technological innovation and public-private partnership investment in energy can predict consumption-based carbon emissions in Brazil. Therefore, Brazilian policymakers should actively encourage the R&D of low-carbon technologies and renewable energy consumption. Domestic consumption levels, on the other hand, should be targeted, specifically those that are more energy-intensive and cause a rise in CO2 emissions due to consumption.

An evaluation of the causal effect between air pollution and renewable electricity production in Sweden: Accounting for the effects of COVID-19.

The COVID-19 pandemic has made a significant disruption in the renewable industry, and the effects will last longer. In this context, understanding how and which specific renewable power got affected due to this crisis is of crucial importance. This study examines the nexus between COVID-19 and Sweden's renewable electricity production from three sources of energy such as nuclear, solar, and wind, where the data ranges from January 1, 2019, to February 17, 2021. Since this study compares the period before and during the pandemic event, the study uses Air Quality Index as a measure of COVID-19 induced event and thus study the linkage between air quality and electricity production from three types of renewable energy. To analyse the above issue, several advanced techniques such as Wavelet Power Spectrum, Wavelet Coherence, Partial and Multiple Wavelet Coherence have been applied. The findings from the Wavelet Coherence approach demonstrate that COVID-19 has disrupted the linkage between wind energy generation and air quality, while the disruption in the case of solar and nuclear electricity generation has been minimal. Moreover, solar energy generation and air pollution both negatively affect each other, implying the need to generate solar power as well as reduce the level of air pollution in Sweden. In light of the above findings, the study discusses possible policy actions the country can take to fulfil its renewable development goals.

The anthropogenic consequences of energy consumption and population expansion in Africa? Do governance factors make any difference?

Sub-Saharan Africa is greatly affected by global warming and is the most affected region in the world. Although several studies in the literature have attempted to identify the causative agents and recommendations to the environmental damages, the gap remains unfilled as the situation is still not any better. This study contributes to the existing body of knowledge through the investigation of the role of governance, energy consumption and population on the environmental quality in Sub-Saharan Africa using data spanning over the period 1998-2014 for 46 countries in the region. For the empirical analysis, the system-generalised method of moments (S-GMM) is employed to analyse the model. Findings from the study reveal that while the total population has a negative but insignificant impact on emissions, the urban population has a positive and statistically significant impact on emissions. The moderation effect of governance is found to overturn the adversities of the urban population on emissions, but this effect is statistically insignificant. The study recommends proper and strategic management of population pressure in urban centres to mitigate its impact on emissions.

Do energy use and economic policy uncertainty affect CO2 emissions in China? Empirical evidence from the dynamic ARDL simulation approach.

Global warming is currently the biggest problem. China is the world's highest CO2 emitter. The Chinese authorities agreed to overcome global pollution per the current Paris treaty and have shown deep concern regarding global warming. Hence, policymakers are paying attention to economic policy uncertainty. Motivated by this issue, the study examines the effect of energy use, economic policy uncertainty, and economic growth on China's CO2 emissions from 1970 to 2018 by employing a novel dynamic ARDL simulation model. The findings show that energy use and economic growth have statistically substantial long-run and short-run positive effects on CO2 emissions. However, economic policy uncertainty has a statistically insignificant effect on CO2 emissions, due to firms' sustainability policies. Energy use can have valuable policy consequences, particularly for environmental sustainability. Therefore, based on the empirical findings, the crucial partnership and feedback on China's carbon emission policy should be carried forward.

A quantile analysis of energy efficiency, green investment, and energy innovation in most industrialized nations.

The continuous use of fossil fuels to meet the energy demands of the industrialized nations has led to environmental degradation. As such, there has been a call for research, exploration, and the usage of alternative energy which is believed to improve the depleting quality of the environment. This study investigates the relationship between energy efficiency, green energy investment, and energy innovation in a panel of nine highly industrialized countries, namely Canada, Japan, France, Spain, Germany, Switzerland, Italy, the USA, and the UK. Relying on the environmental Kuznets' hypothesis (EKC), we employ the quantile-on-quantile regression approach to the data obtained between 1980 and 2018. The empirical estimates validate the EKC hypothesis in most of these industrialized nations considered. The findings also reveal that the continuous use of non-renewable energy consumption escalates emissions, while the use of renewable energy reduces the level of emissions "in" the environment. Therefore, energy efficiency leads to an increase in emissions in the first 3 quantiles and reduces emissions in the remaining quantiles. Also, energy innovation leads to a high amount of emissions. Finally, the study calls for increased investments in renewable energy as well as energy efficiency to ensure continuous improvement in the quality of the environment.

Roadmap for climate alliance economies to vision 2030: retrospect and lessons.

The United Nations Climate Conference 25, held in December 2019, reached a significant agreement against implementing the Paris agreement come 2020. Bound by the contract, 189 countries who are party to the deal agreed to constrain worldwide temperature to ascend to 1.5° Celsius. To this end, the present study attempts to investigate the readiness of selected countries in the European Union to implement the agreement, which will better the quality of the global environment. In line with this, this study appraises the connection between economic growth, renewable and non-renewable energy consumption, on emissions in 11 countries in the European Union from 1990 to 2016. The study utilises the Pooled Mean Group-Auto Regressive Distributed Lag (PMG-ARDL) model estimator and Dumitrescu and Hurlin Panel Causality analysis to analyse the long-run and short-run impact and direction of causality among these factors, respectively. The long-run study's empirical results show a U-shaped Environmental Kuznets Curve (EKC) and a negative connection between renewable energy use and emissions in the EU-11 countries. In the short-run, non-renewable energy use worsens CO2 emissions while renewable energy use leads to a fall in emissions. Similarly, causality tests show a feedback mechanism between emissions and renewable energy use and between non-renewable energy and renewable use. Also, there is unidirectional causality from income to CO2 emissions, non-renewable energy use to CO2 emissions. The investigation recommends an expanded proportion of renewable energy sources in the EU countries' energy mix to cut down on emissions.