Search results

The dual epidemic of non-communicable diseases (NCDs) and human immuno-deficiency virus (HIV) in Sub-Saharan Africa has increased substantially in recent years, with cardiovascular disease representing a significant contributor to the regional burden of disease. Very little is known about the cardiovascular health of people deprived of their liberty in the region. The purpose of this study was to collate extant literature on the topic.

A scoping review mapped and described what is known about cardiovascular disease in prison populations in Sub-Saharan Africa. A systematic search of empirical literature with no date limitation was conducted in English. Sixteen studies representing six Sub-Saharan African countries (Cameroon, Nigeria, Guinea, Burkina Faso, Ghana and Ethiopia) were charted, categorised and thematically analysed.

Seven key themes were identified: custodial deaths and autopsy; cardiorespiratory fitness and exercise; cardiovascular disease and elderly people in prison; cardiovascular disease and women in prison; dietary deficiencies; influence of sleep patterns on cardiovascular disease; and other associated risk factors. Most natural deaths at autopsy of custodial deaths were due to cardiovascular disease. Cardiorespiratory fitness was low in prisons, and poor sleep patterns and dietary deficiencies are likely contributors to the burden of cardiovascular disease in prisons. The needs of elderly and female prison populations are ill-considered.

To the best of the authors’ knowledge, this is the first known attempt to scope extant literature on cardiovascular disease in Sub-Saharan African prisons. A strategic focus on the cardiovascular health of people in prison is warranted. Routine monitoring and expansion of existing prison health-care services and integration of NCD services with infectious disease (HIV and tuberculosis) programmes in prisons are required.

Contextual to the recognition of the complex interplay between health and behavioral aspects, integrated behavioral health (IBH) has emerged. Although this model is becoming popular in the Western world, its presence in the global context is not promising. This paper aims to explore the need for IBH in India and address its barriers to implementation and possible solutions.

We analyzed the case of IBH and its potential implications for India using the current evidence base, authors' reflections and experience of implementing similar programs.

This paper identifies contextual factors, including increased instances of non-communicable diseases and psychosocial and cultural determinants of health, that necessitate the implementation of IBH programs in India. The key features of different IBH models and their applicability are outlined. The current status of IBH and potential challenges in implementation in India in terms of human resources and other factors are delineated. We also discuss the potential models for implementing IBH in India.

Integrating behavioral health in primary care is considered an effective and sustainable model to promote health and well-being across various target populations. Towards this end, this paper is the first to discuss the contextual factors of IBH in India. It is a significant addition to the knowledge base on IBH and its possible implementation barriers and strategies in low- and middle-income countries.

The study aims to develop a multilayer high-effective ensemble of ensembles predictive model (stacking ensemble) using several hyperparameter optimized ensemble machine learning (ML) methods (bagging and boosting ensembles) trained with high-volume data points retrieved from Internet of Things (IoT) emission sensors, time-corresponding meteorology and traffic data.

For a start, the study experimented big data hypothesis theory by developing sample ensemble predictive models on different data sample sizes and compared their results. Second, it developed a standalone model and several bagging and boosting ensemble models and compared their results. Finally, it used the best performing bagging and boosting predictive models as input estimators to develop a novel multilayer high-effective stacking ensemble predictive model.

Results proved data size to be one of the main determinants to ensemble ML predictive power. Second, it proved that, as compared to using a single algorithm, the cumulative result from ensemble ML algorithms is usually always better in terms of predicted accuracy. Finally, it proved stacking ensemble to be a better model for predicting PM_2.5 concentration level than bagging and boosting ensemble models.

A limitation of this study is the trade-off between performance of this novel model and the computational time required to train it. Whether this gap can be closed remains an open research question. As a result, future research should attempt to close this gap. Also, future studies can integrate this novel model to a personal air quality messaging system to inform public of pollution levels and improve public access to air quality forecast.

The outcome of this study will aid the public to proactively identify highly polluted areas thus potentially reducing pollution-associated/ triggered COVID-19 (and other lung diseases) deaths/ complications/ transmission by encouraging avoidance behavior and support informed decision to lock down by government bodies when integrated into an air pollution monitoring system

This study fills a gap in literature by providing a justification for selecting appropriate ensemble ML algorithms for PM_2.5 concentration level predictive modeling. Second, it contributes to the big data hypothesis theory, which suggests that data size is one of the most important factors of ML predictive capability. Third, it supports the premise that when using ensemble ML algorithms, the cumulative output is usually always better in terms of predicted accuracy than using a single algorithm. Finally developing a novel multilayer high-performant hyperparameter optimized ensemble of ensembles predictive model that can accurately predict PM_2.5 concentration levels with improved model interpretability and enhanced generalizability, as well as the provision of a novel databank of historic pollution data from IoT emission sensors that can be purchased for research, consultancy and policymaking.

Increased outsourcing and importation of drugs from different parts of the world to the Latin America and the Caribbean (LAC) region result in the proliferation of substandard and fake medicines, posing a threat to public health. The presence of substandard and fake medications in LAC regions is a source of public health concern and causes an economic burden to the governments in these regions. Whereas testing and detecting medication quality can easily be achieved in developed countries, the situation is different in developing countries such as LAC. This paper aims to examine the public health challenges faced by LAC regarding substandard, fake and counterfeit medicines and how the region can tackle these challenges.

Databases such as Scopus, PubMed, ScienceDirect, Embase, HINARI, EBSCOhost, Google Scholar, unpublished data, conference abstracts and papers from World Health Organization, Pan-American Health Organization and electronic newspapers were searched concerning medicine quality and in LAC.

Drug treatment improves the quality of life while decreasing morbidity and mortality among diseased populations. Absence of or inadequate testing laboratories, old and ineffective legislature, lack of enforcement or willpower and lack of effective surveillance are challenges in LAC for the proliferation of substandard and falsified medicines (SFMs).

The most significant limitation of this study was the need for the reviewers to have used articles written in other languages besides English. The LAC region has a large population in non-English-speaking countries, and many articles are written using local languages. Hence, excluding those articles is a limitation worthy of note in this review. The articles accessed needed to provide adequate information on SFM markets and illegal pharmacies or hospitals but did not. Future reviews may focus on providing illegal substandard and falsified medicines markets in the region and how they can be minimized or eliminated.

This review highlights the challenges faced by LAC countries regarding substandard, fake and counterfeit medicines. The sources, prevalence and consequences of substandard and falsified drugs were identified to suggest the measures needed to curb the infiltration of low-quality medicines in LAC.

This systematic review examined the emerging threat of indoor and outdoor pollutants to public health in Latin America and the Caribbean (LAC).

Pollutants and pollution levels are becoming an increasing cause for concern within the LAC region, primarily because of the rapid increase in urbanization and the use of fossil fuels. The rise in indoor and outdoor air pollutants impacts public health, and there are limited regional studies on the impact of these pollutants and how they affect public health. A comprehensive literature search was conducted using Google Scholar, PubMed, Scopus, EBSCOhost, Web of Science and ScienceDirect databases. Significant search terms included “indoor air pollution,” “outdoor air pollution,” “pollution,” “Latin America,” “Central America,” “South America” and “Caribbean was used.” The systematic review utilized the Rayyan systematic software for uploading and sorting study references.

Database searches produced 1,674 results, of which, after using the inclusion–exclusion criteria and assessing for bias, 16 studies were included and used for the systematic review. These studies covered both indoor and outdoor pollution. Various indoor and outdoor air pollutants linked to low birth weight, asthma, cancer and DNA impairment were reported in this review. Even though only some intervention programs are available within the region to mitigate the harmful effects of pollution, these programs need to be robust and appropriately implemented, causing possible threats to public health. Significant gaps in the research were identified, especially in the Caribbean.

Limitations of the study include limited available research done within LAC, with most of the research quantifying pollutants rather than addressing their impacts. Additionally, most studies focus on air pollution but neglect water and land pollution’s effects on public health. For this reason, the 16 studies included limited robustness of the review.

Although available studies quantifying pollution threats in LAC were identified in this review, research on the adverse impacts of pollution, especially concerning public health, is limited. LAC countries should explore making cities more energy-efficient, compact and green while improving the transportation sector by utilizing clean power generation. In order to properly lessen the effects of pollution on public health, more research needs to be done and implemented programs that are working need to be strengthened and expanded.

Background: This study aimed to appraise the monetary value of human life losses associated with COVID-19 in Turkey. To our knowledge, it is the first study in Turkey to value human life losses associated with COVID-19.

Methods: A human capital approach (HCA) model was applied to estimate the total monetary value of the 4,807 human lives lost in Turkey (TMVHL) from COVID-19 by 15 June 2020. The TMVHL equals the sum of monetary values of human lives lost (MVHL) across nine age groups. The MVHL accruing to each age group is the sum of the product of discount factor, years of life lost, net GDP per capita, and the number of COVID-19 deaths in an age group. The HCA model was re-calculated five times assuming discount rates of 3%, 5%, and 10% with a national life expectancy of 78.45 years; and the world highest life expectancy of 87.1 years and global life expectancy of 72 years with 3% discount rate.

Results: The 4807 human life losses from COVID-19 had a TMVHL of Int$1,098,469,122; and a mean of Int$228,514 per human life. Reanalysis with 5% and 10% discount rates, holding national life expectancy constant, reduced the TMVHL by Int$167,248,319 (15.2%) and Int$ 429,887,379 (39%), respectively. Application of the global life expectancy reduced the TMVHL by 36.4%, and use of world highest life expectancy increased TMVHL by 69%. However, the HCA captures only the economic production losses incurred as a result of years of life lost. It ignores non-market contributions to social welfare and the adverse effects of economic activities.

Conclusions: Additional investment is needed to bridge the persisting gaps in international health regulations capacities, universal health coverage, and safely managed water and sanitation services.

Due to their limited capacity for adaptation and dependence on natural resources for economic growth, developing countries (DCs) tend to be more prone to climate change. It is argued that climate finance (CF) is a significant financial innovation to mitigate the negative effects of climate variation. However, the heterogeneous impacts of CF on environmental sustainability (ES) and social welfare (SW) have been masked. Thus, this study aims to investigate the heterogeneous effects of CF on ES and SW in 80 CF receipt DCs from 2002 to 2018. This study also aims to investigate the effects of CF on ES and SW based on population size, income heterogeneity and the type of CF.

The method of moments quantile regression (MMQR) with fixed effects is utilized. Alternatively, the fully modified least square (FMOLS) and dynamic least square (DOLS) estimators are used for the robustness test.

The findings revealed that DCs with the lowest and middle quantiles of EF, carbon dioxide (CO₂) emissions and human development exhibit large beneficial impacts of CF on ES and SW. In contrast, the positive effects of CF on ES breakdown for countries with the largest distributions of EF and CO₂ emissions. Besides, the impacts of CF on ES and SW depend on income heterogeneity, population size and the type of CF.

This study calls for a framework to integrate CF into all economic development decisions to strengthen climate-resilient SW and ES in DCs.

To the best of the authors’ knowledge, this is the first study to investigate the effects of CF on ES and SW in a wide range of DCs. Thus, it complements existing related literature focusing on the effects of CF on ES and SW.

This study aims to demonstrate the evaluation of an incentive scheme to encourage pregnant people to set a quit-smoking date.

The paper outlines a collaborative approach, working with pregnant people, clinicians, tobacco dependency practitioners and academics to gain insights into their perspectives and experiences. Quantitative and qualitative data were analysed.

The incentive scheme and appropriate support from clinicians have been shown to encourage pregnant people to set a quit date. The tobacco dependency practitioners helped remove barriers, such as the perception of the stigmatisation of smoking when pregnant. The practitioners also helped pregnant people make informed decisions to support successful behaviour change. The impact of the scheme resulted in improved infant health indicators. The scheme’s evaluation also supported establishing stakeholder knowledge exchange and learning processes.

This is a single-site study among a relatively small group of people designed to achieve a specific evaluation objective. Caution in generalising to wider settings should be exercised.

This study highlights the efficacy of an incentive scheme, complemented with support from clinicians, and the significance of knowledge exchange and collaboration between stakeholders in health care with significance in similar settings.

The paper details the incentive scheme input, actions, output, outcomes and impact involving a wider range of stakeholders, including the emotional consequences for participants, clinicians and academics.