Malaria vaccination in Africa: A mini-review of challenges and opportunities.

Malaria remains an endemic public health concern in Africa, significantly contributing to morbidity and mortality rates. The inadequacies of traditional prevention measures, like integrated vector management and antimalarial drugs, have spurred efforts to strengthen the development and deployment of malaria vaccines. In addition to existing interventions like insecticide-treated bed nets and artemisinin-based combination therapies, malaria vaccine introduction and implementation in Africa could drastically reduce the disease burden and hasten steps toward malaria elimination. The malaria vaccine rollout is imminent as optimistic results from final clinical trials are anticipated. Thus, determining potential hurdles to malaria vaccine delivery and uptake in malaria-endemic regions of sub-Saharan Africa will enhance decisions and policymakers' preparedness to facilitate efficient and equitable vaccine delivery. A multisectoral approach is recommended to increase funding and resources, active community engagement and participation, and the involvement of healthcare providers.

The role of machine learning algorithms in detection of gestational diabetes; a narrative review of current evidence.

Gestational Diabetes Mellitus (GDM) poses significant health risks to mothers and infants. Early prediction and effective management are crucial to improving outcomes. Machine learning techniques have emerged as powerful tools for GDM prediction. This review compiles and analyses the available studies to highlight key findings and trends in the application of machine learning for GDM prediction. A comprehensive search of relevant studies published between 2000 and September 2023 was conducted. Fourteen studies were selected based on their focus on machine learning for GDM prediction. These studies were subjected to rigorous analysis to identify common themes and trends. The review revealed several key themes. Models capable of predicting GDM risk during the early stages of pregnancy were identified from the studies reviewed. Several studies underscored the necessity of tailoring predictive models to specific populations and demographic groups. These findings highlighted the limitations of uniform guidelines for diverse populations. Moreover, studies emphasised the value of integrating clinical data into GDM prediction models. This integration improved the treatment and care delivery for individuals diagnosed with GDM. While different machine learning models showed promise, selecting and weighing variables remains complex. The reviewed studies offer valuable insights into the complexities and potential solutions in GDM prediction using machine learning. The pursuit of accurate, early prediction models, the consideration of diverse populations, clinical data, and emerging data sources underscore the commitment of researchers to improve healthcare outcomes for pregnant individuals at risk of GDM.

Metformin mitigates dementia risk among individuals with type 2 diabetes.

This mini-narrative review explores the relationship between diabetes and dementia, focusing on the potential mitigating role of metformin in reducing cognitive decline among individuals with type 2 diabetes. The interplay of factors such as glycemic control, diabetic complications, and lifestyle influences characterises diabetes-related dementia. This review emphasises the significance of comprehensive diabetes management in addressing the heightened risk of dementia in this population. Methodologically, the review synthesises evidence from 23 studies retrieved through searches on PubMed, Embase, Google Scholar, and Scopus. Current evidence suggests a predominantly positive association between metformin use and a reduced risk of dementia in individuals with diabetes. However, the review shows the complex nature of these outcomes, revealing variations in results in some studies. These discrepancies show the importance of exploring dose-response relationships, long-term effects, and demographic diversity to unravel the complexities of metformin's impact on cognitive health. Limitations in the existing body of research, including methodological disparities and confounding variables, necessitate refined approaches in future studies. Large-scale prospective longitudinal studies and randomised controlled trials focusing specifically on cognitive effects are recommended. Propensity score matching and exploration of molecular mechanisms can enhance the validity of findings in clinical practice. From a clinical perspective, metformin can serve as a potential adjunctive therapy for individuals with diabetes at risk of cognitive decline.

Telemedicine as a tool to prevent multi-drug resistant tuberculosis in poor resource settings: Lessons from Nigeria.

Background: This mini review aims to provide an overview of the role of telemedicine in preventing multi-drug resistant tuberculosis (MDR-TB) in Nigeria. The specific objectives include examining the potential benefits of telemedicine, identifying the challenges associated with its implementation, and highlighting the importance of addressing infrastructure limitations and data privacy concerns. Methods: This minireview is based on a comprehensive analysis of existing literature, including scholarly articles, and reports,. A systematic search was conducted using electronic databases, such as PubMed and Google Scholar, to identify relevant publications related to telemedicine and MDR-TB prevention in Nigeria. The selected articles were assessed for their relevance, and key findings were synthesized to provide an overview of the role of telemedicine in addressing the challenges of MDR-TB in Nigeria. Results: The review demonstrates that telemedicine has the potential to significantly contribute to MDR-TB prevention efforts in Nigeria. The benefits of telemedicine include improved access to specialized care, enhanced patient adherence to treatment, and potential cost savings. However, challenges such as infrastructure limitations and data privacy concerns need to be addressed for successful implementation. Integrating telemedicine into the healthcare system has the potential to strengthen MDR-TB prevention, particularly in underserved areas, including within Nigeria. Specifically, the integration of telemedicine into the healthcare system can enhance access to specialized care, improve patient adherence, and potentially reduce costs associated with MDR-TB management. Conclusions: Addressing infrastructure challenges, ensuring data privacy and security, and fostering trust among healthcare providers and patients are critical for successful implementation of telemedicine. Further research and policy frameworks are needed to guide the effective implementation and scale-up of telemedicine in MDR-TB prevention efforts in Nigeria.

Closing the diagnostic gap: Liquid biopsy potential to transform ovarian cancer outcomes in sub-Saharan Africa.

Ovarian cancer presents a significant health challenge in sub-Saharan Africa (SSA), where late-stage diagnosis contributes to high mortality rates. This diagnostic gap arises from limited resources, poor healthcare infrastructure, and a lack of awareness about the disease. However, a potential game-changer is emerging in the form of liquid biopsy (LB), a minimally invasive diagnostic method. This paper analyses the current diagnostic gap in ovarian cancer in SSA, highlighting the socio-economic, cultural, and infrastructural factors that hinder early diagnosis and treatment. It discusses the challenges and potential of LB in the context of SSA, emphasizing its cost-effectiveness and adaptability to resource-limited settings. The transformative potential of LB in SSA is promising, offering a safer, more accessible, and cost-effective approach to ovarian cancer diagnosis. This paper provides recommendations for future directions, emphasizing the need for research, infrastructure development, stakeholder engagement, and international collaboration. By recognizing the transformative potential of LB and addressing the diagnostic gap, we can pave the way for early detection, improved treatment, and better outcomes for ovarian cancer patients in SSA. This paper sheds light on a path toward better healthcare access and equity in the region.

Revisiting the smart metallic nanomaterials: advances in nanotechnology-based antimicrobials.

Despite significant advancements in diagnostics and treatments over the years, the problem of antimicrobial drug resistance remains a pressing issue in public health. The reduced effectiveness of existing antimicrobial drugs has prompted efforts to seek alternative treatments for microbial pathogens or develop new drug candidates. Interestingly, nanomaterials are currently gaining global attention as a possible next-generation antibiotics. Nanotechnology holds significant importance, particularly when addressing infections caused by multi-drug-resistant organisms. Alternatively, these biomaterials can also be combined with antibiotics and other potent biomaterials, providing excellent synergistic effects. Over the past two decades, nanoparticles have gained significant attention among research communities. Despite the complexity of some of their synthesis strategies and chemistry, unrelenting efforts have been recorded in synthesizing potent and highly effective nanomaterials using different approaches. With the ongoing advancements in nanotechnology, integrating it into medical procedures presents novel approaches for improving the standard of patient healthcare. Although the field of nanotechnology offers promises, much remains to be learned to overcome the several inherent issues limiting their full translation to clinics. Here, we comprehensively discussed nanotechnology-based materials, focusing exclusively on metallic nanomaterials and highlighting the advances in their synthesis, chemistry, and mechanisms of action against bacterial pathogens. Importantly, we delve into the current challenges and prospects associated with the technology.

Using artificial intelligence to improve public health: a narrative review.

Artificial intelligence (AI) is a rapidly evolving tool revolutionizing many aspects of healthcare. AI has been predominantly employed in medicine and healthcare administration. However, in public health, the widespread employment of AI only began recently, with the advent of COVID-19. This review examines the advances of AI in public health and the potential challenges that lie ahead. Some of the ways AI has aided public health delivery are via spatial modeling, risk prediction, misinformation control, public health surveillance, disease forecasting, pandemic/epidemic modeling, and health diagnosis. However, the implementation of AI in public health is not universal due to factors including limited infrastructure, lack of technical understanding, data paucity, and ethical/privacy issues.

Determinants of maternal mortality in south-western Nigeria: Midwives' perceptions.

BACKGROUND: Maternal mortality remains one of Nigeria's most significant public health challenges. In order to address this issue sustainably, it is necessary to consider the perceptions of all stakeholders involved, including midwives. OBJECTIVES: To examine the determinants of maternal mortality in south-western Nigeria from the midwife's perspective. DESIGN: A cross-sectional study was employed using mixed methods with a semi-structured questionnaire and an in-depth interview guide. PARTICIPANTS: Quantitative data were obtained from 215 midwives using a convenience sampling technique. Qualitative data were obtained from 25 midwives from five government health centres, selected using a stratified sampling technique. METHODS: Quantitative data were analysed using SPSS Version 20 using descriptive and inferential statistics with 95 % confidence intervals, while qualitative data were analysed using thematic analyses. FINDINGS: The mean age and work experience of the participants were 35.2 ± 9.3 years and 8.4 ± 7.0 years, respectively. The midwives perceived that the main determinants of maternal mortality were postpartum haemorrhage (86.5 %), hypertensive disorder in pregnancy (80.9 %), mismanagement at mission homes/traditional birth attendant centres (MH/TBAs) (79.1 %) and sepsis (70.1 %). Some of the priority target areas to improve the well-being of pregnant women as identified by the midwives, were increased awareness of pregnancy danger signs (97 %), destigmatising caesarean section (CS) (96 %), regulation of MH/TBAs (92 %), and increased accessibility of hospitals (84 %). Findings from the qualitative data also affirmed that regulating MH/TBAs, destigmatising CS and subsidising healthcare expenses were prerequisites to curbing maternal mortality. Inferential analysis revealed that determinants such as unsafe abortion (p < 0.001), ectopic pregnancy (p = 0.001), domestic violence (p = 0.023), malaria (p = 0.029), short interbirth interval (p = 0.03), and patients' negative perceptions of CS delivery (p = 0.036) were more commonly perceived to be associated with maternal mortality by younger midwives (age 17-34 years) compared with older midwives. KEY CONCLUSION: The results indicate that resolving the maternal mortality crisis sustainably in Nigeria will require increased accessibility to basic health care and health promotion campaigns to counteract unhelpful sociocultural norms. IMPLICATIONS FOR PRACTICE: Future interventions must be tailored to address both traditional and emerging causes of maternal mortality in southwestern Nigeria.

Predictors and influencing factors of emotional intelligence among nurses in the North East England, United Kingdom.

BACKGROUND: Recognising that high levels of emotional intelligence (EI) are required for involvement in the nursing practice, this study was conducted to assess the traits of emotional intelligence, perception of emotional intelligence and factors associated with emotional intelligence among nursing teams in Northeast England. MATERIALS AND METHODS: For this descriptive cross-sectional study, a concurrent mixed method was employed (qualitative and quantitative method) using a convenience sampling technique. Data were obtained from one hundred and ten (110) staff nurses practicing with the National Health Service via a validated semi-structured questionnaire and in-depth interview. Data collected through questionnaires (online- Google form link) were retrieved via Ms excel spreadsheet and then imported to Statistics Package for Social Sciences (SPSS) version 25 for analyses. Interviews recorded were transcribed word for word as Nvivo software (version 12) was utilised for thematic analysis and rapid analysis was also adopted to validate the responses. RESULTS: Majority (77%) of the respondents were females, and about half (46%) have work experience between one to five years. The mean emotional intelligence trait score for each domain was self-awareness (20.20), self-regulation (38.15), self-motivation (20.54), empathy (18.78), and social skills (29.60), as 82% of the nurses had high emotional intelligence trait. There was a statistically significant relationship between empathy, and race of the respondents (P = 0.040). Also, from the qualitative data; cultural differences, personality traits, self-care, family support, and organisational structure are key predictors of emotional intelligence traits among nurses. CONCLUSION: Enhancing emotional intelligence traits among nursing teams is significant, as it may serve as an intervention strategy to manage changes and still increase level of morale and productivity among nurses. Hence, creating a more supportive environment, encouragement from team leads or supervisors, and training on stress management strategies can help to reduce burnout, anxiety and stress in nurses.

Prevalence and predictors of bullying among in-school adolescents in Nigeria.

Objective: As an emerging significant public health issue affecting many students globally, school bullying is a threat that should not be disregarded. While several published studies have focused on bullying in developed countries, very little is known about the prevalence and predictors of bullying in Nigeria. This study aimed to determine the prevalence and predictors of bullying in secondary schools in Edo State, Nigeria. Method: A descriptive cross-sectional study was conducted with 621 in-school adolescents using a multistage random sampling technique. The 40-item Olweus Bully/Victim Questionnaire (OBVQ) was utilized for data collection. The chi-squared test, Fisher's test, and binomial logistic regression analysis were utilized to examine associations between variables at 5% level of significance. Results: Approximately half of the respondents (51.9%) had experienced at least one type of bullying, while 173 (27.9%) reported themselves as bullies. The most common type of bullying was physical bullying in different forms (belonging taken/stolen-68.3%; kicked, pushed or locked indoor-52.2%; threatened-47.8%), while the most common location of bullying was the classroom in the absence of a teacher (75%); the perpetrators were reported by the majority (58.3%) to be classmates. Respondents in junior classes were 1.61-fold more likely to be bullied than those in senior classes (adjusted odds ratio [AOR]: 1.60; confidence interval [CI]: 1.15-2.24), those who live in rural areas were 1.75-fold more likely to be bullied than urban cities (AOR: 0.45; CI: 0.58-1.80), and those who were frequently beaten by their parents were 2.28-fold more likely to be bullies than those who were not beaten (AOR: 2.16; CI: 1.33-3.52). Furthermore, the act of bullying others was significantly associated with family monthly income (p = 0.01). Conclusion: Owing to the prevalence and predictors of bullying reported in this study, we recommend that policies should be implemented in schools to protect the most affected and vulnerable groups from being victims of school bullying.

Sanitary conditions, waste management, safety measures and sources of air pollution associated with shopping malls in Nigeria's largest city.

Objectives: Shopping malls are fast becoming one of the most visited public spaces globally. However, information on the possible environmental conditions in relation to health hazards in shopping malls is poorly documented in developing countries. This study assessed the sanitary conditions, waste management, safety measures and sources of air pollution associated with selected shopping malls in Nigeria.Study Design: a descriptive cross-sectional study design was adopted using a comparative approach. Methods: Three shopping malls (Mall Q, Mall R, and Mall S) in urban areas in Ibadan, Oyo State, Nigeria, were selected using convenience sampling technique. Three major shopping malls were selected using convenience sampling technique. Fifty seven, thirty five, and twenty nine stores were sampled in Mall Q, Mall R, and Mall S respectively. Direct on-site built environment and sanitary conditions of shopping malls were assessed using an observational checklist. Results: It was observed that all the selected shopping malls had air vents that were free from dust, unbroken walls, and emergency exits, although mold growths were observed on the walls and ceilings of Mall Q and Mall R. Toilet facilities were present and functional across all the shopping malls. Waste management facilities were available across the shopping malls with the absence of overfilled waste bins as regular emptying of the waste bins was a routine. Also, various safety measures and equipment were utilized across all the shopping malls, but safety signals and smoke detectors were absent in Mall R. Furthermore, Mall R and S were 5 m within the proximity of major roads, parking lots and public drainage channels. Conclusions: These findings reveal a need for improvement in the hygiene and sanitary conditions within shopping malls. Hence, there should be periodic environmental monitoring, and proper housekeeping practices should be encouraged in shopping malls in Nigeria.

COVID-19 vaccine hesitancy among Nigerian youths: Case study of students in Southwestern Nigeria.

BACKGROUND AND AIM: Vaccination has been appraised to be one of the most significant public health achievements in human history. However, in countries like Nigeria, vaccine hesitancy is a public health challenge that has consistently forestalled concerted efforts made by health authorities to curb the spread of communicable diseases such as COVID-19. To improve COVID-19 vaccine acceptance via targeted interventions, it is imperative to examine the public's perception. Thus, this study aims to evaluate vaccine hesitancy among university students in Southwestern Nigeria. MATERIALS AND METHODS: The study utilized a descriptive cross-sectional design. A self-administered questionnaire was administered to a total of 366 respondents who were recruited using the convenience sampling technique and snowball approach. Data were entered and analyzed using SPSS. RESULTS: The majority of the respondents were over 18 years (88%) and were between their first and third years (81%). Over a tenth of the respondents reported having at least a loved one that had tested positive for the virus, while only 88% believed the virus is real. Furthermore, only 17% of the students had a positive attitude toward the vaccine. Although 90% of the respondents were aware of the administration of COVID-19 vaccine in Nigeria, only around a quarter were willing to take the vaccine, while 5.5% had been vaccinated. The major reasons for COVID-19 vaccine hesitancy highlighted by the respondents were concerns about vaccine side effects (21.3%), lack of trust in the authorities (26.5%), vaccine efficacy (13.1%), and diverse mystical possibilities (39.1%). CONCLUSION: The results indicate that a significant communication gap exists between the respondents and local health authorities. To enhance the acceptance of COVID-19 vaccines, extensive and targeted health promotion campaigns are required to allay specific concerns raised by the public.

Crude oil exploration in Africa: socio-economic implications, environmental impacts, and mitigation strategies.

Crude oil exploration is a source of significant revenue in Africa via trade and investment since its discovery in the mid-19th Century. Crude oil has bolstered the continent's economy and improved the wellbeing of the citizenry. Historically, Africa has suffered from conflicts due to uneven redistribution of crude oil revenue and severe environmental pollution. Advancements in geophysical survey techniques, such as magnetic and gravity methods, to seismic methods, have made the commercial exploration of crude oil possible for some other countries in Africa apart from Nigeria, Angola, Algeria, Libya, and Egypt. The occurrence of organic-rich, oil-prone Type I, II, and mixed II/III kerogens in sedimentary basins and entrapment within reservoir rocks with intrinsic petrophysical properties are majorly responsible for the large deposits of hydrocarbon in Africa. The unethical practices by some multinational oil corporations have resulted in social movements against them by host communities and human rights groups. The unscrupulous diversion of public funds, award of oil blocks, and production rights to certain individuals have impaired economic growth in Africa. The over-dependence on crude oil revenues has caused the economic recession in oil-producing countries due to plummeting oil prices and global pandemic. Most host communities of crude oil deposits suffer from a lack of infrastructure, arable soils, clean water, and their functioning capabilities are violated by crude oil exploratory activities, without adequate compensations and remedial actions taken by oil companies and the government. Thus, this review examines crude oil exploration in Africa and provides insight into the environmental and socio-economic implications of crude oil exploration in Africa. Furthermore, this report highlights some recommendations that may ensure ethical and sustainable practices toward minimizing negative impacts and improving the quality of life in affected communities.

Review on 3D printing: Fight against COVID-19.

The outbreak of coronavirus disease in 2019 (COVID-19) caused by the SARS-CoV-2 virus and its pandemic effects have created a demand for essential medical equipment. To date, there are no specific, clinically significant licensed drugs and vaccines available for COVID-19. Hence, mapping out COVID-19 problems and preventing the spread with relevant technology are very urgent. This study is a review of the work done till October, 2020 on solving COVID-19 with 3D printing. Many patients who need to be hospitalized because of COVID-19 can only survive on bio-macromolecules antiviral respiratory assistance and other medical devices. A bio-cellular face shield with relative comfortability made of bio-macromolecules polymerized polyvinyl chloride (BPVC) and other biomaterials are produced with 3D printers. Summarily, it was evident from this review study that additive manufacturing (AM) is a proffered technology for efficient production of an improved bio-macromolecules capable of significant COVID-19 test and personal protective equipment (PPE) to reduce the effect of COVID-19 on the world economy. Innovative AM applications can play an essential role to combat invisible killers (COVID-19) and its hydra-headed pandemic effects on humans, economics and society.