Navigating Nigeria's Health Landscape: Population Growth and Its Health Implications

This comprehensive analysis examines the multifaceted impacts of population growth on public health in Nigeria. Drawing parallels with Omran's epidemiological transition model (that focuses on the intricate means that patterns of health and illness are changing, as well as the relationships that exist between these patterns and the sociological, demographic, and economic factors that influence them) and referencing experiences from Chile and Ceylon. The study highlights a substantial rise in Nigeria's population causing a double burden of infectious and non-communicable diseases, leading to higher morbidity, and mortality rates, increased healthcare costs, decreased productivity, and health inequalities, posing significant challenges to the country's healthcare system. Furthermore, the correlation between low education levels and health outcomes underscores the importance of addressing systemic deficiencies in Nigeria's educational sector. The article emphasizes the urgent need for strategic interventions to mitigate the adverse effects of population growth on health. Recommendations include revitalizing primary healthcare centers, fostering public-private partnerships to enhance healthcare accessibility, leveraging technological advancements like telemedicine, and promoting initiatives to improve nutrition and environmental sustainability. Moreover, prioritizing education on reproductive health and family planning emerges as a crucial strategy to manage population growth sustainably. In conclusion, the article underscores the imperative for collaborative efforts across sectors to navigate Nigeria's evolving health landscape amidst increasing population growth. By implementing targeted policies and interventions, Nigeria can strive toward achieving universal health coverage, enhancing health outcomes, and ultimately raising the standard of living for its populace.

Implications of climatic change on sickle cell anemia: A review

Sickle cell anemia (SCA) is a hereditary blood disorder characterized by abnormal hemoglobin, causing red blood cells to assume a sickle shape, leading to various complications. Climate change has emerged as a significant global challenge, influencing environmental conditions worldwide. This paper explores the implications of climatic variations on the prevalence, management, and outcomes of SCA. Climate change affects weather patterns, leading to altered temperatures, increased frequency of extreme weather events, and variations in humidity levels. These changes can have a profound impact on individuals living with SCA. High temperatures exacerbate the symptoms of SCA, potentially triggering painful vaso-occlusive crises due to dehydration and increased blood viscosity. Conversely, cold temperatures may induce vaso-occlusion by causing blood vessels to constrict. Changes in rainfall patterns might also affect water accessibility, which is crucial for maintaining adequate hydration, particularly in regions prone to droughts. The management of SCA is multifaceted, involving regular medical care, hydration, and avoiding triggers that could precipitate a crisis. Adverse weather events and natural disasters can disrupt healthcare infrastructure and access to essential medications and resources for SCA patients, especially in vulnerable communities. To mitigate the implications of climatic change on SCA, interdisciplinary strategies are essential. These strategies may include enhancing healthcare systems' resilience to climate-related disruptions, implementing adaptive measures to address changing environmental conditions, and promoting public awareness and education on managing SCA amidst climate variability. In conclusion, climatic variations pose significant challenges for individuals with SCA, affecting the prevalence, management, and outcomes of the disease.

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.

The Journey of Zanzibar's Digitally Enabled Community Health Program to National Scale: Implementation Report

BACKGROUND

While high-quality primary health care services can meet 80%-90% of health needs over a person's lifetime, this potential is severely hindered in many low-resource countries by a constrained health care system. There is a growing consensus that effectively designed, resourced, and managed community health worker programs are a critical component of a well-functioning primary health system, and digital technology is recognized as an important enabler of health systems transformation.

OBJECTIVE

In this implementation report, we describe the design and rollout of Zanzibar's national, digitally enabled community health program-Jamii ni Afya.

METHODS

Since 2010, D-tree International has partnered with the Ministry of Health Zanzibar to pilot and generate evidence for a digitally enabled community health program, which was formally adopted and scaled nationally by the government in 2018. Community health workers use a mobile app that guides service delivery and data collection for home-based health services, resulting in comprehensive service delivery, access to real-time data, efficient management of resources, and continuous quality improvement.

RESULTS

The Zanzibar government has documented increases in the delivery of health facilities among pregnant women and reductions in stunting among children younger than 5 years since the community health program has scaled. Key success factors included starting with the health challenge and local context rather than the technology, usage of data for decision-making, and extensive collaboration with local and global partners and funders. Lessons learned include the significant time it takes to scale and institutionalize a digital health systems innovation due to the time to generate evidence, change opinions, and build capacity.

CONCLUSIONS

Jamii ni Afya represents one of the world's first examples of a nationally scaled digitally enabled community health program. This implementation report outlines key successes and lessons learned, which may have applicability to other governments and partners working to sustainably strengthen primary health systems.

Influence of geography, stroke timing, and weather conditions on transport and workflow times: Results from a longitudinal 5-year Canadian provincial registry

BACKGROUND

In areas with high population spread such as Saskatchewan, it can be challenging to provide timely endovascular stroke treatment (EVT) to patients living far away from comprehensive stroke centres (CSC). We assessed the association of geography, stroke timing and weather conditions on EVT workflow times and clinical outcomes in Saskatchewan.

METHODS

We included patients who underwent EVT between January 2017 and December 2022 in the province of Saskatchewan, Canada. Univariable and multivariable associations of time from last known well-to-CSC arrival, CSC arrival-to-reperfusion, and 90-day modified Rankin Score (mRS) with driving distance from patient home to CSC, transport mode, outdoor temperature and stroke timing (day & time) were assessed using descriptive statistics and multivariable regression.

RESULTS

Three-hundred-three patients in the province of Saskatchewan underwent EVT between January 2017 and December 2022. Distance from patient home to CSC (beta-coefficient per 10 km increase = 0.02, 95% CI: 0.01-0.03) and direct to CSC transport (beta-coefficient = -0.76, 95% CI = -1.01-[-0.51]) were associated with last known well to CSC arrival time. In-hospital stroke (beta-coefficient = 0.37, 95% CI: 0.16-0.58), direct-to-CSC transfer (beta-coefficient = 0.27, 95% CI: 0.13-0.41) and daytime stroke onset (beta-coefficient = -0.15, 95% CI: -0.28-[-0.04]) were associated with time from CSC arrival to reperfusion. No association with 90-day mRS was seen.

CONCLUSION

Geographic factors and stroke timing were associated with EVT workflow times. However, no association with clinical outcomes was seen, suggesting that EVT patients living remote areas of Saskatchewan have similar benefit from EVT compared to urban areas. Every effort should be made to offer timely EVT to patients from remote areas.

Artificial Intelligence and Machine Learning Based Intervention in Medical Infrastructure: A Review and Future Trends

People in the life sciences who work with Artificial Intelligence (AI) and Machine Learning (ML) are under increased pressure to develop algorithms faster than ever. The possibility of revealing innovative insights and speeding breakthroughs lies in using large datasets integrated on several levels. However, even if there is more data at our disposal than ever, only a meager portion is being filtered, interpreted, integrated, and analyzed. The subject of this technology is the study of how computers may learn from data and imitate human mental processes. Both an increase in the learning capacity and the provision of a decision support system at a size that is redefining the future of healthcare are enabled by AI and ML. This article offers a survey of the uses of AI and ML in the healthcare industry, with a particular emphasis on clinical, developmental, administrative, and global health implementations to support the healthcare infrastructure as a whole, along with the impact and expectations of each component of healthcare. Additionally, possible future trends and scopes of the utilization of this technology in medical infrastructure have also been discussed.

The Development of an Infrastructure to Facilitate the Use of Whole Genome Sequencing for Population Health

The clinical use of genomic analysis has expanded rapidly resulting in an increased availability and utility of genomic information in clinical care. We have developed an infrastructure utilizing informatics tools and clinical processes to facilitate the use of whole genome sequencing data for population health management across the healthcare system. Our resulting framework scaled well to multiple clinical domains in both pediatric and adult care, although there were domain specific challenges that arose. Our infrastructure was complementary to existing clinical processes and well-received by care providers and patients. Informatics solutions were critical to the successful deployment and scaling of this program. Implementation of genomics at the scale of population health utilizes complicated technologies and processes that for many health systems are not supported by current information systems or in existing clinical workflows. To scale such a system requires a substantial clinical framework backed by informatics tools to facilitate the flow and management of data. Our work represents an early model that has been successful in scaling to 29 different genes with associated genetic conditions in four clinical domains. Work is ongoing to optimize informatics tools; and to identify best practices for translation to smaller healthcare systems.

Ethnolinguistic diversity and the spread of communicable diseases: a cross-country study on the COVID-19 pandemic

Motivated by the varying effectiveness of government intervention policies to contain the COVID-19 pandemic, and the potential positive relationship between ethnolinguistic diversity and social distance, this paper aims to provide empirical evidence on the relationship between ethnolinguistic diversity and the spread of COVID-19. In particular, using global data from 113 developed and developing countries during the early stages of the pandemic (from 31 December 2019 to 8 July 2020), we have found a significant negative effect of ethnolinguistic diversity on the spread of the virus. The result is robust to alternative measures of ethnolinguistic diversity and estimator that addresses endogeneity. Moreover, we also show that the impact of ethnolinguistic diversity on the spread of COVID-19 differs in economies characterized by different levels of democracy, policy stringency on addressing COVID-19 and health expenditure.

Socio-economic and environmental factors influenced the United Nations healthcare sustainable agenda: evidence from a panel of selected Asian and African countries

The objective of the study is to evaluate socio-economic and environmental factors that influenced the United Nations healthcare sustainable agenda in a panel of 21 Asian and African countries. The results show that changes in price level (0.0062, p < 0.000), life risks of maternal death (4.579, p < 0.000), and under-5 mortality rate (0.374, p < 0.000) substantially increases out-of-pocket health expenditures, while CO₂ emissions (5.681, p < 0.003), prevalence of undernourishment (15.184, p < 0.000), PM_2.5 particulate emission (1557, p < 0.000), unemployment, and private health expenditures (30.729, p < 0000) are associated with high mortality rate across countries. Healthcare reforms affected by low healthcare spending, unsustainable environment, and ease of environmental regulations that ultimately increases mortality rate across countries. The Granger causality estimates confirmed the different causal mechanisms between socio-economic and environmental factors, which is directly linked with the country's healthcare agenda, i.e., the causality running from (i) CO₂ emissions to life risks of maternal death and under-5 mortality rate, (ii) from depth of food deficit to incidence of tuberculosis and unemployment, (iii) from PM_2.5 emissions to infant mortality rate, (iv) from foreign direct investment (FDI) inflows to PM_2.5 emissions, (v) from trade openness to greenhouse gas (GHG) emissions, and (vi) from mortality indicators to per capita income, while there is a feedback relationship between health expenditures and per capita income across countries. The variance decomposition analysis shows that (i) under-5 mortality rate will increase out-of-pocket health expenditures, (ii) unemployment rate will increase mortality indicators, and (iii) health expenditures will increase economic well-being in a panel of selected countries, for the next 10 years.

Person-centric clinical trials: defining the N-of-1 clinical trial utilizing a practice-based translational network

A person-centric clinical trial is inclusive of both the investigator and the person and as such represents point-of-use data generated at the practice level and encompasses both health and disease. Raising the clinical encounter to a research encounter and providing an infrastructure to support a level of quality assurance creates a synergy for efficiency for healthcare delivery. The interface of translational studies and clinical research poses an opportunity, whereby person-centricity can support transparency, facilitate informed consent, improve safety, enhance recruitment and compliance, improve dissemination of results, implement change and help close the translational gap. The model represents robust clinical data from persons of record allowing for improved interpretation of drug/device side-effects and for regulatory reviewers to expedite the approval process.

Hospital concessions in Chile: where we are and where we are heading

CONTEXT

Public-private partnerships began under President Ricardo Lagos, driven by the need to provide roads and other hard facilities. Over time, they expanded into social concessions such as prisons and hospitals. During the Bachelet administration, the construction of two mid-sized hospitals of Santiago was tendered with private finance initiative. During the government of Sebastián Piñera, three more hospitals were tendered.

CRITICAL ANALYSIS

This article critically examines the grounds on which social concessions have been introduced in different parts of the world. I argue that the there are two main rationales underlying the position of those favorable to concession arrangements: pragmatic reasons and ideological-utopian reasons. I refute the arguments related to closing the infrastructure gap, effect on public debt, transfer of risk to the private sector, greater efficiency of the private sector, freeing-up of public funds and quality of health care.

CONCLUSIONS

Review of the international literature does not yield evidence in favor of hospital concessions consistent with the principles and drivers that promote them. Quite the contrary, when the “Value for Money” methodology has been used, concessions have proven to decrease the overall capacity of the health system and to negatively affect quality of health care. I also note that there is a potential impact on intergenerational equity with projects that span for long periods, as is the case of hospital concessions. I conclude that, since there is no evidence base grounded on sound technical principles in favor of this policy, the real underlying reasons to promote private financing of public health infrastructure are ideological, and functional to market interests but not to collective preferences.

Using appendiceal perforation rates to measure impact of a disaster on healthcare system effectiveness

OBJECTIVES

To understand baseline inequities in appendiceal perforation rates and the impact of hurricane destruction on the healthcare system with respect to perforation rates and racial disparities.

METHODS

We used claims data extracted from Medicaid Analytic Extract files to identify appendicitis diagnoses in children and adolescents based on International Classification of Diseases-9 codes and appendectomy procedures based on Current Procedural Terminology codes in the hurricane-affected states of Mississippi and Louisiana. County-level summary data obtained from 2005 Area Resource Files were used to determine high and low hurricane-affected areas. We estimated logistic regression models, mutually adjusting for race, sex, and age, to examine disparities and mixed logistic regression models to determine whether county-level effects contributed to perforation rates.

RESULTS

There were nine counties in the high-impact area and 133 counties in the low-impact area. Living in the high- or low-impact area was not associated with a statistically different rate of perforation before or after Hurricane Katrina; however, living in the high-impact area was associated with a change from a lower risk (odds ratio [OR] 0.62) of perforation prehurricane to a higher risk (OR 1.14) posthurricane compared with those living in the low-impact areas. African Americans had statistically higher perforation rates than whites in the high-impact areas both before (OR 1.46) and after (OR 1.71) Hurricane Katrina.

CONCLUSIONS

Health professionals and hospital systems were able to maintain effective levels of care before and after Hurricane Katrina; however, perforation rates in African Americans suggest ongoing racial disparities during disasters.