An Economic Assessment of Energy Poverty and Households Welfare in Ghana

This study sought to investigate the effects of household socio-economic factors on energy poverty in Ghana. Strong evidence points to the fact that energy is a driver of economic growth, hence, the presence of energy poverty is a major barrier to achieving the development objectives of any country. A binomial logistic model was used to analyse the effects of parametric factors on energy poverty. Data of 16,048 households from the Ghana Living Standards Survey 6, a nationally representative survey, served as the basis for the logistics analysis.  The results showed that the energy poverty rate in Ghana stands at 38% and households spend around 22% of income on modern energy forms. In addition, energy poverty is more prevalent in rural areas with them being 5.7 times more likely to be energy poor. Also, the results indicated that determinants including age and household size had a negative effect on energy poverty while a higher level of education, income, and welfare had non-decreasing effects on energy poverty. The study concludes that a high welfare level reduces the likelihood that a household is energy poor. To close the disparity between the rural and urban areas with regards to energy access, development of off-grid energy schemes should be implemented largely in rural areas. Keywords: Energy Stacking, Logistic Regression, Energy Poverty, Households Welfare. DOI: 10.7176/JESD/11-16-01 Publication date:August 31st 202

Postoperative Corneal and Surgically Induced Astigmatism following Superior Approach Manual Small Incision Cataract Surgery in Patients with Preoperative Against-the-Rule Astigmatism

The aim of the study was to report postoperative corneal and surgically induced astigmatism (SIA) in patients with preoperative against-the-rule (ATR) astigmatism who underwent superior approach manual small incision cataract surgery (MSICS). 58 eyes of 58 cataract patients with preoperative ATR astigmatism were involved in this study. All patients had operable cataracts and underwent superior approach MSICS. Keratometric (K) readings were taken prior to surgery and at 12 weeks after surgery. Centroid values of SIA, preoperative astigmatism, and postoperative astigmatism were calculated using Cartesian coordinates based analysis. Wilcoxon signed rank test was used to compute statistical significance between mean preoperative and postoperative corneal astigmatism. Cohen’s d was used as effect size measure. Centroid values of 1.42 D × 179, 2.48 D × 0, and 1.07 D × 1 were recorded, respectively, for preoperative astigmatism, postoperative astigmatism, and SIA. Wilcoxon signed rank test indicated that mean ± SD postoperative corneal astigmatism (2.80±1.40 D) was statistically significantly greater than preoperative corneal astigmatism (1.49±1.34 D), Z=-6.263, p<0.0001. A high Cohen’s d of 1.32 was found. Our results suggest statistical and clinically significant greater postoperative corneal astigmatism than preoperative corneal astigmatism for ATR astigmatism cataract patients who underwent superior approach MSICS

Whole genome sequencing and spatial analysis identifies recent tuberculosis transmission hotspots in Ghana

Whole genome sequencing (WGS) is progressively being used to investigate the transmission dynamics of; Mycobacterium tuberculosis; complex (MTBC). We used WGS analysis to resolve traditional genotype clusters and explored the spatial distribution of confirmed recent transmission clusters. Bacterial genomes from a total of 452 MTBC isolates belonging to large traditional clusters from a population-based study spanning July 2012 and December 2015 were obtained through short read next-generation sequencing using the illumina HiSeq2500 platform. We performed clustering and spatial analysis using specified R packages and ArcGIS. Of the 452 traditional genotype clustered genomes, 314 (69.5%) were confirmed clusters with a median cluster size of 7.5 genomes and an interquartile range of 4-12. Recent tuberculosis (TB) transmission was estimated as 24.7%. We confirmed the wide spread of a Cameroon sub-lineage clone with a cluster size of 78 genomes predominantly from the Ablekuma sub-district of Accra metropolis. More importantly, we identified a recent transmission cluster associated with isoniazid resistance belonging to the Ghana sub-lineage of lineage 4. WGS was useful in detecting unsuspected outbreaks; hence, we recommend its use not only as a research tool but as a surveillance tool to aid in providing the necessary guided steps to track, monitor, and control TB

Quality of nutritional status assessment and its relationship with the effect of rainfall on childhood stunting: a cross-sectional study in rural Burkina Faso

Objectives: In Burkina Faso, one in every four children under 5 years is stunted. Climate change will exacerbate childhood stunting. Strengthening the health system, particularly the quality of nutrition care at primary health facilities, can minimise the adverse climate effect on stunting. Thus, we examined the quality of nutritional status assessment (QoNA) during curative childcare services in primary health facilities in rural Burkina Faso and its relationship with rainfall-induced childhood stunting. Study design: We conducted a cross-sectional analysis using anthropometric, rainfall, and clinical observation data. Methods: Our dependent variable was the height-for-age z-score (HAZ) of children under 2 years. Our focal climatic measure was mean rainfall deviation (MRD), calculated as the mean of the difference between 30-year monthly household-level rainfall means and the corresponding months for each child from conception to data collection. QoNA was based on the weight, height, general paleness and oedema assessment. We used a mixed-effect multilevel model and analysed heterogeneity by sex and socio-economic status. Results: Among 5027 young (3–23 months) children (mean age 12 ± 6 months), 21% were stunted (HAZ ≤ −2). The mean MRD was 11 ± 4 mm, and the mean QoNA was 2.86 ± 0.99. The proportion of children in low, medium, and high QoNA areas was 10%, 54%, and 36%, respectively. HAZ showed a negative correlation with MRD. Higher QoNA lowered the negative effect of MRD on HAZ (β = 0.017, P = 0.003, confidence interval = [0.006, 0.029]). Males and children from poor households benefited less from the moderating effect of QoNA. Conclusion: Improving the quality of nutrition assessments can supplement existing efforts to reduce the adverse effects of climate change on children's nutritional well-being

Drug discovery research in Ghana, challenges, current efforts, and the way forward

We have a long-term vision to develop drug discovery research capacity within Ghana, to tackle unmet medical needs in Ghana and the wider West African region. However, there are several issues and challenges that need to be overcome to enable this vision, including training, human resource, equipment, infrastructure, procurement, and logistics. We discuss these challenges from the context of Ghana in this review. An important development is the universities and research centres within Ghana working together to address some of these challenges. Therefore, while there is a long way to go to fully accomplish our vision, there are encouraging signs

Every drop matters: combining population-based and satellite data to investigate the link between lifetime rainfall exposure and chronic undernutrition in children under five years in rural Burkina Faso.

Climate change is projected to induce extreme and irregular rainfall patterns in the West African Sahel region, affecting household food security and income. Children are among the worst affected population groups. Previous studies focusing on rainfall irregularities in specified periods have revealed how child health and nutritional status are impacted, especially in rural settings. However, the aggregated effect of rainfall over a lifetime on chronic child undernutrition remains poorly understood. We conducted a multilevel regression using a 2017 household survey from rural Burkina Faso containing 12 919 under-five-year-old children and their corresponding household rainfall data. The rainfall data originated from the Climate Hazards Infrared Precipitation with Stations monthly dataset with a native resolution of 4.8 km (0.05°). We show that an increase in rainfall below 75 mm monthly average tends to produce poor nutritional outcomes (regression coefficient = −0.11***; 95% CI = −0.13, −0.10; p < 0.001) in rural Burkina Faso children. We found a consistent negative relationship between different sex and household wealth groups, but not age groups. Vulnerable younger children were more affected by the adverse effects of increased rainfall, while older children seemed to handle it better. Our methodological approach tracing the impact of rainfall over children’s lifetimes makes a meaningful contribution to the portfolio of tools for studying the complex relationship between climate change and health outcomes. Our work confirms that rainfall is a risk factor for chronic child undernutrition, highlighting the need for adaptation strategies that boost household and community resilience to counteract the harmful impacts of climate change on child nutritional status

Current trends in the application of causal inference methods to pooled longitudinal non-randomised data: A protocol for a methodological systematic review

Introduction Causal methods have been adopted and adapted across health disciplines, particularly for the analysis of single studies. However, the sample sizes necessary to best inform decision-making are often not attainable with single studies, making pooled individual-level data analysis invaluable for public health efforts. Researchers commonly implement causal methods prevailing in their home disciplines, and how these are selected, evaluated, implemented and reported may vary widely. To our knowledge, no article has yet evaluated trends in the implementation and reporting of causal methods in studies leveraging individual-level data pooled from several studies. We undertake this review to uncover patterns in the implementation and reporting of causal methods used across disciplines in research focused on health outcomes. We will investigate variations in methods to infer causality used across disciplines, time and geography and identify gaps in reporting of methods to inform the development of reporting standards and the conversation required to effect change. Methods and analysis We will search four databases (EBSCO, Embase, PubMed, Web of Science) using a search strategy developed with librarians from three universities (Heidelberg University, Harvard University, and University of California, San Francisco). The search strategy includes terms such as 'pool∗', 'harmoniz∗', 'cohort∗', 'observational', variations on 'individual-level data'. Four reviewers will independently screen articles using Covidence and extract data from included articles. The extracted data will be analysed descriptively in tables and graphically to reveal the pattern in methods implementation and reporting. This protocol has been registered with PROSPERO (CRD42020143148). Ethics and dissemination No ethical approval was required as only publicly available data were used. The results will be submitted as a manuscript to a peer-reviewed journal, disseminated in conferences if relevant, and published as part of doctoral dissertations in Global Health at the Heidelberg University Hospital

Application of causal inference methods in individual-participant data meta-analyses in medicine: addressing data handling and reporting gaps with new proposed reporting guidelines

Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) conducted with non-randomized exposures, published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy

Stage at diagnosis of breast cancer in sub-Saharan Africa: a systematic review and meta-analysis

Background The incidence of breast cancer in sub-Saharan Africa is relatively low, but as survival from the disease in the region is poor, mortality rates are as high as in high-income countries. Stage at diagnosis is a major contributing factor to poor survival from breast cancer. We aimed to do a systematic review and meta-analysis on stage at diagnosis of breast cancer in sub-Saharan Africa to examine trends over time, and investigate sources of variations across the region. Methods We searched MEDLINE, Embase, Web of Knowledge, and Africa-Wide Information to identify studies on breast cancer stage at diagnosis in sub-Saharan African women published before Jan 1, 2014, and in any language. Random-effects meta-analyses were done to investigate between-study heterogeneity in percentage of late-stage breast cancer (stage III/IV), and meta-regression analyses to identify potential sources of variation. Percentages of women with late-stage breast cancer at diagnosis in sub-Saharan Africa were compared with similar estimates for black and white women in the USA from the Surveillance, Epidemiology, and End Results database. Findings 83 studies were included, which consisted of 26 788 women from 17 sub-Saharan African countries. There was wide between-study heterogeneity in the percentage of late-stage disease at diagnosis (median 74·7%, range 30·3–100%, I2=93·3%, p<0·0001). The percentage of patients with late-stage disease at diagnosis did not vary by region in black women, but was lower in non-black women from southern Africa than in black women in any region (absolute difference [AD] from black women in western Africa [reference group] −18·1%, 95% CI −28·2 to −8·0), and higher for populations from mixed (urban and rural) settings rather than urban settings (13·2%, 5·7 to 20·7, in analyses restricted to black women). The percentage of patients with late-stage disease at diagnosis in black Africans decreased over time (–10·5%, −19·3 to −1·6; for 2000 or later vs 1980 or before), but it was still higher around 2010 than it was in white and black women in the USA 40 years previously. Interpretation Strategies for early diagnosis of breast cancer should be regarded as a major priority by cancer control programmes in sub-Saharan Africa

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic