ghanaopendata/ghanaian-research-english huggingface dataset:
Implementing effective community‑based surveillance in research studies of maternal, newborn and infant outcomes in low resource settings

Background: Globally adopted health and development milestones have not only encouraged improvements in the health and wellbeing of women and infants worldwide, but also a better understanding of the epidemiology of key outcomes and the development of effective interventions in these vulnerable groups. Monitoring of maternal and child health outcomes for milestone tracking requires the collection of good quality data over the long term, which can be particularly challenging in poorly-resourced settings. Despite the wealth of general advice on conducting field trials, there is a lack of specific guidance on designing and implementing studies on mothers and infants. Additional considerations are required when establishing surveillance systems to capture real-time information at scale on pregnancies, pregnancy outcomes, and maternal and infant health outcomes. Main body: Based on two decades of collaborative research experience between the Kintampo Health Research Centre in Ghana and the London School of Hygiene and Tropical Medicine, we propose a checklist of key items to consider when designing and implementing systems for pregnancy surveillance and the identification and classification of maternal and infant outcomes in research studies. These are summarised under four key headings: understanding your population; planning data collection cycles; enhancing routine surveillance with additional data collection methods; and designing data collection and management systems that are adaptable in real-time. Conclusion: High-quality population-based research studies in low resource communities are essential to ensure continued improvement in health metrics and a reduction in inequalities in maternal and infant outcomes. We hope that the lessons learnt described in this paper will help researchers when planning and implementing their studies.

Source: UG
Implementing health technology assessment in Ghana to support universal health coverage: building relationships that focus on people, policy, and process

Ghana is one of the few African countries to enact legislation and earmark significant funding to establish universal health coverage (UHC) through the National Health Insurance Scheme, although donor funds have declined recently. Given a disproportionate level of spending on medicines, health technology assessment (HTA) can support resource allocation decisions in the face of highly constrained budgets, as commonly found in low-resource settings. The Ghanaian Ministry of Health, supported by the International Decision Support Initiative (iDSI), initiated a HTA study in 2016 to examine the cost-effectiveness of antihypertensive medicines. We aimed to summarize key insights from this work that highlights success factors beyond producing purely technical outputs. These include the need for capacity building, academic collaboration, and ongoing partnerships with a broad range of experts and stakeholders. By building on this HTA study, and with ongoing interactions with iDSI, HTAi, WHO, and others, Ghana will be well positioned to institutionalize HTA in resource allocation decisions and support progress toward UHC.

Source: UG
Implementing integrated disease surveillance and response: Four African countries' experience, 1998-2005

The Integrated Disease Surveillance and Response (IDSR) strategy was developed by the Africa Regional Office (AFRO) of the World Health Organisation (WHO) and proposed for adoption by member states in 1998. The goal was to build WHO/AFRO countries' capacity to detect, report and effectively respond to priority infectious diseases. This evaluation focuses on the outcomes in four countries that implemented this strategy. Major successes included: integration of the surveillance function of most of the categorical disease control programmes; implementation of standard surveillance, laboratory and response guidelines; improved timeliness and completeness of surveillance data and increased national-level review and use of surveillance data for response. The most challenging aspects were: strengthening laboratory networks; providing regular feedback and supervision on surveillance and response activities; routine monitoring of IDSR activities and extending the strategy to sub-national levels. © 2010 Taylor & Francis.

Source: UG
Implementing Machine Learning for Smart Farming to Forecast Farmers’ Interest in Hiring Equipment

Farmers’ physical labor and debt are reduced as a result of agricultural automation, which emphasizes efficient and effective use of various machines in farming operations with the purpose of reducing physical labor and debt. It is a revolutionary idea in agriculture to create custom hiring centers, which are intended to make it easier for like-minded farmers to embrace technology/ machinery for enhanced resource management practices. The study in question examines the significance of tool renting and sharing in the workplace. Rental and sharing equipment are two approaches that might be used to enable farmers to borrow equipment at a cheaper cost than they would otherwise have to pay for it. The following is a manual pilot study of 562 farmers in India to address the numerous challenges farmers face when looking for tools and equipment, as well as to determine their strong interest in the process of renting and sharing equipment. The study was conducted to address the numerous challenges farmers face when looking for tools and equipment and to determine their strong interest in the process of renting and sharing equipment. Farmers are divided into three groups according to the results of this poll: small, moderate, and large. Training and testing splits were used on the same data set in order to get a better understanding of the target variables. The data set for the survey was standardized in order to remove ambiguity. In this research, three different machine learning models were utilized: nearest neighbors, logistic regression, and decision trees. K-nearest neighbors was the most often used model, followed by logistic regression and decision trees. In order to get the best possible result, a comparison of the aforementioned algorithm models was carried out, which revealed that the decision tree is the better model among the others in this regard. Because the decision tree model is completely reliant on a large number of input factors, such as the kind of crop, the time/month of harvest, and the type of equipment necessary for the crops, it has the potential to have a social and economic impact on farmers and their livelihoods.

Source: UG
Implementing Machine Learning for Smart Farming to Forecast Farmers’ Interest in Hiring Equipment

Farmers’ physical labor and debt are reduced as a result of agricultural automation, which emphasizes efficient and effective use of various machines in farming operations with the purpose of reducing physical labor and debt. It is a revolutionary idea in agriculture to create custom hiring centers, which are intended to make it easier for like-minded farmers to embrace technology/ machinery for enhanced resource management practices. *e study in question examines the significance of tool renting and sharing in the workplace. Rental and sharing equipment are two approaches that might be used to enable farmers to borrow equipment at a cheaper cost than they would otherwise have to pay for it. *e following is a manual pilot study of 562 farmers in India to address the numerous challenges farmers face when looking for tools and equipment, as well as to determine their strong interest in the process of renting and sharing equipment. *e study was conducted to address the numerous challenges farmers face when looking for tools and equipment and to determine their strong interest in the process of renting and sharing equipment. Farmers are divided into three groups according to the results of this poll: small, moderate, and large. Training and testing splits were used on the same data set in order to get a better understanding of the target variables. *e data set for the survey was standardized in order to remove ambiguity. In this research, three different machine learning models were utilized: nearest neighbors, logistic regression, and decision trees. K-nearest neighbors was the most often used model, followed by logistic regression and decision trees. In order to get the best possible result, a comparison of the aforementioned algorithm models was carried out, which revealed that the decision tree is the better model among the others in this regard. Because the decision tree model is completely reliant on a large number of input factors, such as the kind of crop, the time/month of harvest, and the type of equipment necessary for the crops, it has the potential to have a social and economic impact on farmers and their livelihoods.

Source: UG
Implementing maternal and newborn health quality of care standards in healthcare facilities to improve the adoption of respectful maternity care in Bangladesh, Ghana and Tanzania: a controlled before and after study

Introduction Many women worldwide cannot access respectful maternity care (RMC). We assessed the effect of implementing maternal and newborn health (MNH) quality of care standards on RMC measures. Methods We used a facility-based controlled before and after design in 43 healthcare facilities in Bangladesh, Ghana and Tanzania. Interviews with women and health workers and observations of labour and childbirth were used for data collection. We estimated difference-in differences to compare changes in RMC measures over time between groups. Results 1827women and 818 health workers were interviewed, and 1512 observations were performed. In Bangladesh, MNH quality of care standards reduced physical abuse (DiD −5.2;−9.0 to –1.4). The standards increased RMC training (DiD 59.0; 33.4 to 84.6) and the availability of policies and procedures for both addressing patient concerns (DiD 46.0; 4.7 to 87.4) and identifying/ reporting abuse (DiD 45.9; 19.9 to 71.8). The control facilities showed greater improvements in communicating the delivery plan (DiD −33.8; –62.9 to –4.6). Other measures improved in both groups, except for satisfaction with hygiene. In Ghana, the intervention improved women’s experiences. Providers allowed women to ask questions and express concerns (DiD 37.5; 5.9 to 69.0), considered concerns (DiD 14.9; 4.9 to 24.9), reduced verbal abuse (DiD −8.0; −12.1 to –3.8) and physical abuse (DiD −5.2; −11.4 to –0.9). More women reported they would choose the facility for another delivery (DiD 17.5; 5.5 to 29.4). In Tanzania, women in the intervention facilities reported improvements in privacy (DiD 24.2; 0.2 to 48.3). No other significant differences were observed due to improvements in both groups. Conclusion Institutionalising care standards and creating an enabling environment for quality MNH care is feasible in low and middle-income countries and may facilitate the adoption of RMC.

Source: UG
Implementing Nutrition Interventions In Ghana At District Level: Gaps And Opportunities

Malnutrition among women and children is an underlying cause of high morbidity and mortality in the developing world. Ghana is one of 36 countries with a high prevalence (> 20%) of chronic stunting in childhood. Although proven and inexpensive technologies and interventions exist to address maternal and child malnutrition, their implementation remains at a low scale in many developing countries, including Ghana. In Ghana, barriers to scaling up nutrition actions have been identified at the national level, yet little is known about the situation at the district and sub-district levels where nutrition interventions are directly delivered. The current study assessed district-level capacity and commitment to accelerating the implementation of effective nutrition interventions to address the high burden of maternal and child malnutrition. In June 2010, key informant interviews involving technical officers, clinicians, nurses, and administrative staff, and a desk review of program and administrative reports were conducted in the Omanye District (pseudonym). Using the framework from the WHO landscape analysis of readiness to scale up nutrition actions, interviews explored questions of commitment (financial, planning, collaborations) and capacity (human resources, job aids, skills) to implement nutrition actions in the district. Most key nutrition interventions were being implemented in the Omanye District including growth promotion, micronutrient supplementation, behavior change communication on infant and young child feeding, and a pilot project for community management of severe acute malnutrition. Interventions are challenged, however, by barriers including inadequate financial commitment, low prioritization of nutrition, inadequate personnel, and insufficient job aids. Because nutrition was relatively underfunded in the district, nutrition technical officers had been shifted to perform other or additional tasks. Insufficient investment and inadequate capacity prevent the delivery of quality nutrition services in the Omanye District. Interventions that prioritize and improve investment in nutrition actions are needed to optimize nutrition services at the district level in Ghana.

Source: UG
Implication of Oil Exploration on Livelihood of Residents Around oil Rig Environs and Assessment of oil Exploration Policies: A Case of the Ghana Jubilee Oil

The focus of this paper is to explore and analyze the influence of oil exploration on community livelihoods and to assess oil exploration policies in Ghana. The study was undertaken in two communities (Half Assini and Efaso) in the Jomoro District of the Western region. The study employed purposive sampling of residents living in the Jubilee Oil field environs. After, simple random sampling was used to select 300 respondents from the study area out of a population of about 5000 to 10,000. Community livelihoods considered for this study include household income, education, nutrition and health. The likert type attitudinal question: ‘improving, no change and declining’ in a particular livelihood outcome was used. Results from the multinomial logistic estimation model revealed that the likelihood of the influence of development interventions was negatively and significantly related with respondents’ perception of household income, nutrition and education. That of household health was positive and not significant. Policies on oil exploration are found in the Environment Protection Agency Act of 1994 (Act 490) and the Environmental Assessment Regulations Act of 1999.

Source: UG
The Implications Of Climate Change And Extreme Weather Events For Fiscal Balance And Fiscal Policy In Africa

African countries quite often experience weather-related events as a result of climate variability. In this study, we investigate the effects of climate change and the incidence of extreme weather events on fscal balance and the broad implications for fscal policy formulation in Africa. We employ the system GMM, fixed-efects and random-efects estimation strategies over the period 1990–2017. We find that increases in temperature change anomaly which implies a warmer climate in a meteorological year worsens fscal balance in Africa. Our fndings also reveal that weather-related events may have a signifcant impact on fscal balance, if the damage caused is large and consequential. Furthermore, African countries with relatively strong institutions and adaptive capacities tend to modulate the impact of temperature change anomaly and extreme weather events on fscal balance. We forecast that the frequent incidence of climatic disruptions and extreme weather events which are considered as external shocks may toughen the fscal consolidation eforts and debt sustainability measures of some African governments.

Source: UG
Implications of Climate Change for Ghana’s Economy

Long-run economic development in Ghana is potentially vulnerable to anthropogenic climate change given the country’s dependence on rain-fed agriculture, hydropower and unpaved rural roads. We use a computable general equilibrium model, informed by detailed sector studies, to estimate the economy-wide impacts of climate change under four climate projections. Climate change is found to always reduce national welfare, with poor and urban households and the northern Savannah zone being the worst affected. However, there is wide variation across scenarios in the size of climate impacts and in the relative importance of sectoral impact channels, thus underscoring the need for multi-sector approaches that account for climate uncertainty. Our analysis of adaptation options indicates that investing in agricultural research and extension, and improved road surfaces, are potentially cost-effective means of mitigating most of the damages from climate change in Ghana

Source: UG
Implications of climate change for Ghana's economy

Long-run economic development in Ghana is potentially vulnerable to anthropogenic climate change given the country's dependence on rain-fed agriculture, hydropower and unpaved rural roads. We use a computable general equilibrium model, informed by detailed sector studies, to estimate the economy-wide impacts of climate change under four climate projections. Climate change is found to always reduce national welfare, with poor and urban households and the northern Savannah zone being the worst affected. However, there is wide variation across scenarios in the size of climate impacts and in the relative importance of sectoral impact channels, thus underscoring the need for multi-sector approaches that account for climate uncertainty. Our analysis of adaptation options indicates that investing in agricultural research and extension, and improved road surfaces, are potentially cost-effective means of mitigating most of the damages from climate change in Ghana. © 2015 by the authors; licensee MDPI, Basel, Switzerland.

Source: UG
Implications of COVID-19 Innovations for Social Interaction: Provisional Insights From a Qualitative Study of Ghanaian Christian Leaders

Responses to the COVID-19 pandemic prompted people and institutions to turn to online virtual environments for a wide variety of social gatherings. In this perspectives article, we draw upon our previous work and interviews with Ghanaian Christian leaders to consider implications of this shift. Specifically, we propose that the shift from physical to virtual interactions mimic and amplify the neoliberal individualist experience of abstraction from place associated with Eurocentric modernity. On the positive side, the shift from physical and virtual environments liberates people to selectively pursue the most fulfilling interactions, free from constraints of physical distance. On the negative side, the move from physical to virtual space necessitates a shift from material care to tangible engagement with the local community to the psychologization of care and pursuit of emotional intimacy in relations of one’s choosing—a dynamic that further marginalizes people who are already on the margins. The disruptions of the pandemic provide an opportunity to re-set social relations and to design ways of being that better promote sustainable collective well-being rather than fleeting personal fulfillment.

Source: UG
Implications of crop yield distributions for multiperil crop insurance rating in Ghana: a lasso model application

Purpose – The objective of this paper is to examine crop yield predictions and their implications on MPCI in Ghana. Farmers in developing countries struggle with their ability to deal with agricultural risks. Providing aid for farmers and their households remains instrumental in combatting poverty in Africa. Several studies have shown that correctly understanding and implementing risk management strategies will help in the poverty alleviation agenda. Design/methodology/approach – This study examines the importance of crop yield distributions in Ghana and its implication on multiperil crop insurance (MPCI) rating using the Lasso regression model. A Bonferroni test was employed to test the independence of crop yields across the regions while the Kruskal-Wallis H test was conducted to examine statistical differences in mean yields of crops across the ten regions. The Bayesian information criteria and k-fold cross-validation methods are used to select an appropriate Lasso regression model for the prediction of crop yields. The study focuses on the variability of the threshold yields across regions based on the chosen model. Findings – It is revealed that threshold yields differ significantly across the regions in the country. This implies that the payment of claims will not be evenly distributed across the regions, and hence regional disparities need to be considered when pricing MPCI products. In other words, policymakers may choose to assign respective weights across regions based on their threshold yields. Research limitations/implications – The primary limitation is the unavailability of regional climate data which could have helped in a better explanation of the variation across the regions. Originality/value – This is the first study to examine the implications of regional crop yield variations on multiperil crop insurance rating in Ghana.

Source: UG
Implications of legalisation of cannabis cultivation in Ghana: a critical review

Purpose – Following the trend in the world over and on the African continent, the Parliament of Ghana passed a new law in 2020, the Narcotics Control Commission Act (Act 1019) that eased the legal restrictions on cannabis cultivation and use, subject to obtaining license from the relevant authority/ authorities. This paper aims to examine the implications of Ghana’s decision to legalise the cultivation of cannabis for industrial purposes for the production of fibre and for medicinal purposes. Design/methodology/approach – The author adopted the qualitative analysis critical review methodology in sourcing information from peer-reviewed articles, coupled with the author’s own professional knowledge, background and training, to critically analyse and review the reasons behind Ghana’s decision to legalise cannabis cultivation and the implications such a major policy change/shift. Findings – It was found that, while the law mentions industrial and medicinal purposes for the legalisation of cannabis, the real reason, at least in the immediate term, is mainly economic. This agrees with those of other African countries that have legalised cannabis cultivation but appears to contrast with those of Europe and America. Research limitations/implications – This research is limited to Ghana and the few African countries that have legalised cannabis cultivation so far. The main reason for the legalisation (economic benefits) may also change in the future when the economics of scale turn in the favour of the country. Therefore, Ghana’s case may not represent the case of all countries legalising cannabis cultivation. Practical implications – The research implication of this paper is that it brings to the world the law on cannabis cultivation in Ghana. It provides a professional and scientific position paper on Ghana’s drug law regime regarding cannabis, thus, serving as a useful reference literature to the academic and research community on the topic. More importantly, it discusses the implications of such major policy change from an objective perspective, unravelling the real reason behind the State’s decision to legalise the cultivation of cannabis in Ghana. Social implications – This paper will bring to the fore the other consequences of Ghana’s cannabis cultivation legalisation policy change, which little attention has been devoted to so far. Originality/value – This paper, apart from reference to other published texts on the topic, which have been duly acknowledged, represents the sole work of the author. It has not been produced anywhere or by anyone else either in Ghana or elsewhere

Source: UG