Determinants of Enrolment and Renewing of Community-Based Health Insurance in Households With Under-5 Children in Rural South-Western Uganda

Background: The desire for universal health coverage in developing countries has brought attention to community-based health insurance (CBHI) schemes in developing countries. The government of Uganda is currently debating policy for the national health insurance programme, targeting the integration of existing CBHI schemes into a larger national risk pool. However, while enrolment has been largely studied in other countries, it remains a generally under-covered issue from a Ugandan perspective. Using a large CBHI scheme, this study, therefore, aims at shedding more light on the determinants of households’ decisions to enrol and renew membership in these schemes. Methods: We collected household data from 464 households in 14 villages served by a large CBHI scheme in south-western Uganda. We then estimated logistic and zero-inflated negative binomial (ZINB) regressions to understand the determinants of enrolment and renewing membership in CBHI, respectively.Results: Results revealed that household’s socioeconomic status, husband’s employment in rural casual work (odds ratio [OR]: 2.581, CI: 1.104-6.032) and knowledge of health insurance premiums (OR: 17.072, CI: 7.027-41.477) were significant predictors of enrolment. Social capital and connectivity, assessed by the number of voluntary groups a household belonged to, was also positively associated with CBHI participation (OR: 5.664, CI: 2.927-10.963). More positive perceptions on insurance (OR: 2.991, CI: 1.273-7.029), access to information were also associated with enrolment and renewing among others. Burial group size and number of burial groups in a village, were all significantly associated with increased the likelihood of renewing CBHI. Conclusion: While socioeconomic factors remain important predictors of participation in insurance, mechanisms to promote inclusion should be devised. Improving the participation of communities can enhance trust in insurance and eventual coverage. Moreover, for households already insured, access to correct information and strengthening their social network information pathways enhances their chances of renewing

Assessment of rainfall and climate change patterns via machine learning tools and impact on forecasting in the City of Kigali

Rainfall is changing in intensity and abundance for much of the world as a result of global climate change. Rwanda has been negatively affected by a changing climate, exacerbated by human impact on land and water resources. In most parts of the country, the rainfall pattern has changed over the last decades resulting in both enhanced flooding and water shortage/scarcity in much of the country, especially in the Capital City of Kigali and peripheries which is the main economic hub of the country with strong links to the East African region. Changes in precipitation have affected agricultural production, hydropower production, and water supplies, and has been a result of increased flash floods in the city. This study developed a new predictive model of rainfall patterns in the City of Kigali (CoK) in the Republic of Rwanda using evolutionary methodologies that apply machine learning techniques of Fuzzy Inference Systems (FIS) trained via Genetic Algorithms, Neuro Network Systems and a comparative Support Vector Machine tool, and assessment downscaled climate change combinations with predicted rainfall patterns. The models were calibrated and validated using measured rainfall data in the City of Kigali from 1991 through 2023. The model results show the developed Geno Fuzzy Inference System (GENOFIS) model performed better than the Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM) models. The Coefficient of Efficiency (CE), and Root Mean Square Error (RMSE) were used as diagnostic measures for model performance evaluation. Models generated with GENOFIS are therefore recommended for rainfall and related prediction patterns in the City of Kigali for climate change adaptation and resilience policy and planning

Landslides, soil moisture, and land use changes in the mountainous Northern-western provinces of Rwanda: field-based research in a tropical environment

Landslide and flood hazards and vulnerability in NW Rwanda: towards applicable land management and disaster risk reduction (LAFHAZAV

Rainfall - Soil moisture response in relation to land use in steep tropical enviroments: field-based research in NW-Rwanda

Landslide and flood hazards and vulnerability in NW Rwanda: towards applicable land management and disaster risk reduction (LAFHAZAV

Adoption and impacts of agricultural technologies and sustainable natural resource management practices in fragile and conflict affected settings: A review and meta-analysis

Climate change and conflicts co-exist in many countries with significant welfare and socio-environmental implications. Different approaches are being promoted to adapt and build resilience to these fragilities including the adoption of sustainable farm practices that have the potential to increase agricultural productivity and maintain environmental sustainability. We undertake a systematic review and perform a meta-analysis to understand and synthesize the adoption and impacts of agricultural technologies and natural resource management practices with a special attention to fragile and conflict affected settings. We employ state of the art machine learning methods to enable process and selection of appropriate papers from a universe of over 78,000 papers from leading academic databases. We find that studies on adoption and impact of agricultural technologies and natural resource management practices are highly clustered around Ethiopia and Nigeria. We do not find any studies on Small Island States. We observe a wide array of characteristics that influence adoption of these technologies. Of the over 1400 estimates of determinants collected, majority predict input technologies while very few studies and estimates are found in relation to risk management and mechanisation technologies. Our meta-analysis shows an average effect size of 7 - 9% for the different technologies and practices. For the outcomes: land productivity, food security and household welfare, we obtain effect sizes of 6, 8 and 9% respectively. We do not observe much in terms of publication bias. Both climate and conflict vulnerability not only cause far more food insecurity, poverty, and degradation of the environment on their own but also reinforce each other through the climate change – conflict linkage. For these detrimental effects to be curtailed, utilisation of climate-smart agricultural technologies and natural resource management practices need to be encouraged. We thus lend credence to the development, dissemination and upscaling of these sustainable practices. We observe a lot of space for growth and adoption of these technologies

Independent and combined effects of improved water, sanitation, and hygiene, and improved complementary feeding, on child stunting and anaemia in rural Zimbabwe: a cluster-randomised trial.

BACKGROUND: Child stunting reduces survival and impairs neurodevelopment. We tested the independent and combined effects of improved water, sanitation, and hygiene (WASH), and improved infant and young child feeding (IYCF) on stunting and anaemia in in Zimbabwe. METHODS: We did a cluster-randomised, community-based, 2 × 2 factorial trial in two rural districts in Zimbabwe. Clusters were defined as the catchment area of between one and four village health workers employed by the Zimbabwe Ministry of Health and Child Care. Women were eligible for inclusion if they permanently lived in clusters and were confirmed pregnant. Clusters were randomly assigned (1:1:1:1) to standard of care (52 clusters), IYCF (20 g of a small-quantity lipid-based nutrient supplement per day from age 6 to 18 months plus complementary feeding counselling; 53 clusters), WASH (construction of a ventilated improved pit latrine, provision of two handwashing stations, liquid soap, chlorine, and play space plus hygiene counselling; 53 clusters), or IYCF plus WASH (53 clusters). A constrained randomisation technique was used to achieve balance across the groups for 14 variables related to geography, demography, water access, and community-level sanitation coverage. Masking of participants and fieldworkers was not possible. The primary outcomes were infant length-for-age Z score and haemoglobin concentrations at 18 months of age among children born to mothers who were HIV negative during pregnancy. These outcomes were analysed in the intention-to-treat population. We estimated the effects of the interventions by comparing the two IYCF groups with the two non-IYCF groups and the two WASH groups with the two non-WASH groups, except for outcomes that had an important statistical interaction between the interventions. This trial is registered with ClinicalTrials.gov, number NCT01824940. FINDINGS: Between Nov 22, 2012, and March 27, 2015, 5280 pregnant women were enrolled from 211 clusters. 3686 children born to HIV-negative mothers were assessed at age 18 months (884 in the standard of care group from 52 clusters, 893 in the IYCF group from 53 clusters, 918 in the WASH group from 53 clusters, and 991 in the IYCF plus WASH group from 51 clusters). In the IYCF intervention groups, the mean length-for-age Z score was 0·16 (95% CI 0·08-0·23) higher and the mean haemoglobin concentration was 2·03 g/L (1·28-2·79) higher than those in the non-IYCF intervention groups. The IYCF intervention reduced the number of stunted children from 620 (35%) of 1792 to 514 (27%) of 1879, and the number of children with anaemia from 245 (13·9%) of 1759 to 193 (10·5%) of 1845. The WASH intervention had no effect on either primary outcome. Neither intervention reduced the prevalence of diarrhoea at 12 or 18 months. No trial-related serious adverse events, and only three trial-related adverse events, were reported. INTERPRETATION: Household-level elementary WASH interventions implemented in rural areas in low-income countries are unlikely to reduce stunting or anaemia and might not reduce diarrhoea. Implementation of these WASH interventions in combination with IYCF interventions is unlikely to reduce stunting or anaemia more than implementation of IYCF alone. FUNDING: Bill & Melinda Gates Foundation, UK Department for International Development, Wellcome Trust, Swiss Development Cooperation, UNICEF, and US National Institutes of Health.The SHINE trial is funded by the Bill & Melinda Gates Foundation (OPP1021542 and OPP113707); UK Department for International Development; Wellcome Trust, UK (093768/Z/10/Z, 108065/Z/15/Z and 203905/Z/16/Z); Swiss Agency for Development and Cooperation; US National Institutes of Health (2R01HD060338-06); and UNICEF (PCA-2017-0002)

Adoption and impacts of agricultural technologies and sustainable natural resource management practices in fragile and conflict affected settings: A review and meta-analysis

Climate change and conflicts co-exist in many countries with significant welfare and socio-environmental implications. Different approaches are being promoted to adapt and build resilience to these fragilities including the adoption of sustainable farm practices that have the potential to increase agricultural productivity and maintain environmental sustainability. We undertake a systematic review and perform a meta-analysis to understand and synthesize the adoption and impacts of agricultural technologies and natural resource management practices with a special attention to fragile and conflict affected settings. We employ state of the art machine learning methods to enable process and selection of appropriate papers from a universe of over 78,000 papers from leading academic databases. We find that studies on adoption and impact of agricultural technologies and natural resource management practices are highly clustered around Ethiopia and Nigeria. We do not find any studies on Small Island States. We observe a wide array of characteristics that influence adoption of these technologies. Of the over 1400 estimates of determinants collected, majority predict input technologies while very few studies and estimates are found in relation to risk management and mechanisation technologies. Our meta-analysis shows an average effect size of 7 - 9% for the different technologies and practices. For the outcomes: land productivity, food security and household welfare, we obtain effect sizes of 6, 8 and 9% respectively. We do not observe much in terms of publication bias. Both climate and conflict vulnerability not only cause far more food insecurity, poverty, and degradation of the environment on their own but also reinforce each other through the climate change – conflict linkage. For these detrimental effects to be curtailed, utilisation of climate-smart agricultural technologies and natural resource management practices need to be encouraged. We thus lend credence to the development, dissemination and upscaling of these sustainable practices. We observe a lot of space for growth and adoption of these technologies.Non-PR1 Fostering Climate-Resilient and Sustainable Food Supply; 4 Transforming Agricultural and Rural Economies; 3 Building Inclusive and Efficient Markets, Trade Systems, and Food Industry; IFPRI1Development Strategies and Governance (DSG); Transformation Strategie

Understanding the impact of polymer functionalized electrode fabrication and cycling conditions on stability and selective separation of micropollutants

The main focus of this thesis is on selectively separating target contaminants present in an aqueous environment via electrochemically-mediated capture at polymer interfaces in order to improve water security. Heavy metal pollutants such as arsenic have diverse physico-chemical properties which renders them intractable in current treatment technologies such as wastewater treatment plants (WWTPs). These pollutants are able to pass through WWTPs and end up in the aquatic environment becoming a threat to ecosystems or end up in drinking water. Electrochemically mediated selective capture of the heavy metal pollutants is a promising technology but current methods lack molecular selectivity are unstable and have difficulty separating the target ion without producing toxic byproducts. Polymer coated electrodes comprised of poly(vinyl) ferrocne (PVF) and 3-ferrocenylpropyl acrylamide (PFPMAm) have been developed to selectively separate arsenic due to their electronic tunability, fast electron transfer, redox processes at moderate potentials below that of water splitting, and molecular level recognition of target pollutants of concern. Properties of the resulting redox polymer electrode were also investigated using various analytical instruments.LimitedAuthor requested closed access (OA after 2yrs) in Vireo ETD syste

Dominant Influencing Factors of Groundwater Recharge Spatial Patterns in Ergene River Catchment, Turkey

Groundwater is of great significance in sustaining life on planet earth. The reliable estimation of groundwater recharge is the key understanding the groundwater reservoir and forecasting its potential accessibility. The main objective of this study was to assess the groundwater recharge and its controlling factors at the Ergene river catchment. A grid-based water balance model was adopted to determine the spatially distributed long-term groundwater recharge and other water budget components, relying upon the hydro-climatic variables, land-use, soil, geology, and relief of the investigated area. The model calculations were performed for the hydrological reference horizon of 20 years at a spatial resolution of 100 × 100 m. The base flow index (BFI) separation concept was applied to split up the simulated total runoff into groundwater recharge and direct runoff. Subsequently, the statistical methods of Pearson product–moment correlation and principal component analysis (PCA) were combined for identifying the dominant catchment and meteorological factors influencing the recharge. The average groundwater recharge over the investigated area amounts to 95 mm/year. The model validation and statistical analysis indicate that the difference between simulated and observed total runoff and recharge values is generally under 20% and no significant inconsistency was observed. PCA indicated that recharge is controlled, in order of significance, by land-use, soil, and climate variables. The findings of this research highlight the key role of spatial variables in recharge determination. In addition, the generated outputs may contribute to groundwater resource management in the Ergene river catchment

The Impact of Social Assistance Programmes in a Pandemic: Evidence from Kenya

This paper examines whether social protection – in the form of existing social assistance programmes - affects measures of household well-being such as poverty, food security and costly risk-coping behaviour during the COVID-19 pandemic. Using primary data from nationally representative, in-person surveys in Kenya allows the exploration of the impacts of major social assistance programmes. Our analysis employs the doubly robust difference-in-differences approach to estimate the impacts of social assistance programmes on common measures of household welfare. We find that social assistance programmes significantly reduce the prevalence of economic shocks and the further impoverishment of beneficiaries during the pandemic. Furthermore, households with social assistance coverage are less likely to sell assets as a coping strategy. Overall, the results suggest that, during a systematic crisis such as a pandemic, pre-existing social assistance schemes can deliver positive impacts in line with the primary goals of social safety nets and prevent households from falling deeper into poverty by preserving their asset base