Geostatistical Model-Based Estimates of Schistosomiasis Prevalence among Individuals Aged ≤20 Years in West Africa

Schistosomiasis is a parasitic disease caused by a blood fluke that mainly occurs in Africa. Current prevalence estimates of schistosomiasis are based on historical data, and hence might be outdated due to control programs, improved sanitation, and water resources development and management (e.g., construction of large dams and irrigation systems). To help planning, coordination, and evaluation of control activities, reliable schistosomiasis prevalence estimates are needed. We analyzed compiled survey data from 1980 onwards for West Africa, including Cameroon, focusing on individuals aged ≤20 years. Bayesian geostatistical models were implemented based on environmental and climatic predictors to take into account potential spatial clustering within the data. We created the first smooth data-driven prevalence maps for Schistosoma mansoni and S. haematobium at high spatial resolution throughout West Africa. We found that an estimated 50.8 million West Africans aged ≤20 years are infected with schistosome blood flukes. Country prevalence estimates ranged between 0.5% (in The Gambia) and 37.1% (in Liberia) for S. mansoni and between 17.6% (in The Gambia) and 51.6% (in Sierra Leone) for S. haematobium. Our results allow prioritization of areas where interventions are needed, and to monitor and evaluate the impact of control activities

On a universal model for the prediction of the daily global solar radiation

A model to predict the mean expected daily global solar radiation, H(n) on a day n, at a site with latitude φ is proposed. The model is based on two cosine functions. A regression analysis taking into account the mean measured values Hm.meas(n) obtained from SoDa database for 42 sites in the Northern Hemisphere resulted in a set of mathematical expressions of split form to predict H(n). The parameters of the two cosine model for 0o<φ<23o are obtained by regression analysis using a sum of 3-8 Gaussian functions, while for 23o<φ<71o the two cosine model parameters are expressed by a sum of exponential functions or the product of an exponential and a cosine function. The main equation of the model and the set of parametric expressions provide H(n) for any φ on Earth. Validation results of this model are provided along with the statistical estimators NMBE, NRMSE and t-statistic in comparison to the corresponding values from three databases of NASA, SoDa and the measured values from ground stations provided in Meteonorm

A combined model for PV system lifetime energy prediction and annual energy assessment

This paper presents a generic model for the prediction of the lifetime energy production of photovoltaic (PV) systems and the assessment of their annual energy yield in different time periods of operation. As case studies, it considers domestic PV system generation potentials in the UK and India to demonstrate the model results across a range of contrasting climatic and operating conditions. The model combines long-term averages of solar data, a commercial PV system simulation package and a probability density function to express the range of the annual energy prediction in different time periods of system operation. Moreover, a sensitivity analysis based on degradation rates and energy output uncertainties is embedded in the lifetime energy calculations. The importance of the reliability and maintenance of the PV systems and the energy prediction risks, especially regarding economic viability, are demonstrated through the PV lifetime energy potentials in these two countries. It is shown that, even for countries that are significantly different in respect to their solar resource, PV systems may produce similar amounts of energy during their lifetime for reasonable assumptions of degradation rates and uncertainty levels

Developing a framework to increase Solar Photovoltaic (Solar PV) microgrid penetration in a tropical region: A case study in Indonesia

Although tropical regions receive a significant amount of solar radiation throughout the year, most tropical countries have low solar photovoltaic (PV) penetration. Indonesia has around 208 gigawatts of solar potential but less than one percent of this potential has been harnessed. This research combined both quantitative and qualitative research to develop a framework for increasing solar PV microgrid penetration in Indonesia. A techno-economic evaluation was performed to identify the performance of a solar PV microgrid in Indonesia and to evaluate its economic potential based on two different land acquisition scenarios. Additionally, surveys and interviews were conducted to obtain some perspectives from key stakeholders regarding the policy landscape of the country. The study shows that although high solar radiation is great to produce higher power, the performance ratio can be quite low. The economic evaluation shows that the land purchasing scenario can give a higher profit while the land leasing scenario can provide a quick return. This study also found out that the declining investment costs and the presence of a Power Purchase Agreement are the drivers for the development of solar PV microgrid in the countries. In contrast, the unstable grid connection and the insufficient technical knowledge are some barriers to this development. The development of solar PV microgrid in Indonesia is a complex issue because of a complex relationship between different technical, financial, social and regulatory aspects. The financial aspect, particularly the presence of a solar PV market, has been seen as the top priority to be resolved in the country. After determining the priority, a framework for successful implementation of solar PV microgrid in Indonesia is being developed. The developed framework has four stages in which each key stakeholder has different roles in each stage. Successful implementation of the framework can increase solar PV microgrid penetration in Indonesia

Climate for development in Africa (ClimDev) – climate sciences and services for Africa. Strategic research opportunities for ClimDev-Africa

The purpose of this report is to present the ClimDev Partnership with a much narrower set of strategic research options by which ACPC and AfDB in particular could establish a unique presence in the realm of climate research and resilience planning. As a result, hitherto under-represented sectors and regions would be better equipped to manage risks as well as maximise development opportunities presented by climate variability and change. A gap analysis was undertaken using different sources of evidence drawn from bibliographic metrics, previous research prioritisation exercises, peer-reviewed and grey literature, meta-analysis of web-based material, conference proceedings, ClimDev reports and proposal short-listing, an inventory of climate data requests, case studies and consultations with African experts. Six research opportunities are proposed for consideration by ClimDev

An integrated molecular and conventional breeding scheme for enhancing genetic gain in maize in Africa

Open Access Journal; Published online: 06 Nov 2019Maize production in West and Central Africa (WCA) is constrained by a wide range of interacting stresses that keep productivity below potential yields. Among the many problems afflicting maize production in WCA, drought, foliar diseases, and parasitic weeds are the most critical. Several decades of efforts devoted to the genetic improvement of maize have resulted in remarkable genetic gain, leading to increased yields of maize on farmers’ fields. The revolution unfolding in the areas of genomics, bioinformatics, and phenomics is generating innovative tools, resources, and technologies for transforming crop breeding programs. It is envisaged that such tools will be integrated within maize breeding programs, thereby advancing these programs and addressing current and future challenges. Accordingly, the maize improvement program within International Institute of Tropical Agriculture (IITA) is undergoing a process of modernization through the introduction of innovative tools and new schemes that are expected to enhance genetic gains and impact on smallholder farmers in the region. Genomic tools enable genetic dissections of complex traits and promote an understanding of the physiological basis of key agronomic and nutritional quality traits. Marker-aided selection and genome-wide selection schemes are being implemented to accelerate genetic gain relating to yield, resilience, and nutritional quality. Therefore, strategies that effectively combine genotypic information with data from field phenotyping and laboratory-based analysis are currently being optimized. Molecular breeding, guided by methodically defined product profiles tailored to different agroecological zones and conditions of climate change, supported by state-of-the-art decision-making tools, is pivotal for the advancement of modern, genomics-aided maize improvement programs. Accelerated genetic gain, in turn, catalyzes a faster variety replacement rate. It is critical to forge and strengthen partnerships for enhancing the impacts of breeding products on farmers’ livelihood. IITA has well-established channels for delivering its research products/technologies to partner organizations for further testing, multiplication, and dissemination across various countries within the subregion. Capacity building of national agricultural research system (NARS) will facilitate the smooth transfer of technologies and best practices from IITA and its partners

Scaling up climate services for farmers: Mission Possible. Learning from good practice in Africa and South Asia

This report presents lessons learned from 18 case studies across Africa and South Asia that have developed and delivered weather and climate information and related advisory services for smallholder farmers. The case studies and resulting lessons provide insights on what will be needed to build effective national systems for the production, delivery, communication and evaluation of operational climate services for smallholder farmers across the developing world. The case studies include two national-scale programmes that have been the subject of recent assessments: India’s Integrated Agrometeorological Advisory Service (AAS) Program, which provides tailored weather-based agrometeorological advisories to millions of farmers; and Mali’s Projet d’Assistance Agro-meteorologique au Monde Rural, which provided innovative seasonal agrometeorological advisory services for smallholder farmers and 16 less mature initiatives operating at a pilot scale across Africa and South Asia. The case studies were examined from the standpoint of how they address five key challenges for scaling up effective climate services for farmers: salience, access, legitimacy, equity and integration

Infectious Etiologies of Febrile Illnesses in Cameron.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Spatio-temporal modelling of under-five mortality and associations with malaria-anaemia comorbidity and health interventions in sub-Saharan Africa

A remarkable reduction of the total number of under-five deaths was achieved between 1990 and 2018 in the African setting, as pre-school mortality fell to 5.3 million deaths compared to 12.5 million in 1990. The bulk share of this reduction is attributed to the Millennium Development Goals (MDGs) era, during which time the under-five mortality rate has been declining with an annual rate of 3.8% across Africa. Despite these important achievements, the sub-Sahara African region did not meet the fourth target of the MDGs and still has an unacceptably high under-five mortality rate. Crucially, limiting the under-five mortality rate to a maximum of 25 deaths per 1,000 live births by 2030 lies at the heart of the Sustainable Development Goals (SDGs) and a recent report from the United Nations has warned that based on current trends, the African continent will not meet the SDG target for under-five mortality. Hence, providing useful insights from the associations between under-five mortality, the leading causes of disease and preventative or curative health interventions could make available valuable information to decision makers in order the African countries to achieve the SDGs on pre-school mortality. Malaria is a major contributor to under-five mortality in sub-Saharan Africa, accounting for 400,000 deaths, approximately 60% of which are in children below the age of five. At global scale, the disability-adjusted life-years for the malaria disease are 45 million. An important aspect of the disease is that infection by malaria parasites does not necessarily lead to mortality and it is rather conditions that follow infection or other comorbidities that produce severe forms of the disease with increased mortality risk. Apart from malaria, pneumonia and diarrhea account for the most frequent causes of pre-school deaths. An interesting feature of all these three leading causes of under-fives in Africa, i.e. pneumonia, diarrhea and malaria, is that they share febrile response as their main clinical manifestation. Against the leading causes of under-five mortality, preventative or curative health interventions have been widely adopted in Africa, with their spatial coverage being on a significant rise, particularly due to the so-called scaling-up of health interventions during the last five years of the MDGs. For instance, ownership of Insecticide-Treated nets against malaria rose from 50 to 80 percent between 2010 and 2015, while their utilization averted 663 million clinical malaria cases over the MDGs era. Yet, the coverage of health interventions and the subsequent reduction in under-five deaths has happened in an unequal way across sub- Saharan Africa, raising concerns about health inequities at sub-national level. The overall aim of the present PhD thesis is to develop, implement and interpret Bayesian geostatistical models with spatially varying coefficients in order to analyze approximately one million, cross-sectional mortality related-data in Africa and associate under-five mortality with malaria and health interventions. The point-by-point objectives of our work are as follows: 1. To develop a novel indicator for quantifying malaria-related mortality for children under the age of five in sub-Saharan Africa, namely the malaria-anemia comorbidity prevalence indicator (chapter 2); 2. To identify health inequities experienced by sub-national populations due to the geographical variation in the association between curative or preventive health interventions and under-five mortality in sub-Saharan Africa (chapter 3); 3. To assess the contribution of the leading causes of under-five mortality in sub- Saharan Africa on febrile response by associating the prevalence of malaria parasitaemia, diarrhoea and ARI with fever. (chapter 4); 4. To estimate the association between health interventions and under-five mortality on changes in mortality risk between two time points across Africa (chapter 5); 5. To compare Bayesian variable selection methods for spatially varying coefficient models, given that these approaches are at the forefront of analyzing geolocated mortality data in Africa (chapter 6). In chapter 2, we estimated the association of malaria parasitaemia, anemia, and malaria- anemia comorbidity with all-cause under-five mortality and evaluated the potential of malaria-anemia comorbidity prevalence to quantify malaria-related deaths in sub-Saharan Africa. Additionally, we estimated within-country variation of the association between comorbidity and under-5 mortality, using spatially varying coefficient models. We presented our results at high spatial resolution, including model-based risk maps of malaria, anemia, and malaria-anemia comorbidity. In chapter 3, we modeled the geographical variation in the association between health interventions and all-cause, under-five mortality in order to identify health inequities experienced by sub-national populations within a given country. To achieve that, we developed Bayesian geostatistical Weibull survival models with spatially varying coefficients for the effect of health interventions on mortality. Our approach allowed us to calculate the number of statistically important associations between interventions and mortality at regional level and hence to assess if health equity of interventions exists across the regions of a given country. In chapter 4, we assessed the contribution of the leading causes of under-five mortality in sub-Saharan Africa on febrile response by associating the prevalence of malaria parasitaemia, diarrhoea and ARI with fever. Our flexible Bayesian spatial modelling approach allowed evaluating the geographical distribution of disease-exposure effect on fever in space (Administrative level 1). We also calculated the Potential Attributable Fraction (PAF) in order to quantify the contribution of childhood diseases on fever. In chapter 5, we developed a novel methodology to statistically model the effect of health interventions on the changes in under-five mortality risk between two DHS survey time-points for 21 countries in Africa. We used a Bayesian geostatistical Weibull survival modeling approach and implemented rigorous Bayesian variable selection procedures in order to identify the most suitable set of health interventions for subsequent model fit. In chapter 6, we assessed the performance of stochastic search variable selection (SSVS) for the fixed effects of geostatistical models, we compared three different Bayesian variable selection (BVS) methods for conditionally autoregressive (CAR) structured spatially varying coefficient models and finally we assessed the sensitivity of SSVS for the fixed effects when is co-implemented with a BVS procedure. We conducted a simulation study and applied the methods to the Burundi DHS in order to assess the aforementioned selection procedures. The present PhD thesis has contributed to the scientific fields of Epidemiology and Statistics by committing to the spatio-temporal modelling of under-five mortality data in the African setting, using primarily routinely collected, cross-sectional, household-based survey data coming from the Demographic and Health surveys program. The key outcomes of the research conducted in this thesis are as follows: 1. Our work contributed to the development, proposal and validation of a novel indicator for quantifying malaria-mortality using survey data, i.e. the malaria-anemia comorbidity indicator. Our main conclusions were that malaria burden in sub-Saharan Africa is considerably underestimated when anemia in not taken into account and that the malaria-anemia comorbidity prevalence provides a useful measure of the malaria-related deaths; 2. We presented the first study to assess sub-national health inequities, across most countries in Africa, by employing a spatial statistical modelling approach and routinely collected survey data coming from the DHS and MIS. Our results demonstrated strong sub-national health inequities across various regions for 28 African countries; 3. Our estimates confirmed the strong contribution of diarrhoea and acute respiratory infection on febrile response and accounted only one out of five cases to malaria; 4. Our work concluded that the health interventions that are mostly associated with changes in all-cause, under-five mortality risk in sub-Saharan Africa were Bacillus Calmette–Guérin (BCG) immunization, vitamin A supplementation and deworming medication; 5. Our analysis showed that the SSVS method is able to accurately identify the statistically important predictors for the fixed effects of geostatistical models and that SSVS is not sensitive to co-implementation with a BVS procedure for CAR- structured, spatially varying coefficients. We also concluded that one of the three BVS methods for varying coefficients, namely the Global selection method, is able to identify true varying coefficients with 70% success rate