Lookup table to assign Manning’s roughness coefficient values to LULC.
\\n\\n
More than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\\n\\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\\n\\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\\n\\nAdditionally, each book published by IntechOpen contains original content and research findings.
\\n\\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\\n\\n\\n\\n
\\n"}]',published:!0,mainMedia:null},components:[{type:"htmlEditorComponent",content:'
Simba Information has released its Open Access Book Publishing 2020 - 2024 report and has again identified IntechOpen as the world’s largest Open Access book publisher by title count.
\n\nSimba Information is a leading provider for market intelligence and forecasts in the media and publishing industry. The report, published every year, provides an overview and financial outlook for the global professional e-book publishing market.
\n\nIntechOpen, De Gruyter, and Frontiers are the largest OA book publishers by title count, with IntechOpen coming in at first place with 5,101 OA books published, a good 1,782 titles ahead of the nearest competitor.
\n\nSince the first Open Access Book Publishing report published in 2016, IntechOpen has held the top stop each year.
\n\n\n\nMore than half of the publishers listed alongside IntechOpen (18 out of 30) are Social Science and Humanities publishers. IntechOpen is an exception to this as a leader in not only Open Access content but Open Access content across all scientific disciplines, including Physical Sciences, Engineering and Technology, Health Sciences, Life Science, and Social Sciences and Humanities.
\n\nOur breakdown of titles published demonstrates this with 47% PET, 31% HS, 18% LS, and 4% SSH books published.
\n\n“Even though ItechOpen has shown the potential of sci-tech books using an OA approach,” other publishers “have shown little interest in OA books.”
\n\nAdditionally, each book published by IntechOpen contains original content and research findings.
\n\nWe are honored to be among such prestigious publishers and we hope to continue to spearhead that growth in our quest to promote Open Access as a true pioneer in OA book publishing.
\n\n\n\n
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\r\n\tNational Instruments’ LabVIEW can be considered as a reference point nowadays for Engineers and Scientists all around the world. Employed as a specific solution and normally coupled with NI-made or third-part hardware, or in conjunction with additional software, there is almost no laboratory or industry, which does not adopt LabVIEW as a standard.
\r\n\tLabVIEW is often erroneously considered as a simple tool to acquire, process and display data. On the contrary, it should be considered for what it really is: an extremely powerful and complete Programming Language. Despite its intuitive interface, LabVIEW needs to be carefully understood and its development techniques must be acquired and well known to develop professional applications, which are robust, readable, scalable and maintainable.
\r\n\tThe present book welcomes topics as: LabVIEW in the Industry, in Automotive and Motion, In Monitoring and Controls, In Modelling and in the Educational Domain. The use of LabVIEW in Automotive as for in the Motion domain in general, underwent a big growth during last years so it is worth to dedicate a special section to this topic. A particular section, furthermore, is devoted to the Monitoring and Control Applications, in which Real-time Applications and FPGA programming, or Applications using the Datalogging and Supervisory Control Module are considered.
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He is a member of International collaborations in high-energy physics and a member of the Km3NET collaboration. 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In the past, he taught Computer Architecture, Automatic Measurements and Data Acquisition systems at the Information Technology Department of the University 'Federico II”.\nHe has been a Certified LabVIEW Developer (CLD) and a Certified Professional Instructor (CPI) for the National Instruments Company (Austin, Texas) since 2004, and he is in charge of teaching LabVIEW and Data Acquisition at the National Instruments Italy as a freelancer.\n\nDr. de Asmundis is a member of International collaborations in high-energy physics, previously for the L3 Experiment and currently in the ATLAS Experiment at CERN. He spent several years at CERN, in designing, testing and implementing particle detectors, data acquisition, and monitoring systems. He has been also an expert and responsible for technical infrastructures for detectors and big experimental installations (such as power supply systems for low and high voltage, gas supply systems, even as designer engineer).\n\nHe is currently a member of the Km3NET collaboration, where he carried on research relative to innovative photon detectors of astroparticle physics.\n\nDr. de Asmundis is an author of more than 1060 publications on international reviews in the high-energy physics and technical reviews (Physics Letters B, IEEE Transactions on Nuclear Science, Nuclear Instruments and Methods, Journal of Instrumentation, National Instruments conference proceedings, etc.). He has been an author of ten presentations in national and international Conferences. He has been the editor for scientific publications of the “Scientifica Acta” (Pavia, Italy) and IntechOpen (Croatia).\n\nWith a passion for music and electronic musical instruments, he is the owner of an electronic lab (Jurias, www.jurias.it) for resurrecting and restoration of any kind of electronic equipment related to music: keyboards, synthesizers, organs, HiFi and HiEnd systems and different audio equipment.\n\nHe is currently studying and playing classical piano.",institutionString:"INFN Sezione di Napoli",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"1",institution:{name:"INFN Sezione di Napoli",institutionURL:null,country:{name:"Italy"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"9",title:"Computer and Information Science",slug:"computer-and-information-science"}],chapters:[{id:"75407",title:"Analyzing and Presenting Data with LabVIEW",slug:"analyzing-and-presenting-data-with-labview",totalDownloads:0,totalCrossrefCites:0,authors:[null]}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"259492",firstName:"Sara",lastName:"Gojević-Zrnić",middleName:null,title:"Mrs.",imageUrl:"https://mts.intechopen.com/storage/users/259492/images/7469_n.png",email:"sara.p@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"50422",title:"Applied Hydrological Modeling with the Use of Geoinformatics: Theory and Practice",doi:"10.5772/62824",slug:"applied-hydrological-modeling-with-the-use-of-geoinformatics-theory-and-practice",body:'\nThe technological evolution during the last decades, especially in the field of geoinformatics, has offered new opportunities in hydrological modeling. The current efforts are targeted on optimizing existing models (setting some obsolete), evaluating them (with statistical methods, sensitivity analysis, field data, etc.), combining and comparing them, and most important recommending new ones based on original ideas and tools coming from developing technologies, techniques, and sciences. Part of these new technologies, perhaps the most important one, is occupied by Geographical Information Systems (GIS) and Remote Sensing (RS). These technologies stand on the cutting edge of modern geosciences, finding direct implementation in analysis and modeling of natural phenomena and research in key sectors like hydrology.
\nGIS-based hydrological analysis has a wide range of applications in (true) natural events that demand research, planning, and optimum management. An important aid to implement this methodology is the constantly increasing available free digital data (topographic, morphological, meteorological, land cover, spatially distributed data, etc.), offered by international projects (e.g. CORINE Land use/cover), new technologies such as RS (e.g., SRTM Aster Digital Elevation Model—DEM), national digital databases, and many other available sources. These data are continuously improving in volume, reliability, and spatial detail due to technological evolution, creating thus important databases (significant time series, spatial resolution, etc.) that along with freeware GIS software (e.g., QGIS and HEC-RAS) reduce cost, time, and improve efficacy in hydrological modeling.
\nFollowing not only new scientific trends but also contemporary demands and perspectives, the need for interdisciplinary approaches, in modeling natural processes and phenomena, is gaining more and more ground. For example, modeling runoff in a catchment via GIS can be implemented by a combination of satellite data, in situ measurements, time series data, etc., demanding thus a spherical perception of the study subject (e.g., hydrographic network characteristics, rainfall dynamic, and terrain characteristics) by combining various disciplines such as hydrology, geology, geomorphology, and hydrometeorology. Furthermore, the GIS-based modeling of natural processes requires a minimum understanding of data nature and limitations and processing of algorithms used by the software not only in order to implement the methodology but also to distinguish modeling errors and validate the analysis.
\nNovel environmental challenges have placed water resources management in high academic and research interest. Climate changes throughout the last decades, resulting in temperature augmentation, rainfall volume diminution, desertification, etc., and on the other hand in extreme events such as storms, flooding, landslides and soil erosion, threaten human lives and infrastructures. This constantly forming and alternating environmental regime has upgraded the need for scientific research on relevant disciplines like hydrology. Key goals of this effort are better methodological efficiency, optimum database management (as data volume is continually multiplying and demanding time-consuming data mining) and, more importantly, state-of-the-art modeling, as the understanding and forecasting of an event or a phenomenon are of utmost importance nowadays. Modern technologies based on Geoinformatics (e.g., GIS and RS, respectively) play a crucial role in this ongoing attempt.
\nMany researchers have published (and keep publishing) their work on hydrological issues throughout the years, contributing to literature volume rise concerning this topic and scientific knowledge. A general publications recursion and description over the last 45 years in hydrological references could start with Nash et al. and their series of papers in 1970 in Journal of Hydrology. Nash and Sutcliffe [1] attempted to state the need for a more efficient transition from classical hydrology to applied hydrology. In the first part of their publication series, they tried to propose a number of principles for river flow forecasting through conceptual models, which were put to a test in their second and third parts by applying these principles in two case studies in Brosna Catchment at Ferbane [2] and Ray Catchment at Grendon Underwood [3].
\nAs hydrological modeling started to flourish in scientific research, in the years that followed, many notable studies came to light. Among them, Beven’s and Kirkby’s work [4] was distinctive as they developed a hydrological forecasting model that combined the important distributed effects of channel network topology and dynamic contributing areas with the advantages of simple lumped parameter basin models. In the same year, Rodriguez-Iturbe and Valdes [5] attempted a unifying synthesis of the hydrological response of a catchment to surface runoff, by linking the instantaneous unit hydrograph (IUH) with the geomorphologic parameters of a basin. Closing the decade as it started, Kitanidis and Bras followed Nash and his colleagues (their work 10 years earlier) in setting a conceptual hydrological model for real-time short-term forecasts of river flows. Their first paper refers to an uncertainty analysis of the model, while the second to its applications and results [6, 7].
\nDuring the 1980s new ideas were published, establishing for good the digital era in hydrological modeling, as well as ones relevant to the rising need for evaluation and improvement of physically based models. In 1984, O’Callaghan et al. [8] carried forward to the scientific community their method for extracting drainage networks from digital elevation data, and 5 years later, Hutchinson [9] proposed a new procedure (the ANUDEM algorithm) for gridding elevation and stream line data. In the years between, and specifically in 1986, the Danish Hydraulic Institute along with the British Institute of Hydrology and SOGREAH (France) published their work on “Systeme Hydrologique Europeen” (SHE). This model was developed under the perception that conventional rainfall/runoff models are inappropriate to many demanding hydrological problems, especially those related to the impact of man’s activities on land-use change and water quality, and that only through the use of models which have a physical basis and allow for spatial variations within a catchment can these problems be tackled. This work was described in two chapters in Journal of Hydrology, where the first covered the evolution and general philosophy and the second the structure of the model [10, 11]. At the end of the decade, Beven expressed his criticism about problems in the application of physically based models for practical prediction in hydrology, focusing on limitations and lack of theory in specific aspects, practical constraints, and dimensionality issues [12].
\nIn the years between 1990 and 2000, there is a research outburst concerning hydrological modeling. The studies published in this period cover a wide range of topics referring either directly or indirectly to the discipline of hydrology. Environmental, climatic, and natural hazard issues became extremely important this decade (fact that continued if not increased until today), boosting scientists to direct their interests in aspects such as hydrological modeling interaction with soil erosion, landslides, and vegetation. Attempting a brief overview over these matters, a small number of relevant publications will be cited in the following paragraphs.
\nMaidment proposed a methodology based on GIS raster structure in order to extract a spatially distributed single hydrograph by calculating flow velocities for each cell in the study area. Subsequently, this flow velocity layer is calculated by the influx time of the water in each cell, at the river mouth, by dividing the flow length to velocity. Then, the isochronous curves are constructed (equal confluency time) together with the time-area chart (catchment surface which reflects the increasing extent of the basin that contributes to runoff through time). The unit hydrograph of the basin results from the slope of cumulative runoff surface. The velocity field is permanent, meaning that it is constant over time throughout the duration of the precipitation [13].
\nDaly et al. [14] proposed Precipitation-elevation Regressions on Independent Slopes Model (PRISM) trying to meet the demand for climatological precipitation fields on a regular grid, as ecological and hydrological models became increasingly linked to GIS that spatially represent and manipulate model output. Montgomery and his colleagues described their model for the topographic influence on shallow landslide initiation, by coupling digital terrain data with near‐surface through flow and slope stability models. More specifically, they used “TOPOG” hydrological model in order to predict the degree of soil saturation in response to a steady-state rainfall for topographic elements defined by the intersection of contours and flow tube boundaries, which was later used by the slope stability component to analyze the stability of each topographic element for the case of cohesionless soils of spatially constant thickness and saturated conductivity [15, 16]. In parallel, Wigmosta et al. [17] presented their distributed hydrology—vegetation model that included canopy interception, evaporation, transpiration, and snow accumulation and melt, as well as runoff generation via the saturation excess mechanisms.
\nSellers et al. [18] completed the revision of their first model Simple Biosphere (“SiB”) model creating the new edition “SiB2”, which belongs to a wider group of models that are called General Circulation Models (Atmospheric—“GSMs”). “SiB2” includes canopy photosynthesis—conductance model, use of satellite data to describe the vegetation phenology, a hydrological submodel for describing baseflows and calculate interlayer exchanges within the soil profile, and other tools covering aspects like snowmelt [19]. Morgan et al. [20] published European Soil Erosion Model (“EUROSEM”), which is a dynamic distributed model, able to simulate sediment transport, erosion, and deposition over the land surface and its outputs include total runoff, total soil loss, storm hydrograph, and storm sediment graph.
\nMany researchers have applied the spatially distributed unit hydrograph with spatially variable rainfall, included losses of rain by using the method of curve numbers (Curve Number, USDA), which is particularly suitable for use in a GIS environment, resulting in successful simulated hydrographs that had arisen from actual measurements [21].
\nIn 2000, Iverson tried via a mathematical model to evaluate the effects of rainfall infiltration on landslide occurrence, timing, depth, and acceleration in diverse situations [22]. Finally, the same year, Vörösmarty et al. issued a critical review on global water resources arguing on their vulnerability from climate change and population. The point of views that they expressed was derived by co-evaluation, analysis, and combination of climate model outputs, water budgets, and socioeconomic information along digitized river networks. In few words, they resulted in the opinion that a large proportion of the world’s population is currently experiencing water stress and that rising water demands greatly outweigh greenhouse warming in defining the state of global water systems to 2025. They also stated that the consideration of direct human impacts on global water supply remains a poorly articulated but potentially important facet of the larger global change question [23]. These ideas strengthened the need for hydrological research and sustainable management of water resources, setting thus hydrological modeling as an important priority, and laid the carpet for the 21st century’s scientific goals.
\nFocusing purely on hydrological modeling and analysis, during the decade 1990–2000, it is highly noticeable that new technologies begin to occupy significant space in this field. For example, RS techniques start to define their part as a useful, modern, and continuously evolving scientific trend in environmental sciences and therefore, in hydrology. In short reference, Houser et al. [24] wrote their paper on integrating soil moisture RS and hydrological modeling, while Jackson et al. [25] used microwave radiometry in an attempt to map soil moisture in regional scales. Another parallel trend, on hydrological modeling, these years was neural network modeling. Dawson and Wilby made their approach to rainfall—runoff modeling via Artificial Neural Networks (ANN) [26, 27], and Govindaraju [28, 29] followed them in 2000 with his two papers about ANN in hydrology.
\nNevertheless, the most distinctive and influential research topic of 1990s was the coupling of Digital Elevation Model (DEMs) analysis and raster-based hydrological modeling, which consolidated the use of GIS in hydrology. In 1991, there were many authors that directed their interests toward raster modeling. Tarboton et al. [30] wrote about the extraction of channel networks from digital elevation data, Moore et al. [31] published a review on hydrological, geomorphological, and biological applications through digital terrain modeling, Quinn et al. [32] attempted a prediction of hillslope flow paths using DEMs, and finally, Fairfield and Leymarie [33] worked on deriving drainage networks from grid DEMs. Three years later, Zhang and Montgomery examined the effect of DEM’s grid size in landscape representation and hydrological simulations [16], and Tarboton [34] proposed a new method for the determination of flow directions and upslope areas in grid DEMs. Bates and De Roo [35] closed the century with their raster-based model for flood inundation simulation.
\nThe 21st century started with the place and significance of GIS, RS, and other modern technologies in hydrological modeling well established. New scientists targeted in developing new ideas based on the previous works and tools. Free software packages were developed and distributed, huge global digital data banks were created and various research projects took place. The evolution and revolution of hydrological modeling via modern technologies still flourish, finding constantly new applications, meeting continuously growing demands, and inviting more and more new scientists to work on this field. In the following paragraphs, a short literature review of the last 15 years will be presented, starting with a brief reference on hydrological modeling in general and followed by a wider review on the main topic of this chapter.
\nBeven continued his critical reviews on hydrological modeling with a discussion concerning the problems of distributed models [36]. In the same period, Dawson and Wilby applied ANN, a highly emerging field of research, for rainfall-runoff modeling and flood forecasting [27]. Simultaneously, Thiemann et al. coped with the problem of uncertainty of hydrological modeling, which is the compound effect of the parameter, data, and structural uncertainties associated with the applied model. They presented the framework for a Bayesian recursive estimation approach to hydrological prediction that can be used for simultaneous parameter estimation and prediction in an operational setting [37]. A similar attempt was made a few years later by Ajami et al. [38] with their integrated hydrological Bayesian multimodel combination framework, which also tried to confront the uncertainties in hydrological predictions.
\nAs new ideas and techniques dominate the field, Hock [39] approached a different aspect of hydrological modeling, with direct reference on environmental and climate change. It was none other than temperature index snow or ice melt modeling. Also, Döll et al. expressed their interest on global environmental issues by introducing Water GAP Global Hydrology Model (WGHM), which computes surface runoff, groundwater recharge, and river discharge at a spatial resolution of 0.5 and is a submodel of the global water use and availability model WaterGAP 2, which was also introduced in the same year [40, 41].
\nOne of the most innovative ideas published in 2004 was that of Nayak et al. [42], concerning the combination of ANN and fuzzy logic approaches, creating thus a neuro—fuzzy hybrid computing technique for modeling hydrological time series. Finally, the Distributed Model\nIntercomparison Project (DMIP) was selected as a last reference for 2004, due to its distinctive concept, as it was formulated as a broad comparison of many distributed models among themselves and to a lumped model used for operational river forecasting in the US [43].
\nClosing the general reference on hydrological modeling, it would be inconsiderate not to mention Soil and Water Assessment Tool (SWAT), which is a conceptual, continuous time model that was developed in the early 1990s to assist water resource managers in assessing the impact of management and climate on water supplies and nonpoint source pollution in watersheds and large river basins. This tool was developed further in the 21st century (and keeps developing), and many research studies were based on its application. Some of the most indicative ones are the papers by Arnold and Fohrer [44], by Abbaspour et al. [45], by Kalogeropoulos et al. [46], as well as by Kalogeropoulos and Chalkias [47]. The first refers to SWAT2000 and its capabilities and research opportunities in applied watershed modeling, while the second concerns an application of the model on hydrology and water quality in the prealpine/Alpine Thur watershed. The third one was the developing of a methodology of water resources exploitation, with the potential of creating small mountainous and upland reservoirs, by coupling hydrological analysis and SWAT model. The fourth one was an attempt of hydrological modeling incorporating SWAT model in a GIS environment in order to exam various scenarios of climate change in a Mediterranean catchment. Equally important are the RS-based approaches targeting hydrological—environmental modeling. Among the most important ones is NASA’s modern-era retrospective analysis for research and applications (MERRA), the history of which as well as its contemporary development and applications are sufficiently described [48]. SWAT and other similar models along with RS is highly linked and coupled with GIS, as shown below.
\nThe last part of this literature review aims at identifying the most influential publications of the last 15 years, about empirical hydrological modeling and GIS integration.
\nIn 2001, Weng [49] developed a methodology to relate urban growth studies to distributed hydrological models using an integrated approach of RS and GIS. Following a similar concept, Fortin et al. [50] proposed HYDROTEL, a distributed watershed hydrological model compatible with RS and GIS. US Environmental Protection Agency Office of Water developed Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) system, which integrates GIS, watershed tools, and SWAT model [51]. In parallel, in order to analyze land cover changes, a landscape assessment tool was developed by using a GIS that automates the parameterization of the SWAT and KINEmatic Runoff and EROSion (KINEROS) hydrological models [52]. The first three years of the century closed with Liu et al. [53] proposing a GIS-based diffusive transport approach for the determination of rainfall runoff response and flood routing through a catchment, and with Al-Sabhan et al. [54], introducing a real-time hydrological model for flood prediction using GIS and the World Wide Web. Finally, one of the most interesting studies of 2003 was the work of Huggel et al. [55], which proposes a modeling approach, which takes into account the current evolution of the glacial environment and satisfies a robust first-order assessment of hazards from glacier-lake outbursts in the southern Swiss Alps.
\nIn the next three years, a lot of significant papers were published. Lan et al. [56] used hydrological modeling and GIS for spatial analysis and prediction of landslide hazard in the Xiaojiang watershed, Yunnan, China. During the same year, a grid or cell-based process-oriented distributed rainfall-runoff model, capable of handling the catchment heterogeneity in terms of distributed information on landuse, slope, soil, and rainfall, was developed and applied to isolated storm events in several catchments by Jain et al. [57]. Knebl et al. [58] published their work on regional scale flood modeling that integrates NEXRAD Level III rainfall, GIS, and hydrological model HEC-HMS/RAS, applied on San Antonio River Basin in Central Texas, USA, for a specific storm event. Furthermore, among the most distinguished papers of 2005 was the study of Kyoung et al. [59] in which two digital filter-based separation modules, the BFLOW and Eckhardt filters, were incorporated into the Web-based Hydrograph Analysis Tool (WHAT) system, whose Web GIS version accesses and uses US Geological Survey (USGS) daily streamflow data from the USGS web server. Jia et al. [60] developed the WEP-L, a physically based distributed hydrological model, which couples simulations of natural hydrological and water use processes, with the aid of RS data and GIS techniques. At the same time, Olivera et al. [61] presented ArcGIS-SWAT, a geodata model and GIS interface for the SWAT. The final reference for 2006 concerns the work of Wolski et al. [62] on modeling of the flooding in the Okavango Delta, Botswana, using a hybrid reservoir-GIS model, which is a semidistributed and semiconceptual approach.
\nMelesse and Graham proposed a GIS-based model on calculating the routing time. They perceived the flow within the basin into two major types of flow: the flow into the main river channel and the overland flow (flow onto the slopes of the catchment). Here, the flow time for each cell is the sum of the flow times of all the cells along the path of the water (from each cell until the mouth of the catchment). Instead of the unit hydrograph, they proposed the calculation of a direct flood hydrograph, resulting directly from the sum of the volumetric flow rates of all the confluent cells at each time step. This model was a fixed time spatially distributed direct hydrograph approach [63].
\nThe need to exploit hydrological models for researching various environmental aspects and hazards lead Pandey et al. [64] on an attempt to identify the critical erosion prone areas of Karso watershed of Hazaribagh, Jharkhand, in India, using Universal Soil Loss Equation (USLE), RS technology, and GIS technologies. Simultaneously, Miller et al. [65] presented an open-source toolkit for distributed hydrological modeling at multiple scales called the Automated Geospatial Watershed Assessment (AGWA) tool, which uses commonly available GIS data layers to fully parameterize, execute, and visualize results from both the SWAT and Kinematic Runoff and Erosion model (KINEROS2). In 2008, an approach for groundwater vulnerability assessment (covering thus another sector of hydrology) in shallow aquifer in Aligarh, India, was made by Rahman [66], using a GIS-based DRASTIC model. Jonkman et al. [67] tried to cope with the problem of flood damage in the Netherlands, by integrating hydrodynamic and economic modeling via GIS, offering thus a new approach and perspective in the analysis of this natural phenomenon. During 2009, various interesting papers were published. Among them the studies of Maksimovic et al. [68], Chen et al. [69], Milewski et al. [70], and Sheikh et al. [71] stood out. The first two papers dealt with urban flooding via GIS modeling combining various techniques, tools and data, like high-resolution Digital Elevation Model data collected by the LiDAR technique and GIS-based urban flood inundation model (GUFIM), respectively. The third paper concerns applied methodologies for rainfall-runoff and groundwater recharge computations that heavily rely on observations extracted from a wide-range of global RS datasets (TRMM, SSM/I, Landsat TM, AVHRR, AMSR-E, and ASTER), using the arid Sinai Peninsula and the Eastern Desert of Egypt as test sites, while the fourth one introduced Bridge Event and Continuous Hydrological (BEACH) model (developed in GIS), used for predicting soil moisture.
\nDu et al. [72] proposed a spatially distributed model similar with the model of Melesse and Graham [63], but they took into account the temporal variability. The improvement relates to the calculation of the variation of flow time in each cell, due to the velocity variance, regarding the uneven distribution of rainfall over time. This model also incorporated the rainfall losses by using the curve number methodology (Soil Conservation Service [73]). This model was named time variant spatially distributed direct hydrograph.
\nAt the end of the decade, Van der Knijff et al. [74], described the spatially distributed LISFLOOD model, which is a hydrological model specifically developed for the simulation of hydrological processes in large European river basins.
\nAs flood management became more and more important due to climate change and other environmental and human factors, many researchers pointed their work toward these issues. In this frame, Rozalis et al. [75] used an uncalibrated hydrological model and radar rainfall data for flash flood prediction in a Mediterranean watershed. Also in 2010, Kourgialas et al. [76] published a very interesting case study about Koiliaris River Basin, located east of the city of Chania on the island of Crete in Greece, proposing an integrated framework for the hydrological simulation of this complex geomorphological river basin that includes a two-part Maillet Karstic model, a GIS-based Energy Budget Snow Melt model, an empirical karstic channel model and the Hydrological Simulation Program—FORTRAN (HSPF) model. In the year that followed, Paiva et al. [77] presented a large-scale hydrological model with a full one-dimensional hydrodynamic module to calculate flow propagation on a complex river network, while Lei et al. [78] developed an efficient and cost-effective distributed hydrological modeling tool (MWEasyDHM) based on open-source MapWindow GIS. Furthermore, Fugura et al. [79] coupled hydrodynamic simulation with a well-developed digital surface and terrain model (DEM), derived by aerial photogrammetry, to map flood extent in Kuala Lumpur, Malaysia. Kia et al. [80] developed a flood model, using various flood causative factors, ANN techniques, and GIS to model and simulate flood-prone areas in the southern part of Peninsular Malaysia. Sarhadi et al. linked GIS techniques (HEC-GeoRAS, IRS-P6 satellite images, etc.) with frequency analysis, aiming at probabilistic flood inundation mapping of ungauged rivers and more specifically of the Halilrud basin and Jiroft city in southeastern Iran, which were selected as an example of hazardous regions [81].
\nDespite the significant volume of previous research, the publication list in this topic is still increasing. Lopez–Vicente et al., used the modified version of the revised Morgan, Morgan and Finney (RMMF) model to predict the hydrological connectivity and the rates of soil erosion under four different scenarios of land uses and land abandonment along with GIS in the Estanque de Arriba catchment (Spanish Pre-Pyrenees) [82]. Paiva et al. [83] published their validation work for the implementation of MGB-IPH hydrological model, which uses full Saint Venant equations, a simple storage model for flood inundation and GIS-based algorithms to extract model parameters from digital elevation models, on large-scale hydrological modeling in the Amazon and specifically in the Solimões River basin. Tehrany et al. [84] proposed a novel methodology for flood susceptibility mapping, where weights-of-evidence (WoE) model was utilized first to assess the impact of classes of each conditioning factor on flooding through bivariate statistical analysis (BSA) and then, these factors were reclassified using the acquired weights and entered into the support vector machine (SVM) model to evaluate the correlation between flood occurrence and each conditioning factor. Another published novel idea of the year was that of Formetta et al. [85], who described the structure of JGrass-NewAge: a system for hydrological forecasting and modeling of water resources at the basin scale. Furthermore, among the published papers of 2014, the integration of RS and GIS occupies a rather special place, with the most influential works on this topic. Chen et al. [86] developed a methodology for regional estimates of potential floodwater retention under floodplain inundation, from ecologically significant flood return periods, by coupling RS and GIS technologies with spatial hydrological modeling. Mahmoud [87] estimated the potential runoff coefficient (PRC), using GIS, based on the area’s hydrologic soil group (HSG), land use, slope, and determined the runoff volume in Egypt. Finally, Fiorillo et al. [88], published a model for simulating recharge processes of karst massifs and Krysanova et al. [89] used Soil and Water Integrated Model (SWIM) to model climate and land-use change impacts (four different application studies were made and analyzed). Both research works couple GIS and hydrological modeling.
\nIn conclusion, from the references presented above, it can be easily deduced that hydrological modeling occupies a distinguished place in environmental modeling and research. The latest trends in the field are RS techniques and GIS coupled with hydrological modeling. The development and application of this coupling is expected to flourish the following years in scientific research.
\nAs mentioned earlier, GIS-based hydrological analysis has a very wide variety of applications in natural events and natural disasters. This part of the chapter intends to highlight the contribution of GIS in hydrological analysis and simulation by presenting an empirical analysis.
\nThe basic aim of this simulation is to estimate the peak flood discharge, derived by an extreme rainfall event, as well as the critical time to reach this peak right after the rainfall peak. In order to do that, a synthetic Unit Hydrograph (UH) is obtained by estimating the time-area curve. The curve (histogram) of time-area shows the spatiotemporal relationship during time at which water flows within the basin. This curve can be expressed with a reclassification of time concentration at specific time intervals. These time periods are distinguished by isochrones. These are the lines within the catchment where runoff has the same travel time to reach the outlet of the basin.
\nAccording to the theory of the UH, the duration of the flood is the same for any given amount of active rainfall duration, while the ordinates of the hydrograph on the joint duration (time base flood) is directly proportional to the amount of rain (Chow et al., 1988). Thus, the discharge at the outlet of the basin is resulting from the superposition (addition) of instantaneous UH produced by active rain at each time step. UHs in hydrological practice are exported with numerical techniques from observed hydrographs. Many scientists have used GIS technology in order to construct rainfall-runoff model for UH attainment [13, 21, 63, 72].
\nIn order to estimate the magnitude of a flood, a routing model was designed in a GIS context [63, 72, 90, 91]. The choice of the specific model was based mainly on its ability to be created entirely in a GIS environment. Accordingly, this model is very flexible to changes and connection with other models. Also, it is expandable, and it can be easily used in different areas.
\nThe basic concept of the simulation is the runoff analysis in a GIS environment given a specific storm. The initiate data which is needed for this simulation is
\nThe model can incorporate various types of rainfall data. More specifically, data derived by rainfall stations can be used. In this case, the use of them depends on the number of meteorological gauge stations. So, for example, if there is only one rainfall station in the river basin (i.e., the study area), the rain data is entered into the model (the simulation) as cumulative rainfall (single number). The distribution of rainfall is used after the modeling to construct the flood hydrograph. This simulation is taking into account only the time distribution of the rainfall (time modeling).
\nIf the study area has more than one meteorological gauge stations, then the best way to handle all the rainfall data is to proceed to the tessellation of the data, e.g., with the creation of Voronoi (Thiessen polygons) geometries. In this way, the simulation is taking into account, besides time, the spatial context of the rainfall distribution (semispatiotemporal modeling).
\nNowadays, the use of radar for record rainfall, or the use of data that are provided by Atmospheric Simulation Model, has provided the ability to incorporate in the hydrological modeling both the spatial and temporal variation of rainfall (spatiotemporal modeling).
\nIn each case, the best way to simplify the hydrological modeling is to modify the total rainfall in terms of the part of rainfall which finally becomes surface runoff (excess rainfall). This data can be extracted from Atmospheric Simulation (the rainfall grid values can be only the excess rainfall). Otherwise, techniques such as Curve Numbers CN can be established in order to be used as a layer in the process of simulation [72].
\n\nFigure 1 presents the most common types of rainfall data which can be used in the model. Figure 1a shows a study area which is covered from only one rain station. Figure 1b presents a study area which is covered from many rain gauge stations (that is why the Thiessen polygons are used), and Figure 1c shows six different raster presentation of a 3-h cumulative rainfall (each one) and all together (in a row) cover the entire flood event.
\n(a) One weather station—time modeling, (b) many weather stations—semi-spatiotemporal modeling (dots represents meteorological stations), (c) use of atmospheric simulation data—spatiotemporal modeling (t1–t6 are time snapshots of 3-h cumulative rainfall, blue color indicate high values of cumulative rainfall & yellow color indicate low values of cumulative rainfall).
In order to perform the simulation a Manning’s roughness coefficient layer is needed. The construction of such a layer requires a land use/land cover (LULC) map of the study area.
\nEach type of LULC is assigned to Manning’s roughness coefficient values using suitable lookup tables like the one in Table 1 (for more details see reference [92]).
\nDescription | \nManning’s n | \n
---|---|
Forest/Forest mixed | \n0.1 | \n
Urban/Urban mixed | \n0.015 | \n
Pasture/Pasture mixed | \n0.03 | \n
Permant Crop/Permant crop mixed | \n0.035 | \n
Arable Crop/Arable crop mixed | \n0.03 | \n
Olive/Olive mixed | \n0.15 | \n
Vineyard/Vineyard mixed | \n0.05 | \n
Lookup table to assign Manning’s roughness coefficient values to LULC.
After pairing the values of each LULC type to Manning’s n values, the roughness coefficient layer (grid) is constructed.
\nThe digital elevation models have been used, during the last decades along with the development of GIS, in order to derive hydrological and hydro-geomorphological properties such as streams, basins, flow direction, flow accumulation, flow length, and stream order. Nowadays, the development in satellite technology provides very high accuracy for remotely sensed data in terms of landscape topography. Alternatively, data generated from digitization of topographic maps can be used after applying the suitable algorithms in order to create a DEM, e.g., the algorithm ANUDEM.[93]. This specific algorithm produces a coherent grid which maintains the integrity of the topography [94]. Another way of constructing DEM is to use data derived from the use of Laser Scanners. The elevation point cloud is converted to Triangulated Irregular Network (TIN) and then is converted to DEM.
\nIn GIS-based hydrological analysis, the use of DEM is exceptional and of critical importance. The cell size of a DEM largely determines the accuracy of the analysis that is carried out each time.
\nThe methodology which is presented in this paradigm is actually based on the estimation of concentration time in order to construct a layer of isochrones. Accordingly, calculations were carried out for flow time within the basin, both for channel and overland flow. In order to discrete these two types of water flow, a suitable threshold on flow accumulation must be selected. This can be done by several iterations until the stream layer reflect reality. Hence, the two types of flow are separated, and it also results in drainage network determination and mapping. As mentioned before, the topography of the land surface (expressed by a DEM) is one of the most fundamental elements for this simulation. Thus, DEM construction and analysis is the first step in order to execute the current rainfall-runoff model. There are various derivatives from the hydrological analysis of a DEM such as the slope (surface analysis), flow direction, flow accumulation, and flow length (hydrological analysis).
\nBy extracting the flow accumulation layer (from the above DEM analysis), the discharge within the channel (Qch in m3/s) of the river is calculated according to Eq 1:
where R is the amount of rainfall (in meters) and TR is the duration of rainfall (in seconds). If the rainfall comes from only one meteorological station, R is actually a number which represents the amount of rainfall throughout the duration of the event. If the rainfall comes from several gauge stations, R is a grid layer which corresponds to closest gauge station. Lastly, if the rainfall comes from several grid layers which represent the spatiotemporal distribution of the rain, the discharge within the channel must be calculated as many times as the number of the separate grids. Then, these grids are added to give the total discharge within the river network.
\nThe velocity of the water within the channel (Vc in m/s) can be estimated according to the combination of Manning’s equation with the continuity equation by using the following Eq 2:
Where
Likewise, the overland flow velocity (V0 in m) can be estimated according to Eq 3:
where S0 is the surface slope (m/m), l is the length of the slope (m), ie is the vertical net incoming flux (m/s), and n is the Manning’s roughness coefficient. The combination of the above two types of velocities provides the final velocity, since the final velocity is calculated for each cell off the basin (using conditional algorithms).
\nThe travel time (T in s) in each cell was computed from the travel distance using as a weight raster the 1/V grid as illustrated by Eq 4:
All the above equations can be calculated with the use of map algebra in a GIS software package. Map Algebra is a language that defines a syntax for combining map themes by applying mathematical operations and analytical functions to create new map themes. In a map algebra expression, the operators are a combination of mathematical, logical, or Boolean operators (+, >, AND, tan, etc.), and spatial analysis functions (slope, shortest path, spline, etc), and the operands are spatial data and numbers.
\nFinally, in order to estimate the flow time and isochrones (i.e., curves that connect areas of the basin where the runoff needs the same time to reach the exit of the basin), it is necessary to reclassify the values of travel time T.
\nThe flow chart of the methodology is presented in Figure 2.
\nThe flow chart of the methodology.
The time-area unit hydrograph theory, as it known, inaugurates a specific association between the travel time T and a part of the upper catchment that may contribute runoff during this travel time T. The area which is closest to the catchment outlet will contribute to the runoff hydrograph sooner than the other areas which are on the catchment boundary. This method indicates that the catchment is divided into areas of approximately travel time (isochrones). These lines of equal travel time are known as isochrones. Hence, the time-area histogram is actually converted to a hydrograph. Figure 3 presents a common type of isochrones for the needs of this current empirical paradigm.
\nReclassified travel time (time zones, isochrones).
The total amount of rainfall for the examined flood event is 72 mm (0.072 m) within 18 h. From Figure 3 it is obvious that the distribution of rainfall is presented in 3-h cumulative rainfall snapshots (R1 = 10 mm, R2 = 0.025 mm, R3 = 0.005 mm, R4 = 0.01 mm, R5 = 0.015 mm, and R6 = 0.007 mm). The area of each time zone (0
The main goal is the calculation of the discharge that is reaching the outlet of the basin in order to construct the synthetic UH (the so-called “palm of discharge”). For this reason, the amount of water that falls onto each time zone is calculated. Thus, for the first time zone (t1), the amount of water during the first 3 h is V11 = R1*A1 = 0.01 m*3,200,000 m2 = 32,000 m3, for the second time zone (t2) is V21 = R2*A1 = 0.025 m*6,300,000 m2 = 80,000 m3, etc.
\nThe next step is the calculation of the total volume for each palm of water discharge that reaches the outlet of the basin. Thus, the volume of the first palm is Vpalm1 = V11 = 32,000 m3 (the first purple cell in Figure 3), the volume of the second palm is Vpalm2 = V21 + V12 = 80,000 m3 + 63,000 m3 = 143,000 m3 (the sum of the first red cells in Figure 3) etc.
\nThe synthetic unit hydrograph (UH).
The final step is the reduction of each volume to time, which is actually the calculation of the discharge. By plotting these values of discharges against time the synthetic UH is constructed. This synthetic UH is presenting on Figure 4. This UH reveals two vital values of the flood hydrographs which are the critical time and the maximum (peak) value of the discharge. For this empirical paradigm, these values are Tc = 18 h and the Qpeak = 388.667 m3/s.
\n\nThis methodology attempts to analyze the physical processes of a rainfall event in a hypothetical study area. Thus, a rainfall-runoff model is used for estimating the spatially distributed synthetic UH for the outlet of the catchment.
\nThe form of the model-derived synthetic UH for the outlet of the basin can be used in a variety of cases. There are two crucial values derived from a UH, the critical time (time difference between peak rainfall and maximum discharge) and the peak value of the discharge. The development of such hydrographs can be used for extreme rainfall magnitudes in order to design constructions such as bridges and roads.
\nAlso, UH can be used in order to extrapolate flood flow records based on rainfall records and for the development of flood forecasting and warning systems. Additionally, each UH shows the response of the catchment-study area, i.e., they provide also evaluations of extreme discharges while they are giving the opportunity to design UH (in rivers and streams) with lack of meteorological and hydrometric stations (by applying modeling on rainfall and hydrological data using GIS).
\nThe empirical modeling described earlier has also some limitations. It undertakes uniform distribution of rainfall over the catchment and uniform intensity during the duration of rainfall excess (in case of rainfall data from rain gauge stations). In practice, these conditions are not satisfied during a real storm event. Under specific situations of nonuniform aerial scattering and disparity of intensity, UH, still, can be used if the spatial distribution is constant between different flood events. In addition, in some cases, when the rainfall data comes from meteorological stations, the catchment size levies a superior limit on the pertinency of the UH implementation due to rainfall distribution. In this case, a very big river basin needs to be tackled as the sum of smaller subcatchments. Thus, this obligation noises for an assortment of flood events of so slight a period which would generally yield a strong and approximately unchanging effective rainfall. Also it would yield a distinct single peak of hydrograph of short time base. UHs that are having the same time base are unswervingly relative to the total amount of runoff given by each hydrograph (linearity).
\nUsually, in hydrological modeling and especially in modeling of flash floods, there are some definite assumptions. For instance, the effects of evapotranspiration, as well as the synergy between the aquifer and the rivers, are ignored. This could also be overlooked due to the fact that the amount of evapotranspiration during the time, in which the flood occurs, is insignificant when compared to other fluxes such as infiltration. Furthermore, the effect of the aquifer-river synergy is commonly disregarded due to the response time of overland flow versus the flow within the channel. Similarly, effects of the rest of hydrological procedures such as interception and depression storage are also ignored.
\nDespite the assumptions/limitations of the model, the proposed modeling provides a meaningful estimation of the maximum value of discharge and the peak time of a flood event.
\nThe introduction of GIS technology led researchers to develop data processing automations and to produce reliable simulation models. They appreciate the standing and welfares of such a technology that empower them to evaluate data, contend with complications, generate instinctive visualization approaches, and make conclusions with a higher effectiveness.
\nThe objective of this chapter was to present the extended history of GIS modeling and to converse the modern observes in terms of integration of GIS with the hydrological modeling, and also to discuss the problems, the assumption, and the limitations of GIS-based hydrological models. Generally, four different approaches have been widely proposed and used in terms of integrating GIS with the hydrological modeling. These are (a) embedding GIS-like functionalities into hydrological modeling software, (b) embedding hydrological modeling into GIS software, (c) loose coupling (add-on), and (d) tight coupling which actually is to customize applications into a GIS software [95].
\nTherefore, these models can be used as tools for policy makers in order to take decisions for the construction of artificial dams (i.e., containment barriers) and halting water projects in general. Thus, rainfall-runoff models together with the GIS technology are used as integrated systems of assessing potential impacts for various rainfall events. Hence, the GIS technology has the capability to postprocess the results which are obtaining from a model and sublimate them into policy.
\nMany diseases especially non-communicable diseases (NCDs) culminate in end-stage organ failures; the preferred treatment for most end-stage organ diseases is transplantation. Transplantation programme is a complex healthcare service which entails huge costs and requires highly skilled health professionals, complex infrastructure and equipment, and well-articulated legal frameworks to enable its operationalization [1]. The need for appropriate interventions for organ failures in sub-Saharan Africa (SSA) is underscored by the high prevalence of end-organ diseases such as chronic kidney disease (CKD), chronic liver disease (CLD), chronic lung and heart diseases (interstitial lung disease, cystic fibrosis, cardiomyopathies and chronic rheumatic heart diseases) which cause increased morbidity and mortality. For example, Kaze et al [2] in a systematic review of prevalence studies on CKD in SSA documented the highest prevalence in West Africa 19.8%, Central Africa 16%, East Africa 14.4%, and Southern Africa 10.4%.
Globally, beside organs, tissues and cells (bone marrow cornea, etc.) are also transplanted. However, in SSA, apart from South Africa which also does liver and heart transplantation, the common organ transplanted is the kidney [3]. Though outcomes for transplantation have improved over the years due to better surgical techniques including minimal access surgeries, newer and better immunosuppressive medications, innovations in organ donation; improvement in transplant services is not apparent in SSA. Organ transplantation remains largely inaccessible and unaffordable to this population.
Sub-Saharan Africa has a disproportionate burden of communicable diseases (CDs) and NCDs compared to other world regions [4]. Currently, NCDs are responsible for a large and increasing burden of death and disability in the region. World Health Organization (WHO) in 2018, documented that NCDs killed 41 million people per year accounting for 71% of the global deaths [5]. The ages most affected were 30 to 69 years age-group, belonging to the productive workforce of any population. People from low income countries (LICs) and lower-middle income countries (LMICs) accounted for most of these deaths approximating over 85%. Four of the five commonly quoted diseases i.e. the “Big Five” (cardiovascular diseases, cancers, respiratory diseases, diabetes mellitus (DM) and mental illness) that account for most NCD deaths are drivers of CKD. Several risk factors with multiplier effect on NCDs are tobacco use, physical inactivity, harmful use of alcohol and unhealthy diets. Communicable diseases, though less common in high income countries (HICs) and upper-middle income countries (UMICs) are still prevalent in LICs and LMICs prompting WHO to highlight the double burden of diseases in these regions [6]. Both CDs and NCDs culminate in end-organ disease underscoring the high prevalence of end-organ failures, disabilities and deaths in SSA (see Figure 1). Unfortunately, most countries in this region lack resources to cope.
Causes of deaths in sub Saharan Afirca 1990 and 2017 [from Institute for Health Metrics and Evaluation (IHME) data].
In 2014, Stanifer et al [7], in a systematic review and meta-analysis of 21 studies in SSA documented an overall CKD prevalence of 13·9%. According to the Institute for Health Metrics and Evaluation (IHME) data, CKD and DM were the 14th cause of death in SSA in 1990 but worsened to 11th by 2017 (see Figure 1). Hypertension and DM constitute the main NCDs that cause CKD globally [8]. In many low resource countries (LRCs), chronic glomerulonephritis and interstitial nephritis assume significance because of the pervading and persisting high prevalence of CDs (mainly bacterial, parasitic, and viral infections) [9]. Human Immunodeficiency virus (HIV) infection which continues to plague SSA, albeit better controlled, is a key driver of kidney disease. Of the 38 million people living with HIV globally, more than 25 million live in this region [10, 11]. The recent pandemic of COVID-19 infection which has adverse acute effects on the kidney has probable unknown long-term sequelae [12]. Both CDs and NCDs fuel the high and increasing prevalence of CKD in LRCs. Without renal registries in many LRCs, there is poor documentation of data on kidney diseases.
Viral hepatitis is prevalent in Africa with high endemicity of Hepatitis B Virus (HBV) in SSA and Hepatitis C virus (HCV) in North Africa. Africa has approximately 60–100 million of the world’s 257 million viral hepatitis infections [13]. The WHO noted that between 1980 and 2010, cirrhosis-related deaths doubled in the region. The increasing burden of obesity and DM leading to non-alcoholic fatty liver disease contributes to high prevalence of CLD and end-stage liver disease (ESLD). Up to 40% of patients with chronic hepatitis may progress to liver cirrhosis and/or liver cancer [14] and without liver transplantation mortality is estimated at about 15% in one year [15]. All patients with ESLD will invariably require liver transplantation; however, liver transplants are uncommon in SSA.
There is scant information on prevalence of other end organ failures such as heart, lung, and small bowel requiring organ transplantation in SSA.
The WHO in collaboration with the Organización Nacional de Trasplantes of Spain set up the Global Observatory on Donation and Transplantation (GODT) with the mandate to document the distribution of organ transplantation programmes in the countries that report their data to the Observatory and to evaluate the access of transplantation activities worldwide [16]. Upon subsequent request of the World Health Assembly (Resolutions WHA57.18 and 63.22) that global data on the practices, safety, quality, efficacy, epidemiology and ethical issues of allogeneic transplantation be collected and documented, the GODT was inaugurated in 2007 [16]. This database has ensured provision of transparent and equitable monitoring of national transplant systems.
Currently, according to the GODT database, [17], 139,024 solid organ transplants were reported globally in 2017: 90,306 kidney (36% from living donors), 32,348 liver (19.0% from living donors), 7881 heart, 6084 lung, 2243 pancreas and 162 small bowel transplants. Africa contributes the least number of transplant activity per continent and SSA the least number per WHO World region (Tables 1 and 2; Figure 2). Tables 1 and 2 show data from 2016 GODT Report.
Region | Countries N | Countries with data N (%) | Population millions | Population with data millions (%) |
---|---|---|---|---|
AFR | 46 | 10 (21.7) | 1139.1 | 506.6 (44.5) |
AMR | 35 | 21 (60.0) | 986.5 | 968.5 (98.2) |
EMR | 22 | 15 (68.2) | 656.1 | 535 (81.5) |
EUR | 53 | 49 (92.5) | 909.7 | 904.2 (99.4) |
SEAR | 11 | 5 (45.5) | 1928.4 | 1408.8 (73.1) |
WPR | 27 | 11 (40.7) | 1847.7 | 1815.3 (98.3) |
Total | 194 | 111 (57.2) | 7467.5 | 6138.4 (82.2) |
Proportion of countries and population covered by the GODT database in the WHO regions. Year 2015 [17].
Africa Region (AFR) | America Region (AMR) | Eastern Mediterranean Region (EMR) | Europe (EUR) | South East Asia Region (SEAR) | Western Pacific Region (WPR) | |
---|---|---|---|---|---|---|
Kidney | 488 (1.0) | 31,859 (32.9) | 6127 (11.5) | 26,131 (28.9) | 7202 (5.1) | 12,540 (6.9) |
Liver | 67 (0.1) | 10,426 (10.8) | 1539 (2.9) | 9582 (10.6) | 1292 (0.9) | 4853 (2.7) |
Heart | 14 (0.03) | 3604 (3.7) | 135 (0.3) | 2646 (2.9) | 40 (0.03) | 584 (0.3) |
Lung | 12 (0.02) | 2507 (2.6) | 56 (0.1) | 2007 (2.2) | 1 (0.0) | 463 (0.3) |
Pancreas | 5 (0.01) | 1236 (1.3) | 24 (0.04) | 890 (1.0) | 1 (0.0) | 143 (0.1) |
Small Bowel | 0 (0.0) | 147 (0.2) | 4 (0.01) | 43 (0.05) | 0 (0.0) | 1 (0.0) |
Total Organs | 586 (1.2) | 49,779 (51.4) | 7885 (14.7) | 41,299 (45.7) | 8536 (6.1) | 18,585 (10.2) |
Absolute numbers and rates of the organ transplant activities per WHO region. 2015 [17].
World map of transplantation in 2019 showing total sum of transplants [from global Observatory of Donation and Transplantation].
Kidney transplants are available in 102 countries; living kidney transplants in 98 countries and deceased donors in 76 countries [16]. Sixteen countries representing 6.6% of the global population perform only living donor kidney transplants. In SSA, a handful of countries carry out transplantation: South Africa, Sudan, Seychelles, Ivory Coast, Namibia, Nigeria, Kenya, Ghana, Tanzania, Mauritius, Ethiopia but only five countries (Ethiopia (0.34 pmp), Kenya (1.51 pmp), Nigeria (0.47 pmp), South Africa (6.81 pmp) and Sudan (6.58 pmp)) report their data to GODT (Figure 2).
Sub-Saharan Africa is heterogeneous and has a population estimated at 1.1billion [18]. It is projected that countries in this region would account for more than half of the world’s growth by 2050 [19]. This geographical region fully or partially located south of the Sahara Desert occupies an area of about 24 million Km2 (Figure 3). It is made up of 47 countries divided into 4 WHO sub-regions. Most countries in this region belong to the LICs and LMICs according to World Bank Classification of economies and are also described as LRCs. Africa is the second largest and second most populous continent; SSA occupies about 80% of the continent [20]. Although the economic growth in Africa has been remarkable in recent years, the gap between the rich and poor is wide and many people still do not have access to basic amenities such as potable water, good sanitation and basic health services [20].
Map of Africa showing UN sub-regions.
The WHO defines health systems as “all organizations, people and actions whose primary intent is to promote, restore, or maintain health” [21]. In LRCs, these systems have long been weak and deficient in most aspects of healthcare delivery and therefore, there is persistent need to evaluate health system challenges at all levels [22]. Health security is a crucial public health issue. It is ensured when there is protection against any health threats and also involves ability to handle emerging new health conditions by adapting and developing new approaches [23]. The epidemics in recent years (SARS, MERS and Ebola) including the COVID-19 pandemic bring to the fore the inability of the health systems in SSA to cope with health crisis and other prevalent health conditions [24].
Some healthcare professionals have poor work ethics deriving from unsavory work environment and remunerations. Transplantation is a highly specialized service that entails full commitment of the workforce and long work hours. For a good transplant programme, the national health system and the hospitals have to commit to improving the skill set of the work force through adequate staff training and other development opportunities, incentivization of the programme and offering a very supportive work environment [25].
Traditions and cultures influence the mindset of a people; decision to access healthcare service is informed by many factors (accessibility, affordability, spirituality and religiosity, and knowledge of the disease condition) [26]. When ill, many people in LRCs seek alternative healthcare service including traditional health providers and religious institutions resulting in late presentation to hospitals [27].
In 2018 and 2019, Africa’s economic growth was at 3.4% and was expected to rise to 3.9% and 4.1% in 2020 and 2021 respectively [28]. Amid the COVID-19 pandemic of 2020, the dynamics changed resulting in contraction of economies globally with expected 1.7% to 3.4% contraction of Africa’s economy [29].
The 2001 Abuja Declaration recommended allocation of 15% of the annual national budget to the health sector; achieving this has been challenging [30]. In 2012, 6 countries met the target; and this reduced to 4 in 2014. Currently, the preferred indicator for health financing is the percentage gross domestic product (% GDP). To achieve universal health coverage (UHC), the World Health 2010 Report suggested that a national government has to spend at least 4–5% of GDP on health [31]. Whilst per capita expenditure on health in America and Europe were over $1800 in 2014, the per capita expenditure on health in Africa averaged only $51.6 [32]. Further analysis shows that over the same period, in Africa, general government health expenditure was less than 50% of the total health expenditure while other sources such as out of pocket (OOP) payments and external sources (from funders) accounted for over 50% [32]. In general, transplantation service largely depends on robust and adequate finances hence the programme thrives in HICs and UMICs.
South Africa: the first organ transplantation in Africa was kidney transplant performed by Thomas Starlz and colleagues in 1966 at Wills Donald Gordon Medical Centre, Johannesburg, South Africa [33]. This was followed in 1967 by the first successful heart transplant performed in the world at Groote Shuur Hospital, Cape Town, South Africa by Christian Barnard [34, 35]. Barnard and his team championed the orthotopic and heterotopic (‘piggy-back’) heart transplant. From 1968 to 1983, they engaged in research on cardiac transplantation thereby laying the foundation for heart transplantation as therapy for end-stage cardiac disease. The team advanced the concept of brain death, organ and tissue donation, and ethical issues in transplantation. They also researched on methods to improve preservation and protection of the donor heart: their studies ranged from developing appropriate hypothermic perfusion for heart storage, haemodynamics and metabolic changes in brain death to xenotransplantation [34].
Though, South Africa has the most advanced transplant programme in the continent, globally, their transplant activities remain lower than those of other countries with comparable economic capacity [35, 36]. South African liver programme has existed for about 2 decades and presently offers living-related liver transplantation. Other solid organ programmes available are combined kidney-pancreas and lung transplantation. Her donor programmes have advanced to extended criteria donors (ECD) and donors after circulatory death [37]. South Africa has high prevalence of HIV resulting in a huge HIV-positive population prompting Muller and colleagues to pioneer HIV-positive-to-positive transplant program in 2008 [38]. By 2018, this programme had successfully transplanted 43 kidneys from 25 deceased donors [39].
Namibia had first kidney transplantation in March 2016 [40] and is also reported to have done a heart transplant [41].
Ghana started a kidney transplant programme in 2008 at Korle Bu Teaching Hospital, Accra in collaboration with a hospital and a charity organization in UK. Between 2008 and 2014, the programme performed 17 transplants and in 2015, they established a national registry [42].
Ivory Coast implemented the law authorizing organ donation in 2012 [43] and between 2013 and 2015, ten living-related kidney transplantations had been done [44].
Nigeria commenced organ transplantation activity in 2000 in a privately-owned hospital [45]. Currently, there are 15 centres (public 9, private 6) and over 770 transplants had been performed between 2000 and 2019 [Personal Communication].
Ethiopia commenced its transplant programme in collaboration with an American hospital in September 2015 and by February 2018, had done 70 living donor kidney transplants at their only transplant centre [46].
Kenya started kidney transplantation in 2009 and by 2019 had performed 200 transplants. Their government augmented the existing infrastructures to support 10 transplants per month [47].
Mauritius began kidney transplantation in 1980 and discontinued in 1982 following poor outcomes but resumed in 1993 [48]. Although the “Human Tissue (Removal, Preservation and Transplant) Act” was promulgated in 2006 and amended in 2013, a new legislation was enacted in 2018 [49].
Sudan, according to the African Union belongs to East African sub-region even though the United Nations categorized her as North Africa. Sudan had her first kidney transplant in 1974 and for the subsequent 25 years performed very few transplants. However, in 2000, the program was reactivated; and 222 transplants were performed in 2016 [50].
Tanzania started kidney transplantation services locally in collaboration with hospitals in India and Japan in November 2017 [51]. Earlier, her program consisted of government-sponsored transplantation overseas. Recipients and donors received pre-transplantation work-up locally and donor verification by DNA profiling was done to curtail commercialization.
Ugandan cabinet in June 2020 approved a bill to establish a legal framework for human organs, cells and tissue transplant, and to regulate donations and trade in human organs, cells and tissue [52].
No country in this sub-region has a transplant programme but Angola in March 2019 passed a law on human tissue, cell and organ transplant to enable transplantation [53].
In SSA, the national programs for donation and transplantation of organs and tissues are slow and poorly developed and they are fraught with inadequacies in infrastructures, institutional support, and technical expertise [3]. These are attributed to the huge costs and complexity of transplantation, low GDP, lack of subsidy and dearth of facilities.
Loua et al in 2018, documented that 62 transplant centres across seven countries in Africa had transplant activities involving kidney, heart, cornea, liver and bone marrow [3].
Programmes are classified into different stages of development of transplant services with those from HICs better developed than those from LMICs and LICs [54] (See Table 3).
Stage | Characteristic | Country |
---|---|---|
I | No existing transplant programme with little or no posttransplant and post-donation care. Transplant tourism is rife. | The poorest countries of the world |
II | Faltering or poorly developed transplant programme offering only living-related donation, no nationally structured transplant program, and often no legislation. There is nonexistent deceased-donor program and proliferation of transplant tourism with little or no posttransplant and post-donation care. | Countries in sub-Saharan Africa and many other low- and middle-income countries |
III | Fairly developed transplant programme offering mostly living-related donation with rudimentary deceased-donor program. Poorly developed kidney paired exchange and organ sharing programs, often with poor posttransplant and post-donation care. Some level of transplant tourism and moderate to long wait time. | Many countries in Asia, Central and South America, the Middle East, and North Africa |
IV | Well-developed structured transplant programme and accompanying legislation offering deceased donation, kidney paired exchange, and organ sharing programs with good posttransplant and post-donation care. Little transplant tourism and short to moderate wait times for transplant. | Many of the developed economies belong to this stage |
V | Highly developed and structured transplant programme and accompanying legislation offering mostly deceased donation, advanced donation/kidney paired exchange, and organ sharing programs with excellent posttransplant and post-donation care. There is no transplant tourism and short or no wait times for transplant. | Utopian |
Proposed staging for transplant stratification model (transplant transition) [54].
Careful evaluation of potential organ transplant recipients is necessary to detect co-existing illnesses that can adversely affect the prognosis of the transplantation. The subsisting clinical practice guidelines including the 2020 KDIGO guideline and the 2011 UK Renal Association Clinical Practice guideline (5th Edition) [55, 56] recommend the standard process of evaluation of prospective transplant recipients. Regardless of the recommendations of the practice guidelines, most transplant centres have their in-house protocols for transplant recipient evaluation. However, in SSA, the evaluation may be tailored to the available resources but should be efficient and cost-effective. The discussion below is typical for kidney transplant units in Nigeria but may apply to other organ transplantations and transplantations in other countries in the sub-region.
The evaluation of such candidates involves risk/benefit assessment and they should have at least five-year life expectancy derived from age, gender and race of the individual [57]. Many clinicians, however, consider other factors including severity of life-threatening diseases, functional status, clinical experience and knowledge of the patient to determine suitability for organ transplantation.
The workup evaluation includes: hematological, clinical chemistry, infection profile, diagnostic procedures, imaging and immunological tests. The list of relevant investigations is shown in Table 4.
Blood |
|
Radiology |
|
Urine |
|
Immunology |
|
Gynecological |
|
Other tests |
|
Workup for prospective organ transplant recipients.
Blood grouping establishes the candidate’s blood type and determines if further evaluation should proceed. Recipient and donor must be compatible. Complete blood count and clotting profile should be optimal.
All candidates are assessed for presence of cardiac disease by history, physical examination and electrocardiogram. Recipients with cardiac disease, comorbidities that predispose to coronary artery disease (CAD), history of previous CAD or poor cardiac function are further assessed by cardiologists. Generally, contraindications for transplantation include severe heart disease (New York Heart Association [NYHA] Functional Class III/IV), severe CAD, left ventricular dysfunction [ejection fraction <30%] and severe valvular disease.
Chest radiograph is required for all candidates while chest computerized tomography (CT) is reserved for current or former heavy smokers (≥ 30 pack-years). Candidates with lung disease are further evaluated by a pulmonologist. Severe irreversible obstructive or restrictive pulmonary diseases are contraindications for transplantation.
Sub-Saharan Africa has high prevalence of tuberculosis (TB). It is therefore necessary to screen for TB in prospective organ recipients with a chest radiograph and purified protein derivative (PPD) skin test. Candidates with positive TB screening tests are treated before organ transplantation.
Candidates with history of peptic ulcer disease (PUD) are screened with oesophagogastroscopy and Helicobacter pylori test. Active diseases including PUD, diverticulitis, pancreatitis, cholelithiasis and inflammatory bowel disease should be controlled before transplantation.
Serological tests for potentially transmissible diseases, like HIV, HBV, HCV, cytomegalovirus (CMV), Epstein–Barr virus and varicella-zoster virus are usually performed, and appropriate management instituted when indicated.
Routine cancer screening is done for all recipients. Chest radiograph is mandatory while chest CT is reserved for current or former heavy smokers. Ultrasonography is used for screening candidates at risk of renal cell carcinoma (dialysis >3 years, family history of renal cancer, acquired cystic disease, analgesic nephropathy). Those at risk of urinary bladder cancer (high-level exposure to cyclophosphamide, heavy smoking) require cystoscopy. Patients at risk of hepatocellular carcinoma are screened with ultrasonography and serum alpha fetoprotein. Colonoscopy is done to screen for bowel cancer and inflammatory bowel disease. Females undergo PAP smear and mammography to exclude cervical and breast cancer respectively.
Obesity increases the risk of post-operative complications. Many transplant centres prefer a body mass index (BMI) of <30.
These are very important aspects of the workup for prospective organ transplant recipients and will be discussed later.
Donor protection should always be taken into account during living donor selection and assessment. Organ donation should be altruistic, voluntary and never coerced. Donor evaluation is a multidisciplinary exercise, and is done before, during and after donation. Due to lack of requisite legislation, supporting infrastructure, religious and cultural beliefs, mostly living organ donations are done in SSA countries.
There are risks associated with organ donation and consequently, potential donors should receive medical, surgical and psychological screening. Pre, intra, and post-operative care as well as structured post-donation follow up are important.
Potential donors should be healthy and neither too young nor too old. Medical history and physical examination could elicit risk factors for kidney disease such as: DM, hypertension, family history of kidney disease, herbal drug, non-steriodal anti-inflammatory drugs (NSAIDs), and other nephrotoxin use. History and/or presence of CLD could be suggested by jaundice and alcohol abuse. Also, history of psychiatric illness, malignancies, smoking and substance abuse, etc. should be sought and positive candidates excluded. Donors should not be morbidly obese and blood pressures should be <140/90 mmHg.
For various investigations see Table 5.
Parameters | Relevant indices |
---|---|
Age | >18, <60 years |
History | Diabetes mellitus, hypertension, nephrotoxins, alcohol and other substance abuse, cigarette smoking, psychiatric illness, malignancy |
Physical features | Jaundice, pallor, BP >140/90 mmHg, BMI >35 |
Laboratory features | |
Hematological | FBC, PT/INR |
Chemistry | SEUCr, LFT, lipid profile, FBG, HBA1C, PSA, TFT |
Microbiology | Urinalysis, urine culture |
Serological/ immunological | HIV, Anti HCV, HBsAg, CMV, EBV, ABO blood group, HLA A, B and DR matching, HLA antibody cross- matching |
Imaging | Ultrasound, CT angiography, |
Others | ECG, Echocardiography |
Workup for potential organ transplant donors.
Absence of urinary markers of disease such as proteinuria, haematuria, pyuria and casts, may rule out kidney diseases in potential donors. Glomerular filtration rate (GFR) should ideally be measured but is often estimated using serum creatinine in most LRCs. Prospective donors are screened for chronic viral diseases. Notably, CMV positivity in a donor has implication for a CMV-negative recipient, who due to subsequent immunosuppressive drug use will likely succumb to its infection. Screening for TB (CXR, Mantoux test, sputum GeneXpert) is important in SSA because 1/3 of the population is infected with M. tuberculosis [58]. The ABO blood group compatibility with recipient is mandatory; however, Rhesus factor mismatch is not a major consideration for solid organ matching. There are many HLA antigens (Class I: HLA-A, B, and C; Class II: HLA-DR, DQ and DP), but the HLA A, B and DR are usually cross-matched between donors and recipients (i.e. tissue typing).HLA antibody cross-matching is important to prevent early graft rejection. It detects the presence of HLA antibodies in recipients that can react with donor’s lymphocytes, i.e. donor specific antibodies (DSA).
HLA antibody cross-matching was originally based on complement dependent cytotoxicity (CDC) assays. It is done with recipient’s serum on donor lymphocytes or pooled lymphocytes of previous donors within the transplant centre’s population to determine the Panel Reactive Antibodies (PRA). Reactive Antibodies (PRA). The PRA estimates the recipient’s chances of tolerating allografts from that population and is useful for deceased donation.
Solid phase assays, ELISA or flow cytometry (Luminex)-based are now available and preferred. Most transplant centres in SSA, outsource tissue typing and HLA antibody cross-matching. Protocols require at least two HLA antibody cross-matches, with the last, just before the transplant procedure.
Imaging evaluation using ultrasonography and doppler in prospective donors should demonstrate normal kidneys (sizes and echotexture) and renal blood flow.
The CT-angiography helps to rule out solitary kidney or detect the presence of multiple or abnormal renal arteries, which have surgical implications for nephrectomy in donors and anastomoses in recipients.
Counseling donors on short and long-term risks associated with organ donation is necessary. Possible complications such as pain, post-operative infections, blood loss, deep venous thrombosis and pulmonary embolism can occur. Studies have shown that peri-operative mortality and morbidity during organ donation, are about 0.03% and 10% respectively [59]. Some studies show that with careful selection, kidney donors live long, although hypertension, proteinuria and reduced GFR can occur over time [60]. The risk of ESKD following kidney donation is about 0.3% [61]. Emotional consequences after organ donation should be anticipated therefore psychosocial assessment should be independently organized by the transplant team before and after donation.
Many transplantation programmes in SSA adopt protocols from established and experienced centres.
According to US Organ Procurement and Transplantation Network (OPTN) guidelines, living donor follow-up is done at discharge (or at 6 weeks), 1 year and 2 years [62]. Parameters monitored include weight, blood pressure, lipid profile, kidney and liver functions. Healthy eating, regular exercise and the dangers of substance abuse are emphasized. After uneventful 2 years, donor follow-up is continued by the primary care physicians but for those with adverse outcomes appropriate referral is made. Post-donation follow-up is important for donor safety and wellbeing to enable diagnosis and treatment of co-morbidities.
In transplantation, recipients, donors and their families are faced with various challenges including psychological and behavioral issues. Evaluation is essential in the following aspects: candidate and donor selection, counseling, pre- and post-transplant assessment, patient, caregiver and family adjustments to transplant and issues related to psyche of transplant staff.
Various factors exert neuropsychiatric effects in transplantation. Studies link significant neuropsychiatric adverse effects to cyclosporine, tacrolimus, steroids and other components of treatment. Therefore, psychosocial issues should be considered and addressed in order to achieve a successful transplant.
Psychosocial evaluation of patients for transplant include [63]:
Patient profile: relationships, education, work and legal history
Expectations from the surgery
Organ failure: cause, complications, course, adherence to treatment
Ways of coping with the illness
Support network: caregivers, family, friends, faith organizations and employers
Psychiatric history: extant, past and family.
Substance abuse history
Mental status exam: neuropsychiatric tests
Ability to give informed consent
There are known stressors before and after transplantation including depression and hopelessness, anxiety, uncertainty and aggression. These may be followed by hope, and confidence in an unpredictable pattern as recipients gradually process adaptation to the new situation.
After Transplantation, recipients pass through three phases of adaptation [64]:
“Foreign body” phase: the organ feels strange to the recipient. Persecution anxiety or idealization could arise. The organ could be seen as fragile and precious, thereby generating excessive protective feelings towards it.
“Partial incorporation” phase: recipient begins to integrate the organ.
“Total incorporation” phase: recipient is no longer aware of the organ.
In the long-term postoperative period, medication side effects and associated comorbidities become central stressors affecting the recipients’ quality of life (QOL). The most bothersome stressors are work related, like farming, schooling, etc. [65]. Recipients might feel stressed by the strict adherence to the medical regimen. This, in turn, can compromise their adherence after transplantation. Financial problems and legal disputes constitute other possible sources of psychological strain with health or pension insurance agencies, where available.
Enabling transplant recipients commence productive employment constitutes the main goal of transplantation and is considered an indicator of societal participation [66]. Globally, data show that 18% - 86% of recipients return to work or find new employment. [67, 68] but no data is available for SSA.
Multiple factors motivating donors include intrinsic factors (e.g., desire to relieve another’s suffering or to act in accordance with religious convictions) and extrinsic factors (social pressures or perceived norms) that may operate simultaneously. The combination of motivational forces differs depending on whether and how the donor is related to the recipient.
Most living donors use two decision-making strategies: [69]: “moral” which involves awareness that one’s actions can affect another [70] and “rational” which is focused on gathering relevant information, evaluating alternatives, selecting an alternative, and implementing the decision.
Potential donors’ psychological stability has been one of the greatest concerns for living transplant programmes, particularly in the context of unrelated donation. The willingness or desire to donate to a stranger has been historically viewed with suspicion [71, 72]. Studies suggest that most potential donors do not suffer from mental illness. [73, 74]. Many donors have reported positive feelings about donation however, a few have observed psychological distress, anxiety and depression. Thus, it becomes critical to identify, and mitigate key risk factors for these poorer outcomes: non-first degree relatives [75, 76], ambivalent donors [76, 77] and “black sheep” donors (persons who donate in order to compensate for past wrong doings or to restore their position in the family) are at higher risk for poorer post-donation psychosocial outcomes [76, 77].
The donor kidney angiogram is decisive in selecting the kidney to be harvested. The larger kidney with better blood flow is left for the donor. Minimal access donor nephrectomy and robot-assisted renal engraftment reduce postoperative complications. These, however, are not easily available in most LRCs.
The harvested kidney is covered in ice slush, wrapped in gauze piece and preserved in ice container as organ perfusion machine is not readily available in the sub-region.
Kidneys with multiple arteries are avoided but if inevitable, arteries are anastomosed side to side, end to side, or separately onto the external iliac artery (Figure 4). The right external iliac vessels are more superficial than the left and this side is frequently preferred for the first renal engraftment.
Donor angiogram with multiple left renal arteries.
Anti-reflux uretero-cystostomy is performed over a size 4Fg double J-ureteric stent (Figure 5).
End-to-side donor-recipient arterial anastomosis with kidney wrapped in gauze piece packed with saline ice slush.
Sclerosed External Iliac Vein (EIV): this results from repeated cannulation of EIV for hemodialysis. Recipient pre-operative EIV doppler ultrasound scan for patency is important. Major complications of recipient engraftment include bleeding, delayed graft function, hyperacute rejection and allograft renal vein thrombosis.
Immunosuppressive regimen is divided into induction and maintenance phases.
This is required to prevent acute rejection. Due to sensitization from blood transfusions, previous pregnancies (females) and increased susceptibility to graft rejection (in blacks) recipients undergo induction [81]. A combination of anti-thymocyte globulin (ATG) and methylprednisolone is often used. Prior to this, patients receive pretreatment with acetaminophen and antihistamines to prevent cytokine release syndrome associated with ATG.
Biologic agents (Alemtuzumab, Basiliximab, Daclizumab) may be used when available in less sensitized patients.
To prevent allograft rejection, maintenance immunosuppression is achieved with a combination of low dose corticosteroid (prednisolone is widely in available SSA), an antiproliferative agent (mycophenolate mofetil (MMF) or azathioprine) and a calcineurin inhibitor (CNI) (tacrolimus (TAC) or cyclosporine (CYP)). Tacrolimus has shown superiority over cyclosporine in improving graft survival and preventing acute rejection. Thus, TAC remains an integral part of the common post- transplant immunosuppressive combination [82]. The initiating dose is titrated to achieve a trough level of 8-10 ng/ml in the first three months post-transplant.
Prophylaxis against bacteria, fungi and viruses are commenced within this time.
First day post-surgery, emphasis is on haemodynamic and respiratory stability as well as urine output. By the first week, good graft function should have been established and urethral catheter is removed.
Within this period opportunistic infections are anticipated and appropriate measures taken. The ureteric stent is removed within 4 – 6 weeks.
Absence of transplant registries in SSA precludes transplant data availability. However, between 2010 and 2015, a hospital in South Africa documented recipient survival at 1 and 5 years as 90.4% and 83.1% and that of graft 89.4% and 80% respectively [83].
Organ donation and transplantation in SSA is fraught with numerous challenges including costs of treatment, inadequate infrastructure and equipment, dearth of highly skilled health professionals, and lack of well-articulated ethico-legal framework and policies [3].
Cost of kidney transplant varies from country to country. For example, the cost is estimated at about $32,000 in Nigeria [84], $18,775 in Ghana [85], and $10,000 in Tanzania [20].
Source of funding for organ and tissue donation and transplant depends on the country: public sources in Ethiopia, Ghana, Mali, Seychelles and Comoros but private in Nigeria, Burkina Faso, Madagascar and 10 other countries SeeTable 6. Most recipients pay OOP either personally or by relatives, employers and to a lesser extent philanthropists [45]. While the National insurance pays two-thirds of the transplant cost in Kenya [47], it is free in Tanzania [51].
Indicator | Countries |
---|---|
Countries with functional transplantation programmes | |
Functional transplantation programmes from living donors | Algeria, Côte d’Ivoire, Ethiopia, Ghana, Kenya, Namibia, Nigeria, United Republic of Tanzania, Uganda, South Africa |
No. of transplant centres in the region | |
Kidney centres | Algeria, Côte d’Ivoire, Ethiopia, Ghana, Kenya, Namibia, Nigeria, United Republic of Tanzania, Uganda |
Corneal centres | Kenya, Nigeria, South Africa |
Bone marrow centres | Nigeria, South Africa |
Liver centres | South Africa |
Heart centres | South Africa, others perform open heart surgeries |
Countries having legal requirements | |
Legal requirements in place covering organ donations and/or transplantations | Burkina Faso, Comoros, Côte d’Ivoire, Ethiopia, Kenya, Mauritius, Namibia, Nigeria, Rwanda, Senegal, Sudan, United Republic of Tanzania, Uganda, Zimbabwe |
Governments intended to adopt new legal requirements | Cameroon, Chad, Eswatini, Ghana, Guinea, Madagascar, Mali, Mozambique |
No legislations in place | Angola, Benin, Burundi, Cabo Verde, Congo, Eritrea, Gabon, Guinea Bissau, Seychelles, Sierra Leone |
Legal requirements in place to inform living donors on the risks of the operation | Comoros, Ethiopia, Kenya, Mali, Nigeria, Rwanda, Senegal, Seychelles, United Republic of Tanzania, Uganda |
Legal restrictions on the coverage of donation costs for living donors | Comoros, Mali, Rwanda, Senegal |
Legal requirement to follow-up on the outcomes of living donors | Ethiopia, Mali, Senegal, Seychelles |
Legal requirement to provide care to living donors in case of adverse or medical consequences | Ethiopia, Senegal, Seychelles |
Prohibition of organ trafficking/transplant commercialization | Burkina Faso, Comoros, Côte d’Ivoire, Mali, Namibia, Nigeria, Rwanda, Senegal |
Legal permit and regulation of financial incentives for living donors | None |
Import or export of organs authorized | Ghana, Namibia, Rwanda |
Import or export of organs explicitly prohibited | Burkina Faso, Seychelles |
Legal requirements for organ and tissue donations from living donorsa | Burkina Faso, Comoros, Côte d’Ivoire, Kenya, Mali, Nigeria, Rwanda, Senegal, Seychelles, United Republic of Tanzania, Uganda |
No. of countries having an organization and management system | |
Authorization for transplant services | Burkina Faso, Comoros, Côte d’Ivoire, Ethiopia, Ghana, Guinea, Kenya, Madagascar, Mali, Nigeria, Senegal, Uganda, Zimbabwe |
Ethics Committees at the national or local level | Burkina Faso, Comoros, Côte d’Ivoire, Ethiopia, Gabon, Kenya, Mali, Nigeria, Rwanda, Senegal |
Government recognized authority at the national level | Algeria, Côte d’Ivoire, Ethiopia, Ghana, Kenya, Mali, Nigeria, Senegal, Uganda |
Setting up protocols, guidelines, recommendations | Comoros, Côte d’Ivoire, Ethiopia, Mali, Senegal |
Transplant follow-up registries for post-transplant living donor and for recipients | Côte d’Ivoire, Ethiopia, Namibia, Uganda |
Affiliation with an international organ allocation organization | None |
Cooperation framework to allow transplantation abroad | Côte d’Ivoire, Ethiopia, Kenya, Namibia, United Republic of Tanzania, Uganda |
Training programme for staff in place | Côte d’Ivoire, Ethiopia |
Source of funding | |
Public | Comoros, Ethiopia, Ghana, Mali, Seychelles, United Republic of Tanzania |
Private | Côte d’Ivoire, Ghana, Nigeria |
Public and Private | Kenya, Namibia, South Africa, Uganda |
Not Specified | Eswatini, Gabon, Zimbabwe |
Aspects of transplantation programmes in SSA modified from Loua et al [3].
Post-transplant maintenance of immunosuppression is a major challenge. This is exigent since therapy must be individualized. Two perspectives associated with immunosuppression in SSA include:
Availability, affordability and patient’s adherence to prescription.
Therapeutic drug monitoring (TDM).
Adequate immunosuppression is key to allograft survival. In patients who pay OOP, prohibitive costs of medications may have negative impact on their finances. Furthermore, side effects of medications affect their health-related QOL. In many LRCs, these medicines are imported at high cost and not readily available. These contribute to poor adherence with subsequent allograft rejection and graft loss.
Despite their impactful role in improving transplant outcome and graft survival, immunosuppressive medicines exhibit narrow therapeutic range between levels that inhibit rejection and toxic levels hence TDM is often required. Establishing a patient’s dose requirements in the immediate post – surgery period and avoiding over immunosuppression remains a challenge. Calcineurin inhibitors have variable pharmacokinetics [86, 87, 88, 89]. While ethnic differences have not been demonstrated in pharmacokinetics of MMF and AZA, African Americans have been shown to have 20–50% lower oral bioavailability for TAC, CYP, sirolimus and everolimus and as such require higher drug doses than Caucasians [90, 91]. This has been attributed to genetic polymorphism of key enzymes in the metabolism of these medications [90]. Genetic profiling is not readily done in SSA hence, TDM is essential. This attracts huge costs for the health system and for patients who pay OOP. It is imperative to tailor medications to patient’s need. Some countries do not have the capacity to analyze drug levels, so patient’s blood samples are sent overseas for analysis. Within the first-year post-transplant, TDM is done at least twice during timed follow-up visit for patients coming from rural and urban areas. However, more frequent monitoring is done when indicated. During emergency presentation for allograft dysfunction, patients are admitted, samples for TDM sent out and other possible causes of allograft dysfunction are excluded or managed if present. Decision to increase drug dosage is often delayed till TDM result is available but dose reduction or withdrawal can be done in the presence of overt signs and symptoms suggestive of toxicity. For subsequent years, TDM is done as indicated.
Tissue typing, cross-matching and some viral studies, which are major aspects of patient preparation, are done overseas. This tends to delay the procedure and leads to an increase in the cost of transplantation. Adequate histological evaluation of biopsy specimens are largely unavailable, making prompt management of rejections and infections problematic.
Health-workforce is the backbone of any health care system. Transplantation involves collaboration of many health professionals (nephrologists, transplant surgeons, urologists, renal nurses, pathologists, etc.). Worldwide transplant workforce and training capacity remain unknown. Of the 47 countries in SSA, only 15 (32.6%) had data on the number of nephrologists in their countries. Nigeria and South Africa have the greatest number of nephrologists with rates <10 per 10,000 population while others have < two per 10,000 population [3]. The situation is worse for other specialists involved in transplantation. Opportunities for training and employment have caused brain drain to developed countries from LRCs [3].
Despite the burden of ESKD in SSA, only few countries have sustained transplant programmes [20]. There are only 62 centres across 7 countries in SSA [3]. Nigeria with a population of 206 million has 15 renal transplant centres (RTCs) with majority recording low activities ranging 1–5 transplants per year (Personal Communication). South Africa with a population of 59.37 million (2020) has 14 RTCs and did 250 to 450 kidney transplants annually between 1991 and 2015 [35].
Scarcity of organs for transplantation is a multi-factorial global problem. Living donors remain the major source of organs for transplantation in SSA with largely non-existent deceased donor programmes. This has resulted in the persistent dearth of organs in the face of continuous rise in demand [92]. Unavailable storage facilities, poor knowledge about transplantation, socio-cultural and religious beliefs (which discourage living organ donation, view deceased organ donation as a taboo or an act of mutilating the dead with violation of the person’s dignity [84]) contribute to shortage of organs [93].
There is pervading poverty in SSA with US bureau of statistics reporting rates of 87.8%, 56.9%, 40.1%, 40% and 36.1% in Uganda, Ghana, Nigeria, Cameroun and Kenya respectively [94]. In Nigeria, 85% of ESKD patients earn between $800–7333 annually making kidney transplantation unaffordable [27, 95]. Although unemployment rate in SSA averages 6.2%, many are underemployed and earn low income [96].
Most transplant centres are located in urban cities or state capitals reducing accessibility to rural dwellers [3, 41].
Christianity, Islam and African traditional religion are the major faiths in SSA. Interplay of faith, religion and cultural attitudes and their relationship with views on organ donation is complex. Response to illness as God’s will negates organ donation or reception. Belief in resurrection and reincarnation precludes organ donation since the ‘new body’ may have some missing parts. Desecration of the body of the deceased is reported as a factor prohibiting family members from donating body parts of their deceased relatives.
Functional organizational mechanism for transplant programmes including authorization for transplant services; ethics committees, guidelines and protocols, etc. are few in the region [41, 93]. Additionally, transplant is not sufficiently integrated into national health services and collaboration between SSA countries is limited.
Absence of functional and reliable registries militate against planning and implementation of policies due to lack of data. Most countries do not include performance indicators for organ donation and transplantation in their national health information systems. In addition, there is insufficient multisectoral (schools, transport departments, NGOs, Civil Society Organizations, etc.) involvement in transplantation programmes in SSA.
Some countries have legislation for organ donation and transplantation while others are in various stages of developing theirs (Table 6). The weak regulatory frameworks observed in these countries are often insufficient to ensure the effective oversight needed for the implementation of quality standards for organ transplantation.
The Declaration of Istanbul defines organ transplant tourism as travel for transplantation involving trafficking in persons, for the purpose of organ removal. Organ trafficking is defined as “the recruitment, transport, transfer, harboring, or receipt of living or deceased persons or their organs by means of any form of coercion, of abduction, of fraud, of deception, of the abuse of power or of a position of vulnerability, or of the giving to, or the receiving by, a third party of payments, or benefits to achieve the transfer of control over the potential donor for the purpose of exploitation by the removal of organs for transplantation [97].” Transplant commercialism is the buying and selling of organs i.e. treating of organs as commodities. Travel for transplantation is the transport of organs, donors, recipients, or the professionals across borders for transplantation and it becomes TT if it entails organ trafficking and/or transplant commercialism [97]. Transplant tourism has become an increasing component of medical tourism (MT) especially in SSA. The disparity between the demand for and supply of organs encourages illegal organ procurement as transplantation may the only life-saving treatment in many end-organ failure. Unavailability and high cost of healthcare, lack of faith in local health systems, widening economic gap, ease of global travel and uneven global application of laws, have led to increase in TT.
Transplantation holds lots of opportunities which if well harnessed can improve healthcare in SSA.
For sustainable transplantation programme, individuals, community and governmental commitment and collaboration are required. Availability of organs can be increased through heightened public enlightenment campaigns emphasizing preventive medicine and change in the community’s organ donation perception. This can be achieved by partnering with religious bodies, individual, family and community education, inclusion of transplantation and donation in school syllabus, alliance with the department of motor vehicles (DMV) and novel donation programmes (kidney paired donation, extended criteria organ donation and altruistic non-directed donation).
Transplantation has significant medico-legal implications requiring robust legal framework. This should cover organ donation legitimacy, regulatory bodies, criteria and processes of accreditation, certification and standardization of transplant centres [98]. Transplantation programmes afford SSA opportunities to learn and adapt legislation from other regions. In 2008, Israeli parliament accepted two laws from their Ministry of Health - the Brain-Respiratory Death for determination of brain death and the Organ transplantation laws [99]. These laws defined the ethical, legal and organizational aspects of organ donation, allocation and transplantation with prioritization of registered donors, donor reimbursement and life insurance [99]. These and stoppage of illegal TT reimbursement significantly increased living and deceased organ donation by 2011 [99, 100].
The Multidisciplinary nature of transplant programmes demands highly skilled manpower often not obtainable in many parts of SSA, hence the need for collaboration with advanced transplant centres. Such patnership enables capacity development and training of specialized workforce which will serve the local and sister institutions.
Successful transplantation requires protocols for recipient and donor care. Transplant centres in LRCs can develop or adapt protocols from advanced centres, international organizations like United Network for Organ Sharing, Donation and Transplant Institute etc. National registries of organ transplant and outcomes are essential for documentation of transplant activities, reporting of short and long-term outcomes, and for planning and budgeting.
Each country should establish a sustainable transplant programme. Development of such services will curb organ trafficking and TT [101]. It entails infrastructural, legislative and manpower development with national government’s political will [35, 102]. A well-defined mode of funding which includes transplantation in national health insurance coverage ensures sustainability.
Transplantation programme can be established in a staged fashion [101]: enacting transplantation related laws and regulations, capacity building, extensive public enlightenment campaigns and transplant beginning with live-donor and subsequently, deceased-donor.
Models that can be adapted include:
In the Pakistani model [103, 104], following intense public enlightenment, the community assumed ownership of the programme through donations as individuals, communities and NGOs. Government provided 30–40% of required cost, infrastructure, staff training and emolument enabling patients to receive free nephrology and transplantation care plus post-transplant rehabilitation. Accountability, transparency and equity ensured the success of this model.
Following development of indigenous transplant programme in 1985, there was an unwieldy transplant waiting list necessitating government-sponsored live-unrelated transplant with donor compensation [105]. This programme successfully eliminated waiting list by 1999 increasing kidney transplantation to 28 pmp per year. The Dialysis and Transplant Patients Association facilitated donor-recipient matching excluding third party. Donors also received government-funded life health insurance and gifts. Government additionally supported importation and free distribution of immunosuppressive medications to recipients. Deceased donor transplantation has steadily increased since 2000.
These models emphasize the indispensable roles of community, government and NGOs in ensuring the existence of a sustainable transplantation programme.
The World Health Assembly (WHA) adopted resolutions WHA57.18 and WHA63.22 [106, 107], and the WHO guiding principles on human cell, tissue and organ transplantation to guide transplantation programmes and activities [108]. The United Nations General assembly adopted these resolutions to strengthen and promote effective measures and international cooperation to prevent and combat organ trafficking [109]. The Istanbul declaration on organ trafficking and TT recommends a legal and professional framework to govern organ donation and transplantation activities, transparent regulatory oversight system to ensure donor and recipient safety, enforce standards and prohibit unethical practices in all countries. [97]. A Task Force to check unwholesome practices in transplantation was set up and inaugurated by WHO in 2017 [110].
During the 2013 Global Alliance of Transplantation (GAT) meeting organized by Southern African Transplant Society in Durban [3], the transplantation society (TTS) sponsored a meeting for countries in SSA to assess the need for and ability to optimize or develop local transplant programmes. In 2015, the South African Renal Society–African Association of Nephrology in collaboration with European Renal Association-European Dialysis and Transplant Association held a pre-congress workshop to encourage SSA countries to develop renal registries [111]. Attempts at establishing renal registries in SSA have met with challenges. The International Society of Nephrology (ISN) is supporting establishment of renal registries worldwide through her SHARing Expertise (
To improve kidney disease patients’ care and capacity building worldwide, ISN pioneers these programs: fellowship, ISN continuing medical education, sister renal centre (SRC), sister transplant centre (STC) and educational ambassadors programme. Through ISN- TTS-STC program, ISN encourages establishment and development of transplant centres (
Improvement in the transplant landscape of SSA can be achieved by adapting models that have proven successful in LRCs such as those of Pakistan and Iran. Implementing the 2007 World Health Organization Regional Consultation recommendations: establishment of national legal framework and self-sufficient organ donation and transplantation in each country, transparent transplantation practices, and prevention of commercialized transplantation and TT will improve transplantation programmes in SSA. Also, adopting the WHO Regional Committee for Africa’s proposed actions on organ transplantation for member states and establishment of national registries for organ transplantation in each country are needed.
Sub-Saharan Africa, comprising of 47 countries and occupying an area of about 24 million Km2 is heterogeneous with estimated population of 1.1 billion people. Most of the countries belong to the LICs and LMICs according to World Bank Classification of economies. This region has a high prevalence of end-organ diseases including CKD, CLD, chronic lung diseases and chronic heart diseases resulting from CDs and NCDs.
Although South Africa performed Africa’s first kidney transplant in 1966 and pioneered heart transplantation in 1967, SSA lags behind the developed world in transplant activity. According to WHO, SSA contributes the least number of transplant activity per WHO World region. Cost of treatment, low GDP, inadequate infrastructural and institutional support, dearth of facilities and technical expertise and absence of subsidy have all adversely affected organ donation and transplantation.
The health-care systems in SSA are weak and deficient. Peoples’ decision to access healthcare services is influenced by knowledge of the disease condition, accessibility to health-care facility, affordability, religious and trado-cultural practices. Many people in LRCs patronize alternative healthcare service including traditional health providers and religious institutions as first choice resulting in late presentation to hospitals.
These challenges can be surmounted by adopting the 2007 World Health Organization Regional Consultation recommendations of establishment of national legal framework, self-sufficient organ donation and transplantation in each country, transparent transplantation practice, and prevention of commercialized transplantation and TT. In addition, establishment of national registries of organ transplantation is essential.
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