Research on health transition in Africa: time for action

With rapidly increasing globalization, trends towards unhealthy diets, obesity, sedentary lifestyles and unhealthy habits are resulting in an increased worldwide burden of chronic non-communicable diseases (NCDs). In Africa this means that health systems face the challenge of an increasing burden of NCDs and of continuing high morbidity and mortality from communicable diseases. This health transition represents an enormous challenge to Africa as the region with the least resources for an effective response. Whereas previous epidemics, including HIV, have caught Africa unprepared, the opportunity now arises to take the advancing wave of health transition in Africa seriously. Health research has a key role to play in meeting health and development goals, and must be responsive to changing disease patterns, such as health transition. There is an urgent need for research on health transition in Africa to enable countries to respond effectively to rapidly changing health needs

Health transition in Africa: practical policy proposals for primary care

Sub-Saharan Africa is undergoing health transition as increased globalization and accompanying urbanization are causing a double burden of communicable and noncommunicable diseases. Rates of communicable diseases such as HIV/AIDS, tuberculosis and malaria in Africa are the highest in the world. The impact of noncommunicable diseases is also increasing. For example, age-standardized mortality from cardiovascular disease may be up to three times higher in some African than in some European countries. As the entry point into the health service for most people, primary care plays a key role in delivering communicable disease prevention and care interventions. This role could be extended to focus on noncommunicable diseases as well, within the context of efforts to strengthen health systems by improving primary-care delivery. We put forward practical policy proposals to improve the primary-care response to the problems posed by health transition: (i) improving data on communicable and noncommunicable diseases; (ii) implementing a structured approach to the improved delivery of primary care; (iii) putting the spotlight on quality of clinical care; (iv) aligning the response to health transition with health system strengthening; and (v) capitalizing on a favourable global policy environment. Although these proposals are aimed at primary care in sub-Saharan Africa, they may well be relevant to other regions also facing the challenges of health transition. Implementing these proposals requires action by national and international alliances in mobilizing the necessary investments for improved health of people in developing countries in Africa undergoing health transition

Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

The inhabited zone of the Ugandan Rwenzori Mountains is affected by landslides, frequently causing loss of life, damage to infrastructure and loss of livelihood. This area of ca. 1230 km2 is characterized by contrasting geomorphologic, climatic and lithological patterns, resulting in different landslide types. In this study, the spatial pattern of landslide susceptibility is investigated based on an extensive field inventory constructed for five representative areas within the region (153 km2) and containing over 450 landslides. To achieve a reliable susceptibility assessment, the effects of (1) using different topographic data sources and spatial resolutions and (2) changing the scale of assessment by comparing local and regional susceptibility models on the susceptibility model performances are investigated using a pixel-based logistic regression approach. Topographic data are extracted from different digital elevation models (DEMs) based on radar interferometry (SRTM and TanDEM-X) and optical stereophotogrammetry (ASTER DEM). Susceptibility models using the radar-based DEMs tend to outperform the ones using the ASTER DEM. The model spatial resolution is varied between 10, 20, 30 and 90 m. The optimal resolution depends on the location of the investigated area within the region but the lowest model resolution (90 m) rarely yields the best model performances while the highest model resolution (10 m) never results in significant increases in performance compared to the 20 m resolution. Models built for the local case studies generally have similar or better performances than the regional model and better reflect site-specific controlling factors. At the regional level the effect of distinguishing landslide types between shallow and deep-seated landslides is investigated. The separation of landslide types allows us to improve model performances for the prediction of deep-seated landslides and to better understand factors influencing the occurrence of shallow landslides such as tangent curvature and total rainfall. Finally, the landslide susceptibility assessment is overlaid with a population density map in order to identify potential landslide risk hotspots, which could direct research and policy action towards reduced landslide risk in this under-researched, landslide-prone region.ISSN:1561-8633ISSN:1684-998

Field-based landslide susceptibility assessment in a data-scarce environment: the populated areas of the Rwenzori Mountains

The inhabited zone of the Ugandan Rwenzori Mountains is affected by landslides, frequently causing loss of life, damage to infrastructure and loss of livelihood. This area of ca. 1230 km2 is characterized by contrasting geomorphologic, climatic and lithological patterns, resulting in different landslide types. In this study, the spatial pattern of landslide susceptibility is investigated based on an extensive field inventory constructed for five representative areas within the region (153 km2) and containing over 450 landslides. To achieve a reliable susceptibility assessment, the effects of (1) using different topographic data sources and spatial resolutions and (2) changing the scale of assessment by comparing local and regional susceptibility models on the susceptibility model performances are investigated using a pixel-based logistic regression approach. Topographic data are extracted from different digital elevation models (DEMs) based on radar interferometry (SRTM and TanDEM-X) and optical stereophotogrammetry (ASTER DEM). Susceptibility models using the radar-based DEMs tend to outperform the ones using the ASTER DEM. The model spatial resolution is varied between 10, 20, 30 and 90 m. The optimal resolution depends on the location of the investigated area within the region but the lowest model resolution (90 m) rarely yields the best model performances while the highest model resolution (10 m) never results in significant increases in performance compared to the 20 m resolution. Models built for the local case studies generally have similar or better performances than the regional model and better reflect site-specific controlling factors. At the regional level the effect of distinguishing landslide types between shallow and deep-seated landslides is investigated. The separation of landslide types allows us to improve model performances for the prediction of deep-seated landslides and to better understand factors influencing the occurrence of shallow landslides such as tangent curvature and total rainfall. Finally, the landslide susceptibility assessment is overlaid with a population density map in order to identify potential landslide risk hotspots, which could direct research and policy action towards reduced landslide risk in this under-researched, landslide-prone region

Reconstruction of a flash flood event through a multihazard approach: focus on the Rwenzori Mountains, Uganda

© 2016, Springer Science+Business Media Dordrecht. The increased use of complex and holistic modelling for multi-hazard analysis is in sharp contrast with a lacuna in hazard analysis in equatorial Africa. This study aims to increase understanding of multi-hazard events in poorly documented regions with low accessibility. We focus on the Nyamwamba catchment (107 km2) located in the Rwenzori Mountains (Uganda) where on May 1, 2013, a severe flash flood occurred. In this region, wildfires, earthquakes and landslides occur as well. Here we reconstruct the circumstances under which this flash flood event was triggered, characterize the different processes acting upon the catchment dynamics and estimate the damaging effects of the flash flood within the catchment. The combined occurrence of intense rainfall, a forest fire having burned 18 % of the catchment area and the occurrence of 29 landslides providing debris to the river system, induced a debris-rich and very destructive flash flood which caused several fatalities, the destruction of 70 buildings, several bridges, a hospital, a school, a tarmac road and several lifelines. Although the methodologies applied to estimate peak discharge, detect landslides and delineate wildfires are well established in their disciplines and sometimes limited in their precision, their combination is required to demonstrate the importance of the wildfire and landslides for the magnitude of this flood, unprecedented in decades but characterized by a low return period of the triggering rainfall event. This indicates that flash floods should not be considered as self-determined phenomena but as a result of several cascading and interacting hazard processes.status: publishe

Landslide Diversity in the Rwenzori Mountains (Uganda)

status: publishe