Spatial-Explicit Modeling of Social Vulnerability to Malaria in East Africa.

Despite efforts in eradication and control, malaria remains a global challenge, particularly affecting vulnerable groups. Despite the recession in malaria cases, previously malaria free areas are increasingly confronted with epidemics as a result of changing environmental and socioeconomic conditions. Next to modeling transmission intensities and probabilities, integrated spatial methods targeting the complex interplay of factors that contribute to social vulnerability are required to effectively reduce malaria burden. We propose an integrative method for mapping relative levels of social vulnerability in a spatially explicit manner to support the identification of intervention measures. Based on a literature review, a holistic risk and vulnerability framework has been developed to guide the assessment of social vulnerability to water-related vector-borne diseases (VBDs) in the context of changing environmental and societal conditions. Building on the framework, this paper applies spatially explicit modeling for delineating homogeneous regions of social vulnerability to malaria in eastern Africa, while taking into account expert knowledge for weighting the single vulnerability indicators. To assess the influence of the selected indicators on the final index a local sensitivity analysis is carried out. Results indicate that high levels of malaria vulnerability are concentrated in the highlands, where immunity within the population is currently low. Additionally, regions with a lack of access to education and health services aggravate vulnerability. Lower values can be found in regions with relatively low poverty, low population pressure, low conflict density and reduced contributions from the biological susceptibility domain. Overall, the factors characterizing vulnerability vary spatially in the region. The vulnerability index reveals a high level of robustness in regard to the final choice of input datasets, with the exception of the immunity indicator which has a marked impact on the composite vulnerability index. We introduce a conceptual framework for modeling risk and vulnerability to VBDs. Drawing on the framework we modeled social vulnerability to malaria in the context of global change using a spatially explicit approach. The results provide decision makers with place-specific options for targeting interventions that aim at reducing the burden of the disease amongst the different vulnerable population groups

Regional climate projections in two alpine river basins: Upper Danube and Upper Brahmaputra

Projections from coarse-grid global circulation models are not suitable for regional estimates of water balance or trends of extreme precipitation and temperature, especially not in complex terrain. Thus, downscaling of global to regionally resolved projections is necessary to provide input to integrated water resources management approaches for river basins like the Upper Danube River Basin (UDRB) and the Upper Brahmaputra River Basin (UBRB). This paper discusses the application of the regional climate model COSMO-CLM as a dynamical downscaling tool. To provide accurate data the COSMO-CLM model output was post-processed by statistical means. This downscaling chain performs well in the baseline period 1971 to 2000. However, COSMO-CLM performs better in the UDRB than in the UBRB because of a longer application experience and a less complex climate in Europe. Different climate change scenarios were downscaled for the time period 1960–2100. The projections show an increase of temperature in both basins and for all seasons. The values are generally higher in the UBRB with the highest values occurring in the region of the Tibetan Plateau. Annual precipitation shows no substantial change. However, seasonal amounts show clear trends, for instance an increasing amount of spring precipitation in the UDRB. Again, the largest trends for different precipitation statistics are projected in the region of the Tibetan Plateau. Here, the projections show up to 50% longer dry periods in the months June to September with a simultaneous increase of about 10% for the maximum amount of precipitation on five consecutive days. For the Assam region in India, the projections also show an increase of 25% in the number of consecutive dry days during the monsoon season leading to prolonged monsoon breaks

Stimulant or depressant? Resource-related income shocks and conflict

We provide new evidence about the mechanisms linking resource-related income shocks to conflict. To do so, we combine temporal variation in international drug prices with new data on spatial variation in opium suitability to examine the effect of opium profitability on conflict in Afghanistan. District level results indicate a conflict-reducing effect over the 2002-2014 period, both in a reduced-form setting and with three different instrumental variables. We provide evidence for two main mechanisms. First, the importance of contest effects depends on the degree of violent group competition over valuable resources. By using data on the drug production process, ethnic homelands, and Taliban versus pro-government influence, we show that on average group competition for suitable districts is relatively low in Afghanistan. Second, we highlight the role of opportunity costs by showing that opium profitability positively affects household living standards, and becomes more important after a sudden rise in unemployment due to the dissolution of large armed militias after an exogenous policy change

Climate Change Vulnerability Assessment in Mauritania: Reflections on Data Quality, Spatial Scales, Aggregation and Visualizations

International audienceMauritania is vulnerable to climate change due to its location along the Sahel, the desert climate of the Sahara, and its socioeconomic characteristics. To support the identification of climate change adaptation measures in Brakna and Assaba in Mauritania, a spatial assessment of vulnerability to climate change targeting the livelihood sectors of agriculture and pastoralism was carried out. Based on the identification of relevant drivers of climate change vulnerability in a broad consultation process among national and local stakeholders, a variety of geospatial indicators were identified and integrated in the assessments based on a standardized vulnerability assessment approach. In this paper, we provide a reflection on the methodology applied and identify lessons to be learnt on data quality, spatial scales, aggregation and visualizations. The primary conclusion is that users of the assessment results and stakeholders need to be engaged in the entire assessment process in order to reflect local characteristics more fully, and to ensure that the results are reflected in informed decision-making

Myths and realities about the recovery of L׳Aquila after the earthquake

AbstractThere is a set of myths which are linked to the recovery of L׳Aquila, such as: the L׳Aquila recovery has come to a halt, it is still in an early recovery phase, and there is economic stagnation. The objective of this paper is threefold: (a) to identify and develop a set of spatial indicators for the case of L׳Aquila, (b) to test the feasibility of a numerical assessment of these spatial indicators as a method to monitor the progress of a recovery process after an earthquake and (c) to answer the question whether the recovery process in L׳Aquila stagnates or not. We hypothesize that after an earthquake the spatial distribution of expert defined variables can constitute an index to assess the recovery process more objectively. In these articles, we aggregated several indicators of building conditions to characterize the physical dimension, and we developed building use indicators to serve as proxies for the socio-economic dimension while aiming for transferability of this approach. The methodology of this research entailed six steps: (1) fieldwork, (2) selection of a sampling area, (3) selection of the variables and indicators for the physical and socio-economic dimensions, (4) analyses of the recovery progress using spatial indicators by comparing the changes in the restricted core area as well as building use over time; (5) selection and integration of the results through expert weighting; and (6) determining hotspots of recovery in L׳Aquila. Eight categories of building conditions and twelve categories of building use were identified. Both indicators: building condition and building use are aggregated into a recovery index. The reconstruction process in the city center of L׳Aquila seems to stagnate, which is reflected by the five following variables: percentage of buildings with on-going reconstruction, partial reconstruction, reconstruction projected residential building use and transport facilities. These five factors were still at low levels within the core area in 2012. Nevertheless, we can conclude that the recovery process in L׳Aquila did not come to a halt but is still ongoing, albeit being slow

The Disaster-Knowledge Matrix – Reframing and evaluating the knowledge challenges in disaster risk reduction

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Spatial vulnerability Indicators applied to recovery and risk reduction after earthquakes: The case of L'Aquila - Italy

Vulnerability assessment is a key contribution to formulate recovery and development policies in the risk management process. The post-disaster phases present the opportunity to address the pre-existent vulnerability conditions in order to reduce the risk and create more resilient societies. The aim of this research is to construct a methodology for monitoring and evaluating the recovery and reconstruction process after earthquakes, based on a framework of spatial vulnerability indicators beyond the physical aspect. The research aims to find the correlation between vulnerability conditions and the dynamics of relief, recovery and development processes and to know which other factors influence the interventions during post-disaster phases. The methodological approach relies on spatial indicators but the idea is to construct an index, which is not only based on physical patterns but also on the social, economical, institutional, cultural and environmental dimensions. The case study area is L’Aquila (Italy), which was shaken by the 6th of April 2009 earthquake. Additionally, key elements could also be extrapolated from the experience collected so far in Bogotá D.C. (Colombia), since this city is currently working on its preimpact recovery planning. The research is divided in five phases. The first one consist of the literature review of the concepts, previous experiences, best practices, indicators theory, vulnerability assessment, post-disaster activities, the application of remote sensing, GIS techniques and statistics methods. The second phase corresponds to the fieldwork, which is divided into four activities: discussions with the key stakeholders, observation of the local conditions, surveys among affected population and collection of spatial data. The last three phases correspond to the analysis using tools and techniques according to the specific topic to be analyzed, the explanation and discussion of the results and the conclusion and recommendations to improve future recovery processe

Environmental change and Rift Valley fever in eastern Africa: projecting beyond HEALTHY FUTURES

Outbreaks of Rift Valley fever (RVF), a relatively recently emerged zoonosis endemic to large parts of sub-Saharan Africa that has the potential to spread beyond the continent, have profound health and socio-economic impacts, particularly in communities where resilience is already low. Here output from a new, dynamic disease model [the Liverpool RVF (LRVF) model], driven by downscaled, bias-corrected climate change data from an ensemble of global circulation models from the Inter-Sectoral Impact Model Intercomparison Project run according to two radiative forcing scenarios [representative concentration pathway (RCP)4.5 and RCP8.5], is combined with results of a spatial assessment of social vulnerability to the disease in eastern Africa. The combined approach allowed for analyses of spatial and temporal variations in the risk of RVF to the end of the current century. Results for both scenarios highlight the high-risk of future RVF outbreaks, including in parts of eastern Africa to date unaffected by the disease. The results also highlight the risk of spread from/to countries adjacent to the study area, and possibly farther afield, and the value of considering the geography of future projections of disease risk. Based on the results, there is a clear need to remain vigilant and to invest not only in surveillance and early warning systems, but also in addressing the socio-economic factors that underpin social vulnerability in order to mitigate, effectively, future impacts