3,574 research outputs found
Investigating spatial structure in specific tree species in ancient semi-natural woodland using remote sensing and marked point pattern analysis
No full textRemote sensing classification has the potential to provide important information, such as tree species distribution maps, to ecologists, at a range of spatial and temporal scales. However, standard classification procedures often fail to provide the high accuracies required for many ecological applications. Previously, a modified remote sensing classification technique was used to provide very high classification accuracies for one
or two classes (e.g. species) of interest. The aim of this paper was to demonstrate that the output from the method can be suitable for spatial ecological analyses, and to provide a generic simulation framework for assessing the adequacy of any given remote sensing classification for such analyses. Marked point pattern analysis (MPPA) was applied to tree species distribution data obtained for sycamore Acer pseudoplatanus and ash
Fraxinus excelsior from a 400 ha ancient semi-natural woodland in southern England using the modified remote sensing classification method to test several hypotheses of ecological interest relating to the spatial distribution and interaction of these species. Monte Carlo simulation methods were then used to evaluate the data and data quality requirements of the MPPA to check that the classified tree species maps for sycamore and ash were adequate. Using the combined method the spatial distributions for sycamore and ash were found to be aggregated and inter-dependent at a range of spatial scales. Together, the remote sensing classification and simulation approaches provide the basis for exploiting more fully the potential of remote sensing to provide information of value to ecologists
Database for: Excavations at Tall Jawa, Jordan: Volume 3, The Iron Age Pottery
No full textThis is a Microsoft Access database of imagery, drawings, and photos accompanying Excavations at Tall Jawa, Jordan: Volume 3, The Iron Age Pottery by P.M. Michèle Daviau. The text and database present a detailed typology of the Iron Age pottery excavated from 1989 to 1995. Together, they represent an in-depth analysis of the forming techniques employed to make each type of vessel from bowls to colanders, cooking pots to pithoi.
The digital archive is a work in progress by the author. The archive currently holds the collection for Excavation Field D. Upon completion, it will include seven collections, each one consisting of a database of diagnostic sherds and vessels as well as the images of these pots as .tiff files. Databases are related to excavation fields and are designed for meaningful searches: A, B, C-east, C-west, A-east (associated with C-west), D and E
Information for decision making from imperfect national data: tracking major changes in health care use in Kenya using geostatistics
No full textBackground: most Ministries of Health across Africa invest substantial resources in some form of health management information system (HMIS) to coordinate the routine acquisition and compilation of monthly treatment and attendance records from health facilities nationwide. Despite the expense of these systems, poor data coverage means they are rarely, if ever, used to generate reliable evidence for decision makers. One critical weakness across Africa is the current lack of capacity to effectively monitor patterns of service use through time so that the impacts ofchanges in policy or service delivery can be evaluated. Here, we present a new approach that, for the first time, allows national changes in health service use during a time of major health policy change to be tracked reliably using imperfect data from a national HMIS.Methods: monthly attendance records were obtained from the Kenyan HMIS for 1 271 government-run and 402 faith-based outpatient facilities nationwide between 1996 and 2004. Aspace-time geostatistical model was used to compensate for the large proportion of missing records caused by non-reporting health facilities, allowing robust estimation of monthly and annualuse of services by outpatients during this period.Results: we were able to reconstruct robust time series of mean levels of outpatient utilisation of health facilities at the national level and for all six major provinces in Kenya. These plots revealed reliably for the first time a period of steady nationwide decline in the use of health facilities in Kenyabetween 1996 and 2002, followed by a dramatic increase from 2003. This pattern was consistent across different causes of attendance and was observed independently in each province.Conclusion: the methodological approach presented can compensate for missing records in health information systems to provide robust estimates of national patterns of outpatient service use. This represents the first such use of HMIS data and contributes to the resurrection of these hugely expensive but underused systems as national monitoring tools. Applying this approach to Kenya has yielded output with immediate potential to enhance the capacity of decision makers in monitoring nationwide patterns of service use and assessing the impact of changes in health policy and service deliver
Identification of specific tree species in ancient semi-natural woodland from digital areal sensor imagery
No full textRemote sensing has great potential as a source of information on tree species. The classification approaches used commonly to extract species information from remotely sensed imagery typically aim to optimize the overall accuracy of species identification, a target which need not satisfy the requirements of a particular user. Often users are interested in a specific species or subset of species, and these may not be accurately identified in a conventional classification. Here, a two-phase classification approach was used to map specific species from aerial sensor imagery of an ancient British woodland. Particular attention was focused on the identification of sycamore since this is displacing the native ash and information on its distribution would enhance basic understanding and management activities. The results show that the classification approach can be adapted to focus on a specific species of interest and used to increase classification accuracy significantly. For example, sycamore was classified to a low accuracy when a conventional approach to classification with a neural network was used (46.6–63.6%, depending on perspective), but the adoption of the two-phase approach increased its accuracy significantly (82.3–93.3%). The results demonstrate the ability to map specific class(es) of interest accurately from remotely sensed imagery. The approach used also highlights the ability to tailor an analysis to the specific requirements of the ecological study in hand and is of broad applicability
Geographical access to care at birth in Ghana: a barrier to safe motherhood
No full textBackground: appropriate facility-based care at birth is a key determinant of safe motherhood but geographical access remains poor in many high burden regions. Despite its importance, geographical access is rarely audited systematically, preventing integration in national-level maternal health system assessment and planning. In this study, we develop a uniquely detailed set of spatially-linked data and a calibrated geospatial model to undertake a national-scale audit of geographical access to maternity care at birth in Ghana, a high-burden country typical of many in sub-Saharan Africa.Methodology and findings: we assembled detailed spatial data on health facilities, roads, rivers, and other landscape features influencing journeys. These were used in a geospatial model to estimate journey-time for all women of childbearing age (WoCBA) to their nearest health facility offering differing levels of care at birth, taking into account different transport types and availability. We calibrated the model using data on actual journeys made by women seeking care at birth. We found that a third of women (34%) in Ghana live beyond the clinically significant two-hour threshold from any facility likely to offer emergency obstetric and neonatal care (EmONC) classed at the ‘partial’ standard or better. Nearly half (45%) live that distance or further from ‘comprehensive’ EmONC facilities, offering life-saving blood transfusion and surgery. In the most remote regions these figures rose to 63% and 81%, respectively. Poor levels of access were found in many regions that meet international targets based on facilities-per-capita ratios.Conclusions and significance: detailed data assembly combined with geospatial modelling can provide nation-wide audits of geographical access to care at birth to support systemic maternal health planning, human resource deployment, and strategic targeting. Current international benchmarks of maternal health care provision are inadequate for these purposes because they fail to take account of the location and accessibility of services relative to the women they serve<br/
Bayesian geostatistical analysis and prediction of Rhodesian human African trypanosomiasis
No full textBackgroundThe persistent spread of Rhodesian human African trypanosomiasis (HAT) in Uganda in recent years has increased concerns of a potential overlap with the Gambian form of the disease. Recent research has aimed to increase the evidence base for targeting control measures by focusing on the environmental and climatic factors that control the spatial distribution of the disease.ObjectivesOne recent study used simple logistic regression methods to explore the relationship between prevalence of Rhodesian HAT and several social, environmental and climatic variables in two of the most recently affected districts of Uganda, and suggested the disease had spread into the study area due to the movement of infected, untreated livestock. Here we extend this study to account for spatial autocorrelation, incorporate uncertainty in input data and model parameters and undertake predictive mapping for risk of high HAT prevalence in future.Materials and MethodsUsing a spatial analysis in which a generalised linear geostatistical model is used in a Bayesian framework to account explicitly for spatial autocorrelation and incorporate uncertainty in input data and model parameters we are able to demonstrate a more rigorous analytical approach, potentially resulting in more accurate parameter and significance estimates and increased predictive accuracy, thereby allowing an assessment of the validity of the livestock movement hypothesis given more robust parameter estimation and appropriate assessment of covariate effects.ResultsAnalysis strongly supports the theory that Rhodesian HAT was imported to the study area via the movement of untreated, infected livestock from endemic areas. The confounding effect of health care accessibility on the spatial distribution of Rhodesian HAT and the linkages between the disease's distribution and minimum land surface temperature have also been confirmed via the application of these methods.ConclusionsPredictive mapping indicates an increased risk of high HAT prevalence in the future in areas surrounding livestock markets, demonstrating the importance of livestock trading for continuing disease spread. Adherence to government policy to treat livestock at the point of sale is essential to prevent the spread of sleeping sickness in Uganda
Empirical modelling of government health service use by children with fevers in Kenya
No full textAn understanding of spatial patterns of health facility use allows a more informed approach to the modelling of catchment populations. In the absence of patient use data, an intuitive and commonly used approach to the delineation of facility catchment areas is Thiessen polygons. This study presents a series of methods by which the validity of these assumptions can be tested directly and hence the suitability of a Thiessen polygon catchment model explicitly assessed. These methods are applied to paediatric out-patient origin data from a sample of 81 government health facilities in four districts of Kenya. A geographical information system was used to predict the location of the catchment boundary along a transect between each pair of neighbouring facilities based on patient choice patterns. The mean location of boundaries between facilities of different type was found to be significantly displaced from the Thiessen boundary towards the lower-order facility. The effect of distance on within-catchment utilization rate was assessed by using exclusion buffers to remove the effect of neighbouring facilities. Utilization rate was found to exhibit a slight but steady decrease with distance up to 6 kmfrom a facility. The accuracy of the future modelling of unsampled facility catchments can be increased by the incorporation of these trends
A local space–time kriging approach applied to a national outpatient malaria data set
No full textIncreases in the availability of reliable health data are widely recognised as essential for efforts to strengthen health-care
systems in resource-poor settings worldwide. Effective health-system planning requires comprehensive and up-to-date
information on a range of health metrics and this requirement is generally addressed by a Health Management
Information System (HMIS) that coordinates the routine collection of data at individual health facilities and their
compilation into national databases. In many resource-poor settings, these systems are inadequate and national databases
often contain only a small proportion of the expected records. In this paper, we take an important health metric in Kenya
(the proportion of outpatient treatments for malaria (MP)) from the national HMIS database and predict the values of MP
at facilities where monthly records are missing. The available MP data were densely distributed across a spatiotemporal
domain and displayed second-order heterogeneity. We used three different kriging methodologies to make cross-validation
predictions of MP in order to test the effect on prediction accuracy of (a) the extension of a spatial-only to a space–time
prediction approach, and (b) the replacement of a globally stationary with a locally varying random function model.
Space–time kriging was found to produce predictions with 98.4% less mean bias and 14.8% smaller mean imprecision than
conventional spatial-only kriging. A modification of space–time kriging that allowed space–time variograms to be
recalculated for every prediction location within a spatially local neighbourhood resulted in a larger decrease in mean
imprecision over ordinary kriging (18.3%) although the mean bias was reduced less (87.5%)
IoWoman, March/April 2004, Vol. 34, no. 2
No full textNewsletter for the Iowa Commission on the Status of Wome
Evaluating the impact of the community-based health planning and services initiative on uptake of skilled birth care in Ghana
No full textBackground: the Community-based Health Planning and Services (CHPS) initiative is a major government policy to improve maternal and child health and accelerate progress in the reduction of maternal mortality in Ghana. However, strategic intelligence on the impact of the initiative is lacking, given the persistent ?problems of patchy geographical access to care for rural women. This study investigates the impact of proximity to CHPS on facilitating uptake of skilled ?birth care in rural areas.Methods and findings: data from the ?2003 and 2008 Demographic and Health Survey, ? on 4,349 births from 463 rural communities were linked to georeferenced data on health facilities, CHPS and topographic data on national road-networks. Distance to nearest health facility and CHPS was computed using the closest facility functionality in ArcGIS 10.1. Multilevel logistic regression was used to examine the effect of proximity to health facilities and CHPS on use of skilled care at birth, adjusting for relevant predictors and clustering within ?communities.? The results show that a substantial proportion of births continue to occur in communities more than 8 km from both ?health facilities and CHPS. Increases in uptake of skilled birth care are more pronounced where both health ?facilities and CHPS compounds are within 8 km, but not in communities within 8 km of CHPS but lack access to health facilities. Where both health facilities and CHPS are within 8 km, the odds of skilled ?birth care is 16% higher than ?where there is only a health facility within 8km. Conclusion: where CHPS compounds are set up near health facilities, there is improved access to care, demonstrating the facilitatory role of CHPS in stimulating access to better care at birth, in areas where health facilities are accessible. <br/
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