Use of Bayesian geostatistical prediction to estimate local variations in Schistosoma haematobium infection in western Africa

Objective We aimed to predict sub-national spatial variation in numbers of people infected with Schistosoma haematobium, and associated uncertainties, in Burkina Faso, Mali and Niger, prior to implementation of national control programmes. Methods We used national field survey datasets covering a contiguous area 2,750 × 850 km, from 26,790 school-aged children (5–14 years) in 418 schools. Bayesian geostatistical models were used to predict prevalence of high and low intensity infections and associated 95% credible intervals (CrI). Numbers infected were determined by multiplying predicted prevalence by numbers of school-aged children in 1 km2 pixels covering the study area. Findings Numbers of school-aged children with low-intensity infections were: 433,268 in Burkina Faso, 872,328 in Mali and 580,286 in Niger. Numbers with high-intensity infections were: 416,009 in Burkina Faso, 511,845 in Mali and 254,150 in Niger. 95% CrIs (indicative of uncertainty) were wide; e.g. the mean number of boys aged 10–14 years infected in Mali was 140,200 (95% CrI 6200, 512,100). Conclusion National aggregate estimates for numbers infected mask important local variation, e.g. most S. haematobium infections in Niger occur in the Niger River valley. Prevalence of high-intensity infections was strongly clustered in foci in western and central Mali, north-eastern and northwestern Burkina Faso and the Niger River valley in Niger. Populations in these foci are likely to carry the bulk of the urinary schistosomiasis burden and should receive priority for schistosomiasis control. Uncertainties in predicted prevalence and numbers infected should be acknowledged and taken into consideration by control programme planners.

Spatially stratified sampling using auxiliary information for geostatistical mapping

This paper presents a method of spatial sampling based on stratification by Local Moran’s I i calculated using auxiliary information. The sampling technique is compared to other design-based approaches including simple random sampling, systematic sampling on a regular grid, conditional Latin Hypercube sampling and stratified sampling based on auxiliary information, and is illustrated using two different spatial data sets. Each of the samples for the two data sets is interpolated using regression kriging to form a geostatistical map for their respective areas. The proposed technique is shown to be competitive in reproducing specific areas of interest with high accuracy.

Geostatistical analysis of adult Rhyzopertha dominica (F.) (Coleoptera: Bostrichidae) in wheat stored at constant temperatures

Insect monitoring and sampling programmes are used in the stored grains industry for the detection and estimation of insect pests. At the low pest densities dictated by economic and commercial requirements, the accuracy of both detection and abundance estimates can be influenced by variations in the spatial structure of pest populations over short distances. Geostatistical analysis of Rhyzopertha dominica populations in 2 dimensions showed that, in both the horizontal and vertical directions and at all temperatures examined, insect numbers were positively correlated over short (0-5cm) distances, and negatively correlated over longer (≥10cm) distances. Analysis in 3 dimensions showed a similar pattern, with positive correlations over short distances and negative correlations at longer distances. At 35°C, insects were located significantly further from the grain surface than at 25 and 30°C. Dispersion metrics showed statistically significant aggregation in all cases. This is the first research using small sample units, high sampling intensities, and a range of temperatures, to show spatial structuring of R. dominica populations over short distances. This research will have significant implications for sampling in the stored grains industry.

A Geostatistical Study pf Alumina-Content in Ores of An Indian Iron-Ore Deposit

Mining and blending operations in the high grade iron ore deposit under study are performed to optimize recovery with minimal alumina content while maintaining required levels of other chemical component and a proper mix of ore types. In the present work the regionalisation of alumina in the ores has been studied independently and its effects on global and local recoverable tonnage as well as on alternatives of mining operations have been evaluated. The global tonnage recovery curves for blocks (20m x 20m x 12m) obtained by simulation closely approximated the curves obtained theoretically using a change of support under the discretised gaussian model. Variations in block size up to 80m x 20m x 12m did not affect the recovery as the horizontal dimensions of the blocks are small in relation to the range of the variogram. A comparison of the local tonnage recovery curves obtained through multiple conditional simulations made with that obtained by the method of uniform conditioning of block grades on an estimate of panel 100m x 100m x 12m panel grade reveals comparable results only in panels which have been well conditioned and possesing an ensemble simulation mean close to the ordinary kriged value for the panel. Study of simple alternative sequence of mining on the conditionally simulated deposit shows that concentration of mining operations simultaneously on a single bench enhances the fluctuation in alumina values of ore mined.

Nassau grouper (Epinephelus striatus) spawning aggregations: hydroacoustic surveys and geostatistical analysis

With the near extinction of many spawning aggregations of large grouper and snapper throughout the Caribbean, Gulf of Mexico, and tropical Atlantic, we need to provide baselines for their conservation. Thus, there is a critical need to develop techniques for rapidly assessing the remaining known (and unknown) aggregations. To this end we used mobile hydroacoustic surveys to estimate the density, spatial extent, and total abundance of a Nassau grouper spawning aggregation at Little Cayman Island, Cayman Islands, BWI. Hydroacoustic estimates of abundance, density, and spatial extent were similar on two sampling occasions. The location and approximate spatial extent of the Nassau grouper spawning aggregation near the shelf-break was corroborated by diver visual observations. Hydroacoustic density estimates were, overall, three-times higher than the average density observed by divers; however, we note that in some instances diver-estimated densities in localized areas were similar to hydroacoustic density estimates. The resolution of the hydroacoustic transects and geostatistical interpolation may have resulted in over-estimates in fish abundance, but still provided reasonable estimates of total spatial extent of the aggregation. Limitations in bottom time for scuba and visibility resulted in poor coverage of the entire Nassau grouper aggregation and low estimates of abundance when compared to hydroacoustic estimates. Although the majority of fish in the aggregation were well off bottom, fish that were sometimes in close proximity to the seafloor were not detected by the hydroacoustic survey. We conclude that diver observations of fish spawning aggregations are critical to interpretations of hydroacoustic surveys, and that hydroacoustic surveys provide a more accurate estimate of overall fish abundance and spatial extent than diver observations. Thus, hydroacoustics is an emerging technology that, when coupled with diver observations, provides a comprehensive survey method for monitoring spawning aggregations of fish.

Geostatistical analysis of chlorophyll a in freshwater ecosystems

Horizontal spatial patterns of chlorophyll a in Meiziya Reservoir, Hubei Province, China were analyzed once each month during May, June and July 1997. Two geostatistical techniques, semivariance and fractal analysis, were used to determine variation in chlorophyll a over the whole study area (isotropic) and in different directions (anisotropic). Both techniques provided useful information for detecting and assessing spatial pattern changes of chlorophyll a in freshwater environments. Based on our case study, the distribution of chlorophyll a shifted from aggregated to random distribution in the case of small rainfall event, and then returned to the aggregated distribution after a large rainfall event. On the other hand, the distribution of chlorophyll a became more heterogeneous or random in the direction of water flow (S-N direction) when rainfall events occurred, which was enhanced by rainfall intensity. In contrast, the influence of water flow on the spatial patterns was weak in the E-W direction, and thus the distribution of chlorophyll a remained aggregate with a moderate spatial heterogeneity.

Non-stationary variogram models for geostatistical sampling optimisation: An empirical investigation using elevation data

A problem with use of the geostatistical Kriging error for optimal sampling design is that the design does not adapt locally to the character of spatial variation. This is because a stationary variogram or covariance function is a parameter of the geostatistical model. The objective of this paper was to investigate the utility of non-stationary geostatistics for optimal sampling design. First, a contour data set of Wiltshire was split into 25 equal sub-regions and a local variogram was predicted for each. These variograms were fitted with models and the coefficients used in Kriging to select optimal sample spacings for each sub-region. Large differences existed between the designs for the whole region (based on the global variogram) and for the sub-regions (based on the local variograms). Second, a segmentation approach was used to divide a digital terrain model into separate segments. Segment-based variograms were predicted and fitted with models. Optimal sample spacings were then determined for the whole region and for the sub-regions. It was demonstrated that the global design was inadequate, grossly over-sampling some segments while under-sampling others.