Alternative Sampling Strategies Research Articles

Optimal Survey Designs for Targeting Chemotherapy Against Soil-Transmitted Helminths: Effect of Spatial Heterogeneity and Cost-Efficiency of Sampling

Implementation of helminth control programs requires information on the distribution and prevalence of infection to target mass treatment to areas of greatest need. In the absence of data, the question of how many schools/communities should be surveyed depends on the spatial heterogeneity of infection and the cost efficiency of surveys. We used geostatistical techniques to quantify the spatial heterogeneity of soil-transmitted helminths in multiple settings in eastern Africa, and using the example of Kenya, conducted conditional simulation to explore the implications of alternative sampling strategies in identifying districts requiring mass treatment. Cost analysis is included in the simulations using data from actual field surveys and control programs. The analysis suggests that sampling four or five schools in each district provides a cost-efficient strategy in identifying districts requiring mass treatment, and that efficiency of sampling was relatively insensitive to the number of children sampled per school.

Efficient importance sampling maximum likelihood estimation of stochastic differential equations

Maximum likelihood estimation (MLE) of stochastic differential equations (SDEs) is difficult because in general the transition density function of these processes is not known in closed form, and has to be approximated somehow. An approximation based on efficient importance sampling (EIS) is detailed. Monte Carlo experiments, based on widely used diffusion processes, evaluate its performance against an alternative importance sampling (IS) strategy, showing that EIS is at least equivalent, if not superior, while allowing a greater flexibility needed when examining more complicated models.

Transmission-mode direct analysis in real time and desorption electrospray ionization mass spectrometry of insecticide-treated bednets for malaria control

Transmission-mode direct analysis in real time (TM-DART) is presented as an alternative sampling strategy to traditional methods of sample introduction for DART MS analysis. A custom-designed sample holder was fabricated to rapidly and reproducibly position insecticide-treated nets normal to the ionizing metastable gas stream, enabling transmission of desorbed analyte ions through the holder cavity and into the MS. Introduction of the sample at this fixed geometry eliminates the need for optimizing sample position and allows spectra based on factors such as metastable gas temperature and flow to be systematically evaluated. The results presented here, supported by computational fluid dynamic simulations, demonstrate the effects of these factors on the resulting mass spectra and the potential of this sampling strategy to be used for qualitative and quantitative analyses. Transmission-mode desorption electrospray ionization (TM-DESI) experiments on similar insecticide-treated nets were performed for comparison purposes.

An On-Line Virtual Environment For Teaching Statistical Sampling And Analysis

Regardless of the related discipline, students in statistics courses invariably have difficulty understanding the connection between the numerical values calculated for end-of-the-chapter exercises and their usefulness in decision making. This disconnect is, in part, due to the lack of time and opportunity to actually design the experiments and collect the data. The prototypes proposed in this project were developed to allow students to design experiments and collect data in relevant settings without the impediments to real data collection. The virtual environments attempt to replicate real situations of interest in which students can design and run experiments, devise alternative sampling strategies, analyze the results of experiments, and relate the result to the original experiment. The setting and underlying data set detailed in this paper were developed to allow students to experience a wide range of statistical concepts typically found in introductory statistic courses, such as basic descriptive statistics, estimation, hypothesis testing, ANOVA, and regression. Assessments of student knowledge after using this approach have shown marked increases in students understanding of statistical concepts, especially confidence intervals and hypothesis testing. Specific details about the data set are provided as are suggestions for using it in an introductory statistics class. Potential uses and examples for a variety of disciplines are also included.

Computational methods for parameter estimation in climate models

Intensive computational methods have been used by Earth scientists in a wide range of problems in data inversion and uncertainty quantification such as earthquake epicenter location and climate projections. To quantify the uncertainties resulting from a range of plausible model configurations it is necessary to estimate a multidimensional probability distribution. The computational cost of estimating these distributions for geoscience applications is impractical using traditional methods such as Metropolis/Gibbs algorithms as simulation costs limit the number of experiments that can be obtained reasonably. Several alternate sampling strategies have been proposed that could improve on the sampling efficiency including Multiple Very Fast Simulated Annealing (MVFSA) and Adaptive Metropolis algorithms. The performance of these proposed sampling strategies are evaluated with a surrogate climate model that is able to approximate the noise and response behavior of a realistic atmospheric general circulation model (AGCM). The surrogate model is fast enough that its evaluation can be embedded in these Monte Carlo algorithms. We show that adaptive methods can be superior to MVFSA to approximate the known posterior distribution with fewer forward evaluations. However the adaptive methods can also be limited by inadequate sample mixing. The Single Component and Delayed Rejection Adaptive Metropolis algorithms were found to resolve these limitations, although challenges remain to approximating multi-modal distributions. The results show that these advanced methods of statistical inference can provide practical solutions to the climate model calibration problem and challenges in quantifying climate projection uncertainties. The computational methods would also be useful to problems outside climate prediction, particularly those where sampling is limited by availability of computational resources.

Combined use of phenotypic and genotypic information in sampling animals for genotyping in detection of quantitative trait loci

Conventional selective genotyping which is using the extreme phenotypes (EP) was compared with alternative criteria to find the most informative animals for genotyping with respects to mapping quantitative trait loci (QTL). Alternative sampling strategies were based on minimizing the sampling error of the estimated QTL effect (MinERR) and maximizing likelihood ratio test (MaxLRT) using both phenotypic and genotypic information. In comparison, animals were randomly genotyped either within or across families. One hundred data sets were simulated each with 30 half-sib families and 120 daughters per family. The strategies were compared in these datasets with respect to estimated effect and position of a QTL within a previously defined genomic region at genotyping 10, 20 or 30% of the animals. Combined linkage disequilibrium linkage analysis (LDLA) was applied in a variance component approach. Power to detect QTL was significantly higher for both MinERR and MaxLRT compared with EP and random genotyping methods (either across or within family), for all the proportions of genotyped animals. Power to detect significant QTL (alpha = 0.01) with 20% genotyping for MinERR and MaxLRT was 80 and 75% of that obtained with complete genotyping compared with 70 and 38% genotyping for EP within and across families respectively. With 30% genotyping, the powers were 78, 83, 78 and 58% respectively. The estimated variance components were unbiased in EP strategies (within and across family), only when at least 30% was genotyped. To decrease the number of genotyped individuals either MinERR or MaxLRT could be considered. With 20% genotyping in MinERR, the estimated QTL variance components were not significant compared with complete genotype information but all studied strategies at 20% genotyping overestimated the QTL effect. Results showed that combining the phenotypic and genotypic information in selective genotyping (e.g. MinERR and MaxLRT) is better than using only the EPs and the combined methods can be considered as alternative approaches to decrease genotyping costs, with unbiased QTL effects, decreased sampling variance of the QTL variance component and also increased the power of QTL detection.

Readout-segmented EPI for rapid high resolution diffusion imaging at 3T

Readout mosaic segmentation has been suggested as an alternative approach to EPI for high resolution diffusion-weighted imaging (DWI). In the readout-segmented EPI (RS-EPI) scheme, segments of k-space are acquired along the readout direction. This reduces geometric distortions due to the decrease in readout time. In this work, further distortion reduction is achieved by combining RS-EPI with parallel imaging (PI). The performance of the PI-accelerated RS-EPI scheme is assessed in volunteers and patients at 3T with respect to both standard EPI and PI-accelerated EPI. Peripherally cardiac gated and non-gated RS-EPI images are acquired to assess whether motion due to brain pulsation significantly degrades the image quality. Due to the low off-resonance of PI-driven RS-EPI, we also investigate if the eddy currents induced by the diffusion gradients are low enough to use the Stejskal–Tanner diffusion preparation instead of the twice-refocused eddy-current compensated diffusion preparation to reduce TE. It is shown that non-gated phase corrected DWI performs equally as well as gated acquisitions. PI-driven DW RS-EPI images with substantially less distortion compared with single-shot EPI are shown in patients—allowing the delineation of structures in the lower parts of the brain. A twice-refocused diffusion preparation was found necessary to avoid blurring in the DWI data. This paper shows that the RS-EPI scheme may be an important alternative sampling strategy to EPI to achieve high resolution T2-weighted and diffusion-weighted images.

Clustering of parasites within cages on Scottish and Norwegian salmon farms: Alternative sampling strategies illustrated using simulation

Within the literature, most discussion of sampling protocols for monitoring aquatic parasites is based on the assumptions of simple random sampling. Recent research has shown that in monitoring parasite abundance on fish farms composed of discrete cages, care must be taken to properly account for the clustering which naturally occurs. This paper illustrates the effect of clustering in the context of monitoring ectoparasitic sea lice Lepeophtheirus salmonis and Caligus elongatus in salmon farms. The degree of clustering of sea lice infections in fish within cages is measured using the intraclass correlation coefficient (ICC). A wide range of ICC values from sites in Scotland and Norway were estimated for the chalimus and mobile stages of L. salmonis, and for C. elongatus mobiles. The analyses indicate that significant clustering of lice infections within cages occurs across lice species and stages on both Scottish and Norwegian farms. A Monte-Carlo simulation using two sets of data from Scottish farms with ICC values for adult L. salmonis of 0.35 [0.08–0.73, 95% CI] and for adult C. elongatus of 0.39 [0.16–0.69, 95% CI] were used to illustrate the implications of clustering. The protocols simulated reflect those typically used across a range of countries and production environments in which salmon are currently reared. The findings demonstrate that the “few fish from many cages” approach results in a marked improvement in precision when sampling aquatic one-host parasites in cage-based production systems.

Evidence for lead diagenesis in ancient bones of the Southern Andes

Skeletal samples from pre-Colonial Peru and Bolivia, dating from AD 300 to 1450, were sampled and analyzed for lead content using a non-destructive X-ray fluorescence (XRF) technique. A total of 99 lead measurements were made on bones recovered from three regions of the Southern Andes. Predominantly trabecular bones demonstrated clearly higher lead concentrations than predominantly cortical bones. The magnitudes of lead concentrations and the differences between bony areas that are predominantly cortical and those that are trabecular, indicate diagenesis as the major contributor to observed lead levels. Diagenetic contributions of lead are less substantial in cortical bone. Soil sample analyses confirmed significant quantities of lead in the sediments. Repeated measurements of a tibia and femur from a single individual suggest that the cortical shafts of these bones have similar susceptibilities to lead diagenesis. This is significant for designing alternative sampling strategies in areas where preservation is poor and a specific bone may not be present in all individuals. The XRF system used in this study demonstrates an improved precision of measurement compared with previously reported applications.

A normative value pilot study: Levels of uranium in urine samples from UK civilians

A normative study of the levels of urinary uranium in the general UK population is needed for comparison with levels in UK military and ex-military personnel who served where munitions containing depleted uranium (DU) were used. As preparation, this pilot study trialled the process of collecting 24-h samples from adult male civilians, and compared the measurements from 24-h samples with those from spot samples taken over the subsequent 24 h. The purpose was to assess the relative utility of the two types of samples. Twenty-five convalescent hospital in-patients were recruited as participants. Uranium concentrations in the 24-h samples ranged from 1 to 10.6 ng l −1; in the spots, from not detectable to 38.1 ng l −1. Normalised to creatinine, concentrations in the 24 h samples ranged from approximately 100 to 800 ng mol −1 creatinine; in the spot samples, from not detectable to approximately 4000 ng mol −1 creatinine. The ranges appear similar to those reported for residents of the US. The distribution of spot sample results indicated that 95% of a participant's creatinine-adjusted concentrations from spot samples would be within the range 40–250% of his mean. Adjusting for creatinine almost entirely eliminated a slight indication of diurnal variation in urinary uranium concentration in spot samples. All the 24-h samples and 131 out of the 133 spot samples showed ratios of isotopes 238U to 235U consistent with natural uranium (i.e. neither enriched nor depleted). Slightly elevated ratios in two spot samples were not supported by other samples from the same participants, indicating that slightly elevated ratios may be recorded on very low concentration (<1 ng l −1) samples. In the main, quantification of this isotope ratio from spot samples was only slightly more variable than from 24-h samples. Complete 24-h urine samples gave better precision than spot samples in estimating uranium concentrations at these low levels, but presented more logistic difficulties in the collection of the samples. Clarification of the relative merits of alternative sampling strategies enables the design of a wider study to be optimised.

Random Sampling for Continuous Streams with Arbitrary Updates

The existing random sampling methods have at least one of the following disadvantages: they 1) are applicable only to certain update patterns, 2) entail large space overhead, or 3) incur prohibitive maintenance cost. These drawbacks prevent their effective application in stream environments (where a relation is updated by a large volume of insertions and deletions that may arrive in any order), despite the considerable success of random sampling in conventional databases. Motivated by this, we develop several fully dynamic algorithms for obtaining random samples from individual relations, and from the join result of two tables. Our solutions can handle any update pattern with small space and computational overhead. We also present an in-depth analysis that provides valuable insight into the characteristics of alternative sampling strategies and leads to precision guarantees. Extensive experiments validate our theoretical findings and demonstrate the efficiency of our techniques in practice

Random Sampling for Continuous Streams with Arbitrary Updates

The existing random sampling methods have at least one of the following disadvantages: they 1) are applicable only to certain update patterns, 2) entail large space overhead, or 3) incur prohibitive maintenance cost. These drawbacks prevent their effective application in stream environments (where a relation is updated by a large volume of insertions and deletions that may arrive in any order), despite the considerable success of random sampling in conventional databases. Motivated by this, we develop several fully dynamic algorithms for obtaining random samples from individual relations, and from the join result of two tables. Our solutions can handle any update pattern with small space and computational overhead. We also present an in-depth analysis that provides valuable insight into the characteristics of alternative sampling strategies and leads to precision guarantees. Extensive experiments validate our theoretical findings and demonstrate the efficiency of our techniques in practice

Nontraditional work factors in farmworker adolescent populations: implications for health research and interventions.

Agriculture has been documented to be one of the most hazardous work environments for both adults and children. Adolescents may be especially vulnerable to adverse health effects from agricultural exposures due to the rapid growth and development experienced during those years. Separating the occupational, economic, and social issues in this population is difficult. Weak regulatory protection, lack of compliance with existing regulations, and gaps in service provision characterize the working conditions of adolescent farmworkers. Although there is increasing research on the impact of work organization on mental and physical health in adult working populations, there is a scarcity of research focused on this concept in young workers--and it remains virtually unaddressed in young farmworkers. Work characteristics of the informal work sector, better delineated in international literature, should be considered when planning research or interventions in this at-risk population. Further, the population of adolescent farmworkers is diverse, and research strategies and interventions need to be targeted and tailored to the heterogeneous groups. This article addresses some of the nontraditional work factors associated with the less-than-formal work organization and environments in the farmworker adolescent population and how these factors may inform the planning of research and interventions. Specifically, mobility, cultural patterns and social networks, alternative sampling strategies, alternative delivery of health care and education, and involvement of a wide range of players in the work environment of adolescent farmworkers should all be considered when conducting research or planning programs for this population.

Evaluation of lacrimal fluid as an alternative for monitoring glucose in critically ill patients

This study evaluated the use of lacrimal fluid glucose concentrations as a minimally invasive, alternative sampling strategy for monitoring glucose concentrations in surgical/trauma ICU patients. Prospective, paired sample study in an adult surgical/trauma ICU. Patients receiving subcutaneous or intravenous insulin requiring routine capillary blood glucose measurements. Patients receiving ocular lubricants, artificial tears, or routinely administered ophthalmic medications and patients with facial injuries were excluded. Lacrimal fluid was collected using glass capillary tube placed near the cul-de-sac of the eye. Capillary blood glucose was determined using a bedside glucose meter as per routine ICU care. Lacrimal fluid glucose concentration was analyzed using high-performance liquid chromatography with pulse amperometric detection. Forty-four paired samples from five patients were analyzed. Pearson correlation between lacrimal fluid (microM) and blood glucose (mM) concentrations and the proportional change from baseline revealed no significant associations. Due to the very poor association, enrollment was discontinued after five patients. Lacrimal fluid and blood glucose concentrations were poorly correlated, suggesting that the former is not a reliable alternative to blood glucose monitoring in surgical/trauma ICU patients requiring insulin therapy.

Review of sampling hard-to-reach and hidden populations for HIV surveillance

Adequate surveillance of hard-to-reach and 'hidden' subpopulations is crucial to containing the HIV epidemic in low prevalence settings and in slowing the rate of transmission in high prevalence settings. For a variety of reasons, however, conventional facility and survey-based surveillance data collection strategies are ineffective for a number of key subpopulations, particularly those whose behaviors are illegal or illicit. This paper critically reviews alternative sampling strategies for undertaking behavioral or biological surveillance surveys of such groups. Non-probability sampling approaches such as facility-based sentinel surveillance and snowball sampling are the simplest to carry out, but are subject to a high risk of sampling/selection bias. Most of the probability sampling methods considered are limited in that they are adequate only under certain circumstances and for some groups. One relatively new method, respondent-driven sampling, an adaptation of chain-referral sampling, appears to be the most promising for general applications. However, as its applicability to HIV surveillance in resource-poor settings has yet to be established, further field trials are needed before a firm conclusion can be reached.

Optimal design of measurement networks for groundwater flow predictions

This paper presents a methodology to optimise measurement networks for the prediction of groundwater flow. Two different strategies are followed: the design of a measurement network that aims at minimizing the log-transmissivity variance (averaged over the domain of interest) or a design that minimises the hydraulic head variance (averaged over the domain of interest). The methodology consists of three steps. In the first step the prior log-transmissivity and hydraulic head variances are estimated. This step is completely general in the sense that the prior variances maybe unconditional, or maybe conditioned to log-transmissivity and/or hydraulic head measurements. In case hydraulic head measurements are available in the first step, the inverse groundwater flow problem is solved by the sequential self-calibrated method. In the second step, the full covariance matrices of hydraulic head and log-transmissivity are calculated numerically on the basis of a sufficiently big number of Monte Carlo realisations. On the basis of the estimated covariances, the impact of an additional measurement in terms of variance reduction is calculated. The measurement that yields the maximum domain averaged variance reduction is selected. Additional measurement locations are selected according to the same procedure. The procedure has been tested for a series of synthetic reference cases. Different sampling designs are tested for each of these cases, and the proposed strategies are compared with other sampling strategies. Although the proposed strategies indeed reach their objective and yield in most cases the lowest posterior log-transmissivity variance or hydraulic head variance, the differences as compared to alternative sampling strategies are frequently small. For the cases considered here, a sampling design that covers more or less regularly the aquifer performs well. The paper also illustrates that for the optimal estimation of a well catchment a heuristic criterion (spreading measurement points as regularly as possible over the zone where there is some uncertainty regarding the capture probability) yields better results than a sampling design that minimises the posterior log-transmissivity variance or posterior hydraulic head variance.

Seasonal Variation in Diagnoses and Visits to Family Physicians

Practice-based research networks (PBRNs) replicating the National Ambulatory Medical Care Survey (NAMCS) must sample more than 1 year to account for presumed seasonal variation in illnesses. This study evaluated the effects of seasonality on diagnoses within NAMCS family physician data. Using combined data from the 1995-1998 NAMCS, diagnostic clusters that accounted for more than 1% of total visits were analyzed for seasonality. Seasons were coded categorically as dummy variables with summer as the reference category. A logistic regression was performed with each diagnosis as an outcome on the full data. To examine the ability of alternative sampling strategies to replicate the full year of data, a simulation study was carried out drawing 50 samples of 1,000 visits each for winter-summer and spring-fall sampling periods. We found 23 diagnostic clusters that had a frequency more than 1%, of which 10 had seasonal variations (P < or = .001), primarily between winter and summer. If sampling were restricted to spring, the diagnostic clusters of pregnancy and coronary artery disease would account for less than 1% of visits. All other diagnostic clusters, though changing rank order, would account for more than 1% if sampled in a single quarter. In the simulated sampling strategy, visit prevalence dropped below 1% for at least 1 diagnosis in 24 of 50 samples in spring-fall compared with 20 of 50 samples for winter-summer (P > .20). There is little seasonal variation in the 23 diagnoses that occur in more than 1% of visits to family physicians. There is, however, important seasonal variation in the rank order of these diagnoses. A sampling strategy that uses any quarter of the year but spring (March, April, May) could be used to understand what diagnoses are frequently seen within a PBRN.

Efficacy of Grid and Zone Soil Sampling Approaches for Site-Specific Assessment of Phosphorus, Potassium, pH, and Organic Matter

Within-field variability of plant-available nutrients often results in different fertilizer requirements across a field. There is uncertainty concerning the efficacy of alternative sampling strategies suitable for site-specific management. This study compared various soil sampling approaches for P, K, pH, and organic matter (OM) in eight agricultural fields. Soil samples were collected using an intensive 0.2-ha grid-point procedure, and were used to compare less intensive sampling approaches. The approaches were based on 1.2–1.6-ha grid cells (Grid), soil series of digitized soil survey maps (SSM), soil series of detailed soil survey (1:12,000 scale) maps, elevation zones, and management zones based on various information layers (ZS). The approaches varied in reducing the within-unit soil-test variability and maximizing mean soil-test values across sampling units, but none was superior across all fields and nutrients. All approaches were less efficient for P and K than for pH or OM. The Grid and ZS approach were the most effective across all nutrients and fields. However, the Grid approach was more effective for P, the Grid and ZS approaches were better for K and pH, and the SSM and ZS approaches were better for OM. The ZS approach often resulted in fewer sampling zones than the Grid approach, which implies lower soil testing costs for producers, but required more knowledge and subjective judgement than a Grid approach to adapt it to field-specific conditions.

Measuring toxic emissions from landfills using sequential screening

Comparisons of alternate spatial sampling strategies for characterizing hazardous waste sites can be performed using GIS-based stochastic simulation techniques. This work compares a traditional sampling design that uses only precise laboratory analytical methods to a sequential screening strategy that uses field screening methods to focus quantitative analysis on areas having pollutant concentrations above the analytical detection limit. Cost savings that result from eliminating uncontaminated areas from detailed analysis are spent on obtaining additional measurements until a fixed sampling budget is depleted. The screening strategy produces less biased and more precise estimates of volatile organic compounds emissions from an example landfill.

Potential biases in sampling design and interpretation of intra‐tooth isotope analysis

AbstractAn increasing number of studies dealing with environmental and dietary reconstruction involve measurement of intra‐tooth variation of isotope ratios. The sampling procedure typically consists of collecting a sequence of horizontal bands perpendicular to the growth axis of the tooth. The objective is to obtain a temporal sequence of the changes recorded in dental tissues during tooth development. This paper examines some issues associated with this sampling strategy and consequences for interpretation of the data. Time resolution is influenced by the pattern and duration of enamel mineralization, in a way that might, however, depend on the species and the tooth analysed. Although it may be impossible to sample discrete amounts of time, a chronological order seems to be respected, which should be well enough when the objective is to detect changes in isotope ratios with time. Absolute data must be interpreted with caution. Such issues do not affect studies of inter‐individual variability as long as the sampling procedure applied to the compared specimens is consistent. A new sampling strategy is tested on modern goat teeth, involving drilling in an oblique direction. The results obtained from obliquely drilled samples are very similar to those obtained from the horizontal sampling procedure. More work is still needed to determine the value of alternative sampling strategies. Copyright © 2003 John Wiley &amp; Sons, Ltd.