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New tools for evaluating LQAS survey designs.

ABSTRACT: Lot Quality Assurance Sampling (LQAS) surveys have become increasingly popular in global health care applications. Incorporating Bayesian ideas into LQAS survey design, such as using reasonable prior beliefs about the distribution of an indicator, can improve the selection of design parameters and decision rules. In this paper, a joint frequentist and Bayesian framework is proposed for evaluating LQAS classification accuracy and informing survey design parameters. Simple software tools are provided for calculating the positive and negative predictive value of a design with respect to an underlying coverage distribution and the selected design parameters. These tools are illustrated using a data example from two consecutive LQAS surveys measuring Oral Rehydration Solution (ORS) preparation. Using the survey tools, the dependence of classification accuracy on benchmark selection and the width of the 'grey region' are clarified in the context of ORS preparation across seven supervision areas. Following the completion of an LQAS survey, estimation of the distribution of coverage across areas facilitates quantifying classification accuracy and can help guide intervention decisions.

SUBMITTER: Hund L

PROVIDER: S-EPMC3931287 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature

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New tools for evaluating LQAS survey designs.

Hund Lauren L

Emerging themes in epidemiology 20140215 1

Lot Quality Assurance Sampling (LQAS) surveys have become increasingly popular in global health care applications. Incorporating Bayesian ideas into LQAS survey design, such as using reasonable prior beliefs about the distribution of an indicator, can improve the selection of design parameters and decision rules. In this paper, a joint frequentist and Bayesian framework is proposed for evaluating LQAS classification accuracy and informing survey design parameters. Simple software tools are provi ...[more]

PMID: 24528928

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Project description:Clustered regularly interspaced short palindromic repeats (CRISPRs) comprise a family of short DNA repeat sequences that are separated by non repetitive spacer sequences and, in combination with a suite of Cas proteins, are thought to function as an adaptive immune system against invading DNA. The number of CRISPR arrays in a bacterial chromosome is variable, and the content of each array can differ in both repeat number and in the presence or absence of specific spacers. We utilized a comparative sequence analysis of CRISPR arrays of the plant pathogen Erwinia amylovora to uncover previously unknown genetic diversity in this species. A total of 85 E. amylovora strains varying in geographic isolation (North America, Europe, New Zealand, and the Middle East), host range, plasmid content, and streptomycin sensitivity/resistance were evaluated for CRISPR array number and spacer variability. From these strains, 588 unique spacers were identified in the three CRISPR arrays present in E. amylovora, and these arrays could be categorized into 20, 17, and 2 patterns types, respectively. Analysis of the relatedness of spacer content differentiated most apple and pear strains isolated in the eastern U.S. from western U.S. strains. In addition, we identified North American strains that shared CRISPR genotypes with strains isolated on other continents. E. amylovora strains from Rubus and Indian hawthorn contained mostly unique spacers compared to apple and pear strains, while strains from loquat shared 79% of spacers with apple and pear strains. Approximately 23% of the spacers matched known sequences, with 16% targeting plasmids and 5% targeting bacteriophage. The plasmid pEU30, isolated in E. amylovora strains from the western U.S., was targeted by 55 spacers. Lastly, we used spacer patterns and content to determine that streptomycin-resistant strains of E. amylovora from Michigan were low in diversity and matched corresponding streptomycin-sensitive strains from the background population.

Project description:BackgroundExperimental treatments for Ebola virus disease (EVD) might reduce EVD mortality. There is uncertainty about the ability of different clinical trial designs to identify effective treatments, and about the feasibility of implementing individually randomised controlled trials during an Ebola epidemic.Methods and findingsA treatment evaluation programme for use in EVD was devised using a multi-stage approach (MSA) with two or three stages, including both non-randomised and randomised elements. The probabilities of rightly or wrongly recommending the experimental treatment, the required sample size, and the consequences for epidemic outcomes over 100 d under two epidemic scenarios were compared for the MSA, a sequential randomised controlled trial (SRCT) with up to 20 interim analyses, and, as a reference case, a conventional randomised controlled trial (RCT) without interim analyses. Assuming 50% 14-d survival in the population treated with the current standard of supportive care, all designs had similar probabilities of identifying effective treatments correctly, while the MSA was less likely to recommend treatments that were ineffective. The MSA led to a smaller number of cases receiving ineffective treatments and faster roll-out of highly effective treatments. For less effective treatments, the MSA had a high probability of including an RCT component, leading to a somewhat longer time to roll-out or rejection. Assuming 100 new EVD cases per day, the MSA led to between 6% and 15% greater reductions in epidemic mortality over the first 100 d for highly effective treatments compared to the SRCT. Both the MSA and SRCT led to substantially fewer deaths than a conventional RCT if the tested interventions were either highly effective or harmful. In the proposed MSA, the major threat to the validity of the results of the non-randomised components is that referral patterns, standard of care, or the virus itself may change during the study period in ways that affect mortality. Adverse events are also harder to quantify without a concurrent control group.ConclusionsThe MSA discards ineffective treatments quickly, while reliably providing evidence concerning effective treatments. The MSA is appropriate for the clinical evaluation of EVD treatments.

Project description:BackgroundSchistosomiasis control programmes primarily use school-based surveys to identify areas for mass drug administration of preventive chemotherapy. However, as the spatial distribution of schistosomiasis can be highly focal, transmission may not be detected by surveys implemented at districts or larger spatial units. Improved mapping strategies are required to accurately and cost-effectively target preventive chemotherapy to remaining foci across all possible spatial distributions of schistosomiasis.MethodsHere, we use geostatistical models to quantify the spatial heterogeneity of Schistosoma haematobium and S. mansoni across sub-Saharan Africa using the most comprehensive dataset available on school-based surveys. Applying this information to parameterise simulations, we assess the accuracy and cost of targeting alternative implementation unit sizes across the range of plausible schistosomiasis distributions. We evaluate the consequences of decisions based on survey designs implemented at district and subdistrict levels sampling different numbers of schools. Cost data were obtained from field surveys conducted across multiple countries and years, with cost effectiveness evaluated as the cost per correctly identified school.ResultsModels identified marked differences in prevalence and spatial distributions between countries and species; however, results suggest implementing surveys at subdistrict level increase the accuracy of treatment classifications across most scenarios. While sampling intensively at the subdistrict level resulted in the highest classification accuracy, this sampling strategy resulted in the highest costs. Alternatively, sampling the same numbers of schools currently recommended at the district level but stratifying by subdistrict increased cost effectiveness.ConclusionsThis study provides a new tool to evaluate schistosomiasis survey designs across a range of transmission settings. Results highlight the importance of considering spatial structure when designing sampling strategies, illustrating that a substantial proportion of children may be undertreated even when an implementation unit is correctly classified. Control programmes need to weigh the increased accuracy of more detailed mapping strategies against the survey costs and treatment priorities.

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New tools for evaluating LQAS survey designs.

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New tools for evaluating LQAS survey designs.

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