283 research outputs found

    Spatio-temporal modelling of malaria incidence for evaluation of public health policy interventions in Ghana, West Africa

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    Malaria is a major challenge to both the public health and the socio-economic development of Ghana. Major factors which account for this situation include poor environmental conditions and the lack of prevention services. In spite of the numerous intervention measures, the disease continues to be the most prevalent health problem in the country. The risk assessment reports for Ghana were based on household surveys which provide inadequate data for accurate analysis of incidence cases. This poses a serious threat to planning and management for the health care delivery system in Ghana. Malaria transmission varies with geographical location and time (or season). Spatio-temporal modelling coupled with adequate data has shown to better define the public burden of the disease, providing risk maps to describe the incidence variation in space and time and also identifying high risk areas for health policy implementation. Geostatistics contributes immensely to the prediction of the random processes distributed in space or time in epidemiological studies. In this study, we conduct spatial statistical analysis of malaria incidence to produce evidence-based monthly maps of Ghana illustrating the patterns of malaria risk over space and time. This is achieved using monthly morbidity cases reported on the disease from public health facilities at district level and population data over the period 1998-2010 to compute the malaria incidence rates, being the number of reported cases per unit resident population of 10,000. Lognormal ordinary kriging is used to model the spatial and temporal correlations, and then back-transformed to estimate the monthly malaria risk at local level. The space-time experimental variogram describing the correlations structure is modelled with nested spherical and exponential-cosine functions coupled with nugget effect. The modelled variogram indicate both short and long spatial and temporal dependence of the malaria incidence rates at local level with the temporal component exhibiting an increasing seasonal pattern of period of 12 months. The results also indicate varied spatial distribution of malaria incidence across the country, the highest risk being observed in the northern most and several locations in central and western parts of the country, and lowest in some areas in the north and south along the coast. This statistical-based model approach of malaria epidemiology will be useful for short-term prediction and also provide a basis for resource allocation for the disease’s control in the country

    Trade-off assessments between reading cost and accuracy measures for digital camera monitoring of recreational boating effort

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    Digital camera monitoring is increasingly being used to monitor recreational fisheries. The manual interpretation of video imagery can be costly and time consuming. In an a posteriori analysis, we investigated trade-offs between the reading cost and accuracy measures of estimates of boat retrievals obtained at various sampling proportions for low, moderate and high traffic boat ramps in Western Australia. Simple random sampling, systematic sampling and stratified sampling designs with proportional and weighted allocation were evaluated to assess trade-offs in terms of bias, accuracy, precision, coverage rate and cost in estimating the annual total number of powerboat retrievals in 10,000 jackknife resampling draws. The relative standard error (RSE ± standard deviations) obtained by the sampling designs for sampling proportions from 0.4 onwards were below a 20 % threshold for three of the sampling designs across the three boat ramps. Coverage rates of over 90 % were observed for the confidence intervals for the estimated annual number of powerboat retrievals, with low relative standard errors (RSE \u3c 20 %). Interpreting 40 % of camera footage within a year provided the minimum level to obtain sufficient accuracy measures for all sampling designs considered. The stratified random sampling design with weighted allocation consistently resulted in the smallest variance for estimates of annual powerboat retrievals across the various sampled proportions. These findings have the potential to considerably reduce the cost of manual data interpretation, since operating cost increased linearly with increasing sampling proportion

    Imputation of missing data from time-lapse cameras used in recreational fishing surveys

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    While remote camera surveys have the potential to improve the accuracy of recreational fishing estimates, missing data are common and require robust analytical techniques to impute. Time-lapse cameras are being used in Western Australia to monitor recreational boating activities, but outages have occurred. Generalized linear mixed effect models formulated in a fully conditional specification multiple imputation framework were used to reconstruct missing data, with climatic and some temporal classifications as covariates. Using a complete 12-month camera record of hourly counts of recreational powerboat retrievals, data were simulated based on ten observed camera outage patterns, with a missing proportion of between 0.06 and 0.61. Nine models were evaluated, including Poisson and negative binomial models, and their associated zero-inflated variants. The imputed values were cross-validated against actual observations using percent bias, mean absolute error, root mean square error, and skill score as performance measures. In 90% of the cases, 95% confidence intervals for the total imputed estimates from at least one of the models contained the total actual counts. With no systematic trends in performance among the models, zero-inflated Poisson and its bootstrapping variant models consistently ranked among the top 3 models and possessed the narrowest confidence intervals. The robustness and generality of the imputation framework were demonstrated using other camera datasets with distinct characteristics. The results provide reliable estimates of the number of boat retrievals for subsequent estimates of fishing effort and provide time series data on boat-based activity

    Biplots for compositional data derived from generalized joint diagonalization methods

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    Biplots constructed from principal components of a compositional data set are an established means to explore its features. Principal Component Analysis (PCA) is also used to transform a set of spatial variables into spatially decorrelated factors. However, because no spatial structures are accounted for in the transformation the application of PCA is limited. In geostatistics and blind source separation a variety of different matrix diagonalization methods have been developed with the aim to provide spatially or temporally decorrelated factors. Just as PCA, many of these transformations are linear and so lend themselves to the construction of biplots. In this contribution we consider such biplots for a number of methods (MAF, UWEDGE and RJD transformations) and discuss how and if they can contribute to our understanding of relationships between the components of regionalized compositions. A comparison of the biplots with the PCA biplot commonly used in compositional data analysis for the case of data from the Northern Irish geochemical survey shows that the biplots from MAF and UWEDGE are comparable as are those from PCA and RJD. The biplots emphasize different aspects of the regionalized composition: for MAF and UWEDGE the focus is the spatial continuity, while for PCA and RJD it is variance explained. The results indicate that PCA and MAF combined provide adequate and complementary means for exploratory statistical analysis

    Using intervention analysis to evaluate the trends in release rates of recreational fisheries following extensive management changes

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    Changes to management of a fisheries resource are often required to ensure ongoing sustainability. However, such changes can sometimes lead to unintended effects such as increased release rates and associated post-release mortality. These effects may be highly variable between species and areas. Recreational fishing management changes were introduced on the west coast of Australia in 2009/10 to recover stocks of demersal scalefish. Key changes included reducing mixed species bag limits across management zones and increasing the minimum size limit for one species in some management zones. The restrictive catch limits resulted in increased release rates of key demersal species. However, whether such increases are significant and sustained over time, and thus of management concern, have not been evaluated. We carried out intervention time series analysis to evaluate the impact of management changes on release rates of four key demersal species for the recreational sector in metropolitan and regional management zones covering ∼8° latitude using an 18-year time series of charter recreational fishery data from July 2002 to January 2020. We observed varying responses in release rates by species and zones, the most common of which were a step increase, a ramp and a temporary increase that decayed. These responses may be related to targeted management changes which influenced fisher behaviour, perceived recreational value of some species and recruitment variation. Our study demonstrates that intervention analysis, which has seen limited use in this context, can assist in evaluating the impact of management changes on different species for recreational fisheries

    Improving processing by adaption to conditional geostatistical simulation of block compositions

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    Exploitation of an ore deposit can be optimized by adapting the beneficiation processes to the properties of individual ore blocks. This can involve switching in and out certain treatment steps, or setting their controlling parameters. Optimizing this set of decisions requires the full conditional distribution of all relevant physical parameters and chemical attributes of the feed, including concentration of value elements and abundance of penalty elements. As a first step towards adaptive processing, the mapping of adaptive decisions is explored based on the composition, in value and penalty elements, of the selective mining units. Conditional distributions at block support are derived from cokriging and geostatistical simulation of log-ratios. A one-to-one log-ratio transformation is applied to the data, followed by modelling via classical multivariate geostatistical tools, and subsequent back-transforming of predictions and simulations. Back-transformed point-support simulations can then be averaged to obtain block averages that are fed into the process chain model. The approach is illustrated with a \u27toy\u27 example where a four-component system (a value element, two penalty elements, and some liberable material) is beneficiated through a chain of technical processes. The results show that a gain function based on full distributions outperforms the more traditional approach of using unbiased estimates

    Drowning - a scientometric analysis and data acquisition of a constant global problem employing density equalizing mapping and scientometric benchmarking procedures

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    Background: Drowning is a constant global problem which claims proximately half a million victims worldwide each year, whereas the number of near-drowning victims is considerably higher. Public health strategies to reduce the burden of death are still limited. While research activities in the subject drowning grow constantly, yet there is no scientometric evaluation of the existing literature at the present time. Methods: The current study uses classical bibliometric tools and visualizing techniques such as density equalizing mapping to analyse and evaluate the scientific research in the field of drowning. The interpretation of the achieved results is also implemented in the context of the data collection of the WHO. Results: All studies related to drowning and listed in the ISI-Web of Science database since 1900 were identified using the search term "drowning". Implementing bibliometric methods, a constant increase in quantitative markers such as number of publications per state, publication language or collaborations as well as qualitative markers such as citations were observed for research in the field of drowning. The combination with density equalizing mapping exposed different global patterns for research productivity and the total number of drowning deaths and drowning rates respectively. Chart techniques were used to illustrate bi- and multilateral research cooperation. Conclusions: The present study provides the first scientometric approach that visualizes research activity on the subject of drowning. It can be assumed that the scientific approach to this topic will achieve even greater dimensions because of its continuing actuality

    Granulysin-Expressing CD4+ T Cells as Candidate Immune Marker for Tuberculosis during Childhood and Adolescence

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    BACKGROUND: Granulysin produced by cytolytic T cells directly contributes to immune defense against tuberculosis (TB). We investigated granulysin as a candidate immune marker for childhood and adolescent TB. METHODS: Peripheral blood mononuclear cells (PBMC) from children and adolescents (1-17 years) with active TB, latent TB infection (LTBI), nontuberculous mycobacteria (NTM) infection and from uninfected controls were isolated and restimulated in a 7-day restimulation assay. Intracellular staining was then performed to analyze antigen-specific induction of activation markers and cytotoxic proteins, notably, granulysin in CD4(+) CD45RO(+) memory T cells. RESULTS: CD4(+) CD45RO(+) T cells co-expressing granulysin with specificity for Mycobacterium tuberculosis (Mtb) were present in high frequency in TB-experienced children and adolescents. Proliferating memory T cells (CFSE(low)CD4(+)CD45RO(+)) were identified as main source of granulysin and these cells expressed both central and effector memory phenotype. PBMC from study participants after TB drug therapy revealed that granulysin-expressing CD4(+) T cells are long-lived, and express several activation and cytotoxicity markers with a proportion of cells being interferon-gamma-positive. In addition, granulysin-expressing T cell lines showed cytolytic activity against Mtb-infected target cells. CONCLUSIONS: Our data suggest granulysin expression by CD4(+) memory T cells as candidate immune marker for TB infection, notably, in childhood and adolescence
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