Spatial point analysis based on dengue surveys at household level in central Brazil

<p>Abstract</p> <p>Background</p> <p>Dengue virus (DENV) affects nonimunne human populations in tropical and subtropical regions. In the Americas, dengue has drastically increased in the last two decades and Brazil is considered one of the most affected countries. The high frequency of asymptomatic infection makes difficult to estimate prevalence of infection using registered cases and to locate high risk intra-urban area at population level. The goal of this spatial point analysis was to identify potential high-risk intra-urban areas of dengue, using data collected at household level from surveys.</p> <p>Methods</p> <p>Two household surveys took place in the city of Goiania (~1.1 million population), Central Brazil in the year 2001 and 2002. First survey screened 1,586 asymptomatic individuals older than 5 years of age. Second survey 2,906 asymptomatic volunteers, same age-groups, were selected by multistage sampling (census tracts; blocks; households) using available digital maps. Sera from participants were tested by dengue virus-specific IgM/IgG by EIA. A Generalized Additive Model (GAM) was used to detect the spatial varying risk over the region. Initially without any fixed covariates, to depict the overall risk map, followed by a model including the main covariates and the year, where the resulting maps show the risk associated with living place, controlled for the individual risk factors. This method has the advantage to generate smoothed risk factors maps, adjusted by socio-demographic covariates.</p> <p>Results</p> <p>The prevalence of antibody against dengue infection was 37.3% (95%CI [35.5–39.1]) in the year 2002; 7.8% increase in one-year interval. The spatial variation in risk of dengue infection significantly changed when comparing 2001 with 2002, (ORadjusted = 1.35; p < 0.001), while controlling for potential confounders using GAM model. Also increasing age and low education levels were associated with dengue infection.</p> <p>Conclusion</p> <p>This study showed spatial heterogeneity in the risk areas of dengue when using a spatial multivariate approach in a short time interval. Data from household surveys pointed out that low prevalence areas in 2001 surveys shifted to high-risk area in consecutive year. This mapping of dengue risks should give insights for control interventions in urban areas.</p

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

Lulu smoothers on online data

Ekonomiese En BestuurswetenskappeStatistiek & Aktuariele WetenskapPlease help us populate SUNScholar with the post print version of this article. It can be e-mailed to: [email protected]

Practical Applications of LULU smoothers

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Performance of LULU nonlinear smoothers in signal recovery

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LULU smoothers An Overview

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Characterization of a novel dsRNA element in the pine endophytic fungus Diplodia scrobiculata

Diplodia scrobiculata and Diplodia pinea are endophytic fungi associated with dieback and cankers of mainly Pinus spp. in many parts of the world. These two fungi are closely related and have, in the past, been considered to represent two morphological forms (A and B morphotypes) of D. pinea. dsRNA elements are known to occur in both D. scrobiculata and D. pinea. Two dsRNA elements from D. pinea, SsRV1 and SsRV2, have been characterized previously. The aim of this study was to characterize a third dsRNA element that is most commonly associated with D. scrobiculata and to determine its phylogenetic relationship to other mycoviruses. The 5018-bp genome of this element was sequenced, and it is referred to as D. scrobiculata RNA virus 1, or DsRV1. It has two open reading frames (ORFs), one of which codes for a putative polypeptide with a high degree of similarity to proteins of the vacuolar protein-sorting (VPS) machinery, and the other for an RNA-dependent RNA polymerase (RdRp). Phylogenetic comparisons based on amino acid sequence alignments of the RdRp revealed that DsRV1 is closely related to a dsRNA element isolated from Phlebiopsis gigantea (PgV2), and they grouped separately from virus families in which mycoviruses have previously been described. Although D. pinea and D. scrobiculata are closely related, DsRV1 does not share high sequence identity with SsRV1 or SsRV2, and they probably have different recent evolutionary origins