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Background In 2005, Bangladesh, India and Nepal agreed to eliminate visceral leishmaniasis (VL) as a public health problem. The approach to this was through improved case detection and treatment, and controlling transmission by the sand fly vector Phlebotomus argentipes, with indoor residual spraying (IRS) of insecticide. Initially, India applied DDT with stirrup pumps for IRS, however, this did not reduce transmission. After 2015 onwards, the pyrethroid alpha-cypermethrin was applied with compression pumps, and entomological surveillance was initiated in 2016. Methods Eight sentinel sites were established in the Indian states of Bihar, Jharkhand and West Bengal. IRS coverage was monitored by household survey, quality of insecticide application was measured by HPLC, presence and abundance of the VL vector was monitored by CDC light traps, insecticide resistance was measured with WHO diagnostic assays and case incidence was determined from the VL case register KAMIS. Results Complete treatment of houses with IRS increased across all sites from 57% in 2016 to 70% of houses in 2019, rising to >80% if partial house IRS coverage is included (except West Bengal). The quality of insecticide application has improved compared to previous studies, average doses of insecticide on filters papers ranged from 1.52 times the target dose of 25mg/m2 alpha-cypermethrin in 2019 to 1.67 times in 2018. Resistance to DDT has continued to increase, but the vector was not resistant to carbamates, organophosphates or pyrethroids. The annual and seasonal abundance of P. argentipes declined between 2016 to 2019 with an overall infection rate of 0.03%. This was associated with a decline in VL incidence for the blocks represented by the sentinel sites from 1.16 per 10,000 population in 2016 to 0.51 per 10,000 in 2019. Conclusion Through effective case detection and management reducing the infection reservoirs for P. argentipes in the human population combined with IRS keeping P. argentipes abundance and infectivity low has reduced VL transmission. This combination of effective case management and vector control has now brought India within reach of the VL elimination targets., Author summary Visceral Leishmaniasis (VL), also known as kala-azar, is a major parasitic disease in South Asia (Indian subcontinent), with 85% of the disease incidence in India. Historically VL had been controlled and almost eliminated with Indoor Residual Spraying (IRS) using dichlorodiphenyltrichloroethane (DDT). However, reinitiating this approach in 2015 failed due to high insecticide resistance in the sand fly vector and poor IRS quality, meaning that VL elimination targets were not met. To improve this the National Vector Borne Disease Control Programme changed to an effective insecticide, alpha-cypermethrin and altered the mode of application to compression pumps. Sentinel sites were established to monitor the entomological indicators, these showed the positive impact of these changes from 2016 to 2019. During this period the overall incidence of disease has decreased, and India is now on track to reach it’s target incidence for VL of less than 1/1000 people at the sub-district (block) level.

Norfolk Archaeology, 36 (4), 373-382

Norfolk Archaeology, 37 (3), 356-357

Norfolk Archaeology, 37 (3), 353-355

ObjectiveRising antibiotic resistance could reduce the effectiveness of antibiotics in preventing postoperative infections. We investigated trends in the efficacy of antibiotic prophylaxis regimens for 3 commonly performed surgical procedures—appendectomy, cesarean section, and colorectal surgery—and 1 invasive diagnostic procedure, transrectal prostate biopsy (TRPB).DesignSystematic review and meta-analysis.MethodsWe searched PubMed and Cochrane databases (through October 31, 2017) for randomized control trials (RCTs) that measured the efficacy of antibiotic prophylaxis for 4 index procedures in preventing postoperative infections (surgical site infections [SSIs] following the 3 surgical procedures and a combination of urinary tract infections [UTIs] and sepsis following TRPB).ResultsOf 399 RCTs, 74 studies (9 appendectomy, 11 cesarean section, 39 colorectal surgery, and 15 TRPB) were included. Multilevel logistic regression models with random intercepts for each study showed no statistically significant increase in SSIs over time for appendectomy (adjusted odds ratio [aOR] per year, 1.03; 95% confidence interval [CI], 0.92–1.16; P=.57), cesarean section (aOR per year, 1.01; 95% CI, 0.96–1.05; P=.80), and TRPB (aOR per year, 0.95; 95% CI, 0.77–1.18; P=.67). However, there was a significant increase in SSIs proportion following colorectal surgery (aOR per year, 1.049; 95% CI, 1.03–1.07; PConclusionThe efficacy of antibiotic prophylaxis agents in preventing SSIs following colorectal surgery has declined. Small number of RCTs and low infections rates limited our ability to assess true effect for simple appendectomy, cesarean section, or TRPB.

Objectives: Borderline personality disorder (BPD) is associated with frequent self-harm and suicidal behaviours. This study compared physician-assessed self-harm risk and intervention choice according to a (i) standard risk assessment and (ii) BPD-specific risk assessment methods. Methods: Forty-five junior and senior mental health physicians were assigned to standard or BPD-specific risk training groups. The assessment utilized a BPD case vignette containing four scenarios describing high/low lethality self-harm and chronic/new patterns of self-harm behaviour. Participants chose from among four interventions, each corresponding to a risk category. Results: Standard and BPD-specific groups were alike in their assessment of self-harm risk. Divergence occurred on intervention choice for assessments of low lethality, chronic risk ( pConclusions: Although standard and BPD-specific methods are well aligned for assessing self harm-associated risk, BPD-specific training raised awareness of BPD-appropriate interventions, particularly in the context of chronic patterns of self-harm behaviour. Wider dissemination of BPD-specific risk training may enhance the confidence of mental health clinicians in identifying the nature of self-harm risk as well as the most clinically appropriate interventions for clients with BPD.

The application of agricultural pesticides in Africa has high negative effects on human health and the environment. To analyse the effect, spatial data characterizing the environmental fate of agricultural pesticides are needed. However, poor availability and quality of data that quantify pesticide application and pesticide fate limit direct analysis of the effect. This study selected key geospatial processes affecting the environmental fate of agricultural pesticides utilizing pesticide fate models and modelled the spatial variation of each process using existing geospatial databases. Maps associated with leaching, surface runoff, sedimentation, soil storage and filtering capacity, and volatilization were created using existing geospatial datasets and, if applicable, existing methods. The potential and limitations of the created maps were discussed. An insecticide residue database was created to test the maps. The database contains 10,076 observations, but only limited number of observations remain when extracting a standard dataset for one compound. This study provided a complete set of key processes affecting pesticide fate that can be used in the identification of areas vulnerable to pesticide accumulation. The created maps have potential when used in combination with data on pesticide application or, when it is known which pesticides a crop receives, data on agricultural land use.

The application of agricultural pesticides in Africa can have negative effects on human health and the environment. The aim of this study was to identify African environments that are vulnerable to the accumulation of pesticides by mapping geospatial processes affecting pesticide fate. The study modelled processes associated with the environmental fate of agricultural pesticides using publicly available geospatial datasets. Key geospatial processes affecting the environmental fate of agricultural pesticides were selected after a review of pesticide fate models and maps for leaching, surface runoff, sedimentation, soil storage and filtering capacity, and volatilization were created. The potential and limitations of these maps are discussed. We then compiled a database of studies that measured pesticide residues in Africa. The database contains 10,076 observations, but only a limited number of observations remained when a standard dataset for one compound was extracted for validation. Despite the need for more in-situ data on pesticide residues and application, this study provides a first spatial overview of key processes affecting pesticide fate that can be used to identify areas potentially vulnerable to pesticide accumulation.

The impact of insecticide resistance in malaria vectors is poorly understood and quantified. Here a series of geospatial datasets for insecticide resistance in malaria vectors are provided, so that trends in resistance in time and space can be quantified, and the impact of resistance found in wild populations on malaria transmission in Africa can be assessed. Specifically, data have been collated and geopositioned for the prevalence of insecticide resistance, as measured by standard bioassays, in representative samples of individual species or species complexes. Data are provided for the Anopheles gambiae species complex, the Anopheles funestus subgroup, and for nine individual vector species. Data are also given for common genetic markers of resistance to support analyses of whether these markers can improve the ability to monitor resistance in low resource settings. Allele frequencies for known resistance-associated markers in the Voltage-gated sodium channel (Vgsc) are provided. In total, eight analysis-ready, standardised, geopositioned datasets encompassing over 20,000 African mosquito collections between 1957 and 2017 are released., Design Type(s)data integration objectiveMeasurement Type(s)insecticide resistanceTechnology Type(s)digital curationFactor Type(s)geographic location • temporal_intervalSample Characteristic(s)gambiae species complex • Africa • funestus subgroup • Anopheles gambiae • Anopheles arabiensis • Anopheles rivulorum • Anopheles pharoensis • Anopheles mascarensis • Anopheles funestus • Anopheles coluzzii • Anopheles melas • Anopheles quadriannulatus • Anophelinae Machine-accessible metadata file describing the reported data (ISA-Tab format)

Objectives: With increasing global interest in hospital antimicrobial stewardship (AMS) programmes, there is a strong demand for core elements of AMS to be clearly defined on the basis of principles of effectiveness and affordability. To date, efforts to identify such core elements have been limited to Europe, Australia, and North America. The aim of this study was to develop a set of core elements and their related checklist items for AMS programmes that should be present in all hospitals worldwide, regardless of resource availability. Methods: A literature review was performed by searching Medline and relevant websites to retrieve a list of core elements and items that could have global relevance. These core elements and items were evaluated by an international group of AMS experts using a structured modified Delphi consensus procedure, using two-phased online in-depth questionnaires. Results: The literature review identified seven core elements and their related 29 checklist items from 48 references. Fifteen experts from 13 countries in six continents participated in the consensus procedure. Ultimately, all seven core elements were retained, as well as 28 of the initial checklist items plus one that was newly suggested, all with >= 80% agreement; 20 elements and items were rephrased. Conclusions: This consensus on core elements for hospital AMS programmes is relevant to both high- and low-to-middle-income countries and could facilitate the development of national AMS stewardship guidelines and adoption by healthcare settings worldwide. (C) 2018 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Background Indoor residual spraying (IRS) is a key tool for controlling and eliminating malaria by targeting vectors. To support the development of effective intervention strategies it is important to understand the impact of vector control tools on malaria incidence and on the spread of insecticide resistance. In 2006, the World Health Organization (WHO) stated that countries should report on coverage and impact of IRS, yet IRS coverage data are still sparse and unspecific. Here, the subnational coverage of IRS across sub-Saharan Africa for the four main insecticide classes from 1997 to 2017 were estimated. Methods Data on IRS deployment were collated from a variety of sources, including the President’s Malaria Initiative spray reports and National Malaria Control Programme reports, for all 46 malaria-endemic countries in sub-Saharan Africa from 1997 to 2017. The data were mapped to the applicable administrative divisions and the proportion of households sprayed for each of the four main insecticide classes; carbamates, organochlorines, organophosphates and pyrethroids was calculated. Results The number of countries implementing IRS increased considerably over time, although the focal nature of deployment means the number of people protected remains low. From 1997 to 2010, DDT and pyrethroids were commonly used, then partly replaced by carbamates from 2011 and by organophosphates from 2013. IRS deployment since the publication of resistance management guidelines has typically avoided overlap between pyrethroid IRS and ITN use. However, annual rotations of insecticide classes with differing modes of action are not routinely used. Conclusion This study highlights the gaps between policy and practice, emphasizing the continuing potential of IRS to drive resistance. The data presented here can improve studies on the impact of IRS on malaria incidence and help to guide future malaria control efforts.

The morphologies of microglial arbors in brain tissue are important indicators of their state of activation, and their spatial distribution indicates patterns of tissue perturbation. This paper presents a non-parametric Bayesian approach to unsupervised quantitative profiling of microglial activation states, and mapping their 3-D spatial distributions across extended brain tissue regions imaged by mosaiced confocal microscopy. Our approach is to perform large-scale automated reconstruction of all the microglia using a learned label-consistent dictionary model for the microglial processes, and extract 136 arbor features per cell. We then fit an infinite Gaussian mixture model with collapsed Gibbs sampling to the arbor features, to discover arbor-morphological classes, their morphological ‘signatures’, and the associated covariance matrices all in an unsupervised manner. This nonparametric approach can handle clusters with arbitrarily shaped covariance matrices, perform automatic model selection, handle unbalanced clusters, and detect overlapping classes, without the need to specify the number of clusters. The results can be used for diverse investigational purposes, including: population-scale modeling, automated discovery of arbor classes and their distinguishing quantitative signatures and features, quantifying the nature and extent of the cellular heterogeneity, and spatial mapping of cellular arbor morphologies, and mapping tissue alterations.

The development of insecticide resistance in African malaria vectors threatens the continued efficacy of important vector control methods that rely on a limited set of insecticides. To understand the operational significance of resistance we require quantitative information about levels of resistance in field populations to the suite of vector control insecticides. Estimation of resistance is complicated by the sparsity of observations in field populations, variation in resistance over time and space at local and regional scales, and cross-resistance between different insecticide types. Using observations of the prevalence of resistance in mosquito species from the Anopheles gambiae complex sampled from 1,183 locations throughout Africa, we applied Bayesian geostatistical models to quantify patterns of covariation in resistance phenotypes across different insecticides. For resistance to the three pyrethroids tested, deltamethrin, permethrin, and λ-cyhalothrin, we found consistent forms of covariation across sub-Saharan Africa and covariation between resistance to these pyrethroids and resistance to DDT. We found no evidence of resistance interactions between carbamate and organophosphate insecticides or between these insecticides and those from other classes. For pyrethroids and DDT we found significant associations between predicted mean resistance and the observed frequency of kdr mutations in the Vgsc gene in field mosquito samples, with DDT showing the strongest association. These results improve our capacity to understand and predict resistance patterns throughout Africa and can guide the development of monitoring strategies.

BACKGROUND: Acinetobacter baumannii is a common cause of healthcare-associated infections. Carbapenem-resistant (CR) A baumannii is a significant threat globally. We used a large reference laboratory database to study the epidemiology of A baumannii in children in the United States. METHODS: Antimicrobial susceptibility data from The Surveillance Network were used to phenotypically identify antibiotic resistance in A baumannii isolates in children 1–17 years of age between January 1999 and July 2012. Logistic regression analysis was used to calculate trends in the prevalence of antibiotic resistance in A baumannii. Isolates from infants (

Background There is a need for effective computational methods for quantifying the three-dimensional (3-D) spatial distribution, cellular arbor morphologies, and the morphological diversity of brain astrocytes to support quantitative studies of astrocytes in health, injury, and disease. New method Confocal fluorescence microscopy of multiplex-labeled (GFAP, DAPI) brain tissue is used to perform imaging of astrocytes in their tissue context. The proposed computational method identifies the astrocyte cell nuclei, and reconstructs their arbors using a local priority based parallel (LPP) tracing algorithm. Quantitative arbor measurements are extracted using Scorcioni's L-measure, and profiled by unsupervised harmonic co-clustering to reveal the morphological diversity. Results The proposed method identifies astrocyte nuclei, generates 3-D reconstructions of their arbors, and extracts quantitative arbor measurements, enabling a morphological grouping of the cell population. Comparison with existing methods Our method enables comprehensive spatial and morphological profiling of astrocyte populations in brain tissue for the first time, and overcomes limitations of prior methods. Visual proofreading of the results indicate a >95% accuracy in identifying astrocyte nuclei. The arbor reconstructions exhibited 3.2% fewer erroneous jumps in tracing, and 17.7% fewer false segments compared to the widely used fast-marching method that resulted in 9% jumps and 20.8% false segments. Conclusions The proposed method can be used for large-scale quantitative studies of brain astrocyte distribution and morphology.

Motivation: The arbor morphologies of brain microglia are important indicators of cell activation. This article fills the need for accurate, robust, adaptive and scalable methods for reconstructing 3-D microglial arbors and quantitatively mapping microglia activation states over extended brain tissue regions. Results: Thick rat brain sections (100–300 µm) were multiplex immunolabeled for IBA1 and Hoechst, and imaged by step-and-image confocal microscopy with automated 3-D image mosaicing, producing seamless images of extended brain regions (e.g. 5903 × 9874 × 229 voxels). An over-complete dictionary-based model was learned for the image-specific local structure of microglial processes. The microglial arbors were reconstructed seamlessly using an automated and scalable algorithm that exploits microglia-specific constraints. This method detected 80.1 and 92.8% more centered arbor points, and 53.5 and 55.5% fewer spurious points than existing vesselness and LoG-based methods, respectively, and the traces were 13.1 and 15.5% more accurate based on the DIADEM metric. The arbor morphologies were quantified using Scorcioni’s L-measure. Coifman’s harmonic co-clustering revealed four morphologically distinct classes that concord with known microglia activation patterns. This enabled us to map spatial distributions of microglial activation and cell abundances. Availability and implementation: Experimental protocols, sample datasets, scalable open-source multi-threaded software implementation (C++, MATLAB) in the electronic supplement, and website (www.farsight-toolkit.org). http://www.farsight-toolkit.org/wiki/Population-scale_Three-dimensional_Reconstruction_and_Quanti-tative_Profiling_of_Microglia_Arbors Contact: broysam@central.uh.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Large tertiary care hospitals (TCHs) are thought to have higher antimicrobial resistance (AMR) rates when compared to small community hospitals (SCHs) as they provide care to patients with higher disease severity. However, we found no systematic differences in AMR rates between TCHs and SCHs in the United States.

Antibiotics have revolutionized the treatment of bacterial infections. However, it is widely held that there is underinvestment in antibiotics research and development relative to the socially optimal level for a number of reasons. In this article, we discuss whether existing health technology assessment procedures recognize the full economic and societal value of new antibiotics to patients and society when making reimbursement decisions. We present three recommendations for modelling the unique attributes of value that are specific to novel antibiotics. We find, based on a review of the literature, that some of the value elements proposed by our framework have previously been discussed qualitatively by health technology assessment bodies when evaluating antibiotics, but are not yet formally captured via modelling. We present a worked example to show how it may be possible to capture these dimensions of value in a more quantitative manner. We conclude by answering the question of the title as follows: the unique attributes of novel antibiotics should be considered in reimbursement decision making, in a way that captures the full range of benefits these important technologies bring to patients, health care systems, and society.