Basic Surveillance Research Articles

COVID-19 Social Distance Violation and Face Mask Detection in Workplaces

Social distancing is a suggested arrangement by the World Health Organization (WHO) to limit the spread of COVID-19 in broad daylight places. Most of governments and public wellbeing specialists have set the 2-meter physical removing as a compulsory security measure in retail outlets, schools, and other covered regions. In this exploration, we foster a conventional Deep Neural Network-Based model for mechanized individuals’ identification, following, and between individuals’ distances assessment in the group, utilizing basic CCTV surveillance cameras. The proposed model incorporates a YOLOv4-based system and opposite viewpoint planning for exact individuals’ identification and social removing checking in testing conditions, including individual’s impediment, incomplete perceivability, and lighting varieties. We additionally give an online danger appraisal conspire by factual examination of the Spatio-transient information from the moving directions and the pace of social removing infringement. We distinguish high-hazard zones with the most noteworthy chance of infection spread and diseases. This may assist specialists with updating the design of a public spot or to play it safe activities to relieve high-hazard zones. The effectiveness of the proposed approach is assessed on the Oxford Town Center dataset, with prevalent execution as far as precision and speed contrasted with three bests in class techniques.

Molecular Detection of Carbapenemases in Enterobacterales: A Comparison of Real-Time Multiplex PCR and Whole-Genome Sequencing

Carbapenem-resistant Enterobacterales are a growing problem in healthcare systems worldwide. While whole-genome sequencing (WGS) has become a powerful tool for analyzing transmission and possible outbreaks, it remains laborious, and the limitations in diagnostic workflows are not well studied. The aim of this study was to compare the performance of WGS and real-time multiplex PCR (RT-qPCR) for diagnosing carbapenem-resistant Enterobacterales. In this study, we analyzed 92 phenotypically carbapenem-resistant Enterobacterales, sent to the University Hospital Heidelberg in 2019, by the carbapenem inactivation method (CIM) and compared WGS and RT-qPCR as genotypic carbapenemase detection methods. In total, 80.4% of the collected isolates were identified as carbapenemase producers. For six isolates, discordant results were recorded for WGS, PCR and CIM, as the carbapenemase genes were initially not detected by WGS. A reanalysis using raw reads, rather than assembly, highlighted a coverage issue with failure to detect carbapenemases located in contigs with a coverage lower than 10×, which were then discarded. Our study shows that multiplex RT-qPCR and CIM can be a simple alternative to WGS for basic surveillance of carbapenemase-producing Enterobacterales. Using WGS in clinical workflow has some limitations, especially regarding coverage and sensitivity. We demonstrate that antimicrobial resistance gene detection should be performed on the raw reads or non-curated draft genome to increase sensitivity.

ProkEvo: an automated, reproducible, and scalable framework for high-throughput bacterial population genomics analyses.

Whole Genome Sequence (WGS) data from bacterial species is used for a variety of applications ranging from basic microbiological research, diagnostics, and epidemiological surveillance. The availability of WGS data from hundreds of thousands of individual isolates of individual microbial species poses a tremendous opportunity for discovery and hypothesis-generating research into ecology and evolution of these microorganisms. Flexibility, scalability, and user-friendliness of existing pipelines for population-scale inquiry, however, limit applications of systematic, population-scale approaches. Here, we present ProkEvo, an automated, scalable, reproducible, and open-source framework for bacterial population genomics analyses using WGS data. ProkEvo was specifically developed to achieve the following goals: (1) Automation and scaling of complex combinations of computational analyses for many thousands of bacterial genomes from inputs of raw Illumina paired-end sequence reads; (2) Use of workflow management systems (WMS) such as Pegasus WMS to ensure reproducibility, scalability, modularity, fault-tolerance, and robust file management throughout the process; (3) Use of high-performance and high-throughput computational platforms; (4) Generation of hierarchical-based population structure analysis based on combinations of multi-locus and Bayesian statistical approaches for classification for ecological and epidemiological inquiries; (5) Association of antimicrobial resistance (AMR) genes, putative virulence factors, and plasmids from curated databases with the hierarchically-related genotypic classifications; and (6) Production of pan-genome annotations and data compilation that can be utilized for downstream analysis such as identification of population-specific genomic signatures. The scalability of ProkEvo was measured with two datasets comprising significantly different numbers of input genomes (one with ~2,400 genomes, and the second with ~23,000 genomes). Depending on the dataset and the computational platform used, the running time of ProkEvo varied from ~3-26 days. ProkEvo can be used with virtually any bacterial species, and the Pegasus WMS uniquely facilitates addition or removal of programs from the workflow or modification of options within them. To demonstrate versatility of the ProkEvo platform, we performed a hierarchical-based population structure analyses from available genomes of three distinct pathogenic bacterial species as individual case studies. The specific case studies illustrate how hierarchical analyses of population structures, genotype frequencies, and distribution of specific gene functions can be integrated into an analysis. Collectively, our study shows that ProkEvo presents a practical viable option for scalable, automated analyses of bacterial populations with direct applications for basic microbiology research, clinical microbiological diagnostics, and epidemiological surveillance.

Shaping applied epidemiology workforce training to strengthen emergency response: a global survey of applied epidemiologists, 2019\u20132020

BackgroundRapid and effective emergency response to address health security relies on a competent and suitably trained local and international workforce. The COVID-19 pandemic has highlighted that the health security workforce needs to be well equipped to tackle current and future challenges. In this study, we explored whether training in applied epidemiology was meeting the current needs of the applied epidemiology workforce.MethodWe conducted a cross-sectional online survey that was available in English and French. We used purposive and snowballing sampling techniques to identify potential survey respondents. An online social media advertisement campaign was used to disseminate a REDCap survey link between October 2019 and February 2020 through field epidemiology networks. Survey questions included demographic details of participants, along with their technical background, level of formal education, topics studied during epidemiology training, and years of experience as an epidemiologist. We used Pearson Chi-squared (Chi2) to test the difference between categorical variables, and content analysis to evaluate responses to open-ended questions.ResultsIn total, 282 people responded to the survey. Participants had a range of formal public health and epidemiology training backgrounds. Respondents applied epidemiology experience spanned almost 30 years, across 64 countries. Overall, 74% (n = 210) were alumni of Field Epidemiology Training Programs (FETP). Basic outbreak and surveillance training was well reported by respondents, however training in specialised techniques related to emergency response, communication, and leadership was less common. FETP graduates reported higher levels of formal training in all survey topics.ConclusionIt is critical for the health security workforce to be well-trained and equipped with skills needed to ensure a rapid and effective response to acute public health events. Leadership, communication, interpersonal skills, and specialist training in emergency response are lacking in current training models. Our study has demonstrated that applied epidemiology workforce training must evolve to remain relevant to current and future public health challenges.

Prevention and planning as important factors in ensuring public health in the Philippines during the COVID-19 pandemic.

A recent correspondence discussed that in trying times, technology can help be applied toward epidemiology to benefit communities by building a basic surveillance system. This suggested development in Honduras can be utilized in the Philippines to improve the State’s handling of health emergencies. With this, this paper accentuates the importance of prevention and planning to ensure public health in the Philippines, especially during the COVID-19 pandemic.

Honduras: two hurricanes, COVID-19, dengue and the need for a new digital health surveillance system.

A recently published article of this journal stated that informatics solutions can guide better public health decision-making during the COVID 19 (Coronavirus Disease 2019) pandemic. Honduras is a country facing the COVID-19 pandemic with a weak health surveillance system while also fighting a dengue epidemic and the aftermath of two hurricanes that struck its territory in November 2020. In response, we as academics started a COVID-19 and Dengue Observatory combining several technological platforms and developing multidisciplinary research to help the country navigate the crisis. Mapping the pandemic and the natural disasters showed us that technology can be applied toward epidemiology to benefit communities in a time of need by quickly building a basic digital health surveillance system for Honduras.

Reliability of fetal–infant mortality rates in perinatal periods of risk (PPOR) analysis

Abstract The Fetal–Infant mortality rate (FIMR) is the basic surveillance statistic in perinatal periods of risk (PPOR) analyses. This paper presents a model for the FIMR as the ratio of two Poisson random variables. From this model, expressions for estimators of variance, standard error, and relative standard error are developed. The coverage properties of interval estimators for the FIMR are investigated in a simulation study for both small and large populations and FIMR rates. Results from these studies are applied to a PPOR analysis of NC vital records. Results suggest that the sample size guidance provided in the literature to ensure statistical reliability is overly conservative and interval construction methodology should be selected based on population size.

Research on group behavior model based on neural network computing

AbstractCompute is a term coined from the etymology of French and Latin words computer and computare respectively, so is computing. This field of computing has grown enormously over the years. From the simple, traditional Turing machine invented in 1936 by Alan Turing to the current neural network (NN) computing. NNs, a field of artificial intelligence (AI) was exhilarated from the structure and inner workings of the brain. Just as the brain is, that is, an interconnection of neurons, so is the NN which is an interconnection of basic structures known as the perceptron. They do not differ much in structure. Their only difference is that one is artificial while the other is entirely biological. The hierarchical intricacies of the NN can be represented in three layers: the perceptron, artificial NN (ANN), and deep NN (DNN). With the influx of mental and behavioral disorders, basic surveillance, and the urgency to improve the mental health of people, studying the behavioral dynamics of people is requisite. CCTV and street cameras can only do so much, thus the need to employ the field of NN which makes use of supervised learning in training the models to perfect and automate surveillance. The results of this retrospective research indicate that the use of the NN model surpasses those of traditional methods in terms of efficiency and reliability.

The effect of medication related clinical decision support at the time of physician order entry

Background In advanced clinical decision support systems, patient characteristics and laboratory values are included in the algorithms that generate alerts. These alerts have a higher specificity than basic medication surveillance alerts. The alerts of advanced clinical decision support systems can be shown directly to the prescriber during order entry, without the risk of generating an overload of irrelevant alerts. We implemented five advanced algorithms that are shown directly to the prescriber. These algorithms are for gastrointestinal prophylaxis, folic or folinic acid prescribed with orally or subcutaneously administered methotrexate, vitamin D prescribed with bisphosphonates, hyponatremia and measuring plasma levels for vancomycin and gentamicin. Objective We evaluated the effect of the implementation of the algorithms. Setting We performed prospective intervention studies with a historical group for comparison in both inpatients and outpatients at a teaching hospital in the Netherlands. Methods We compared the time period after implementation of the algorithm with the time period before implementation, using data from the hospital information system Epic. Difference in guideline adherence were analyzed using Chi square tests. Main outcome measure The outcome measures were the number of alerts, the acceptance rate of the advice in the alert, and for the algorithm measuring plasma levels for vancomycin and gentamicin the time to the correct dose. Results For all algorithms, the implementation resulted in a significant increase in guideline adherence, varying from 11 to 36%. The acceptance rate varied from 14% for hyponatremia to 90% for methotrexate. For gastrointestinal prophylaxis the acceptance rate was 4.4% for basic drug-drug interaction alerts when no gastrointestinal prophylaxis was prescribed and increased to 44.7% after implementation of the advanced algorithm. This algorithm substantially decreased the number of alerts from 812 before implementation to 217 after implementation. After implementation of the algorithm for measuring plasma levels for vancomycin and gentamicin, the proportion of patients receiving the correct dose after 48h increased from 73 to 84% (p = 0.03). Conclusion Implementation of advanced algorithms that take patient characteristics into account and are shown directly to the physician during order entry, result in an increased guideline adherence.

COVID19-world: a shiny application to perform comprehensive country-specific data visualization for SARS-CoV-2 epidemic

BackgroundData analysis and visualization is an essential tool for exploring and communicating findings in medical research, especially in epidemiological surveillance.ResultsData on COVID-19 diagnosed cases and mortality, from January 1st, 2020, onwards is collected automatically from the European Centre for Disease Prevention and Control (ECDC). We have developed a Shiny application for data visualization and analysis of several indicators to follow the SARS-CoV-2 epidemic using ECDC data. A country-specific tool for basic epidemiological surveillance, in an interactive and user-friendly manner. The available analyses cover time trends and projections, attack rate, population fatality rate, case fatality rate, and basic reproduction number.ConclusionsThe COVID19-World online web application systematically produces daily updated country-specific data visualization and analysis of the SARS-CoV-2 epidemic worldwide. The application may help for a better understanding of the SARS-CoV-2 epidemic worldwide.

Biochemical changes among municipal solid waste sorting workers: implications for personal protective equipment availability and use

Background. Solid waste management has emerged as one of the greatest challenges facing human and environmental health. Municipal solid waste workers are potentially exposed to a variety of occupational biohazards and safety risks in the workplace. Objective. This study aimed to evaluate the availability and use of personal protective equipment (PPE) and some biochemical changes among solid waste sorting workers. Methods. A group of solid waste sorting workers was interviewed and checked for availability, use and appropriateness of PPE using a structured questionnaire and checklist. Workers were tested for hepatic and renal function parameters and biomarkers of allergy and inflammation. Results. The level of high-sensitivity C-reactive protein (hsCRP) as a biomarker of inflammation was elevated in 12.9% while total serum immunoglobulin E was obviously high among most workers (79.2%). Workers with inadequately available, used or effective PPE were more likely to have morbidities and showed elevated serum levels of serum glutamic pyruvic transaminase, serum glutamic-oxaloacetic transaminase, urea, creatinine, hsCRP and total immunoglobulin E. Conclusions. Elevated biomarkers of allergy and inflammation herald preclinical disease risks that should be included in basic health surveillance. Use of PPE should be emphasized for workers involved in solid waste sorting to effectively protect their health.

Genomic analysis of Staphylococcus capitis isolated from blood cultures in neonates at a neonatal intensive care unit in Sweden

Emergence of a genetically distinct, multidrug-resistant Staphylococcus capitis clone (NRCS-A) present in neonatal intensive care units has recently been extensively reported. The aims of the present study were to investigate which clones of S. capitis isolated from blood in a Swedish neonatal intensive care unit (NICU) have been present since 1987 and to investigate whether the NRCS-A clone has disseminated in Sweden. All S. capitis isolates from blood cultures of neonates (≤ 28 days of age) between 1987 and 2017 (n = 46) were whole-genome sequenced, and core genome multilocus sequence typing (cgMLST) was performed. Single-nucleotide polymorphism (SNP)-based phylogenetic relationships between the S. capitis isolates and in silico predictions of presence of genetic traits specific to the NRCS-A clone were identified. Furthermore, antibiotic susceptibility testing, including screening for heterogeneous glycopeptide-intermediate resistance, was performed. Thirty-five isolates clustered closely to the isolates previously determined as belonging to the NRCS-A clone and had fewer than 81 core genome loci differences out of 1063. Twenty-one of these isolates were multidrug resistant. The NRCS-A clone was found in 2001. Six pairs of isolates had differences of fewer than two SNPs. Genetic traits associated with the NRCS-A clone such as nsr, ebh, tarJ, and CRISPR were found in all 35 isolates. The increasing incidence of S. capitis blood cultures of neonates is predominantly represented by the NRSC-A clone at our NICU in Sweden. Furthermore, there were indications of transmission between cases; adherence to basic hygiene procedures and surveillance measures are thus warranted.

Health facility preparedness for cholera outbreak response in four cholera-prone districts in Cameroon: a cross sectional study

BackgroundThe risk of cholera outbreak remains high in Cameroon. This is because of the persistent cholera outbreaks in neighboring countries coupled with the poor hygiene and sanitation conditions in Cameroon. The objective of this study was to assess the readiness of health facilities to respond to cholera outbreak in four cholera-prone districts in Cameroon.MethodologyA cross-sectional study was conducted targeting all health facilities in four health districts, labeled as cholera hotspots in Cameroon in August 2016. Data collection was done by interview with a questionnaire and by observation regarding the availability of resources and materials for surveillance and case management, access to water, hygiene, and sanitation. Data analysis was descriptive with STATA 11.Principal findingsA total of 134 health facilities were evaluated, most of which (108/134[81%]) were urban facilities. The preparedness regarding surveillance was limited with 13 (50%) health facilities in the Far North and 22(20%) in the Littoral having cholera case definition guide. ORS for Case management was present in 8(31%) health facilities in the Far North and in 94(87%) facilities in the littoral. Less than half of the health facilities had a hand washing protocol and 7(5.1%) did not have any source of drinking water or relied on unimproved sources like lake. A total of 4(3.0%) health facilities, all in the Far North region, did not have a toilet.ConclusionsThe level of preparedness of health facilities in Cameroon for cholera outbreak response presents a lot of weaknesses. These are present in terms of lack of basic surveillance and case management materials and resources, low access to WaSH. If not addressed now, these facilities might not be able to play their role in case there is an outbreak and might even turn to be transmission milieus.

Developing the active larval indices surveillance system for dengue solution in low and high dengue risk primary care units, Southern Thailand

Purpose The purpose of this paper is to develop an active larval indices surveillance system and compare the outcomes of the implementation in primary care units (PCUs) at low and high risk of dengue. Design/methodology/approach The study design was conducted by implementing a community participation action research system in low and high dengue risk PCUs in Lansaka district, Nakhon Si Thammarat province, in the Southern Region of Thailand. There were five phases to the process including preparation of all stakeholders, situation assessment, development of the surveillance system, program implementation and evaluation. The system was developed in ten villages that were categorized as either low dengue risk PCUs (comprising six villages) or high dengue risk PCUs (four villages). A village was assigned as being at high or low dengue risk according to pre-determined criteria. The low dengue risk PCU assessments were conducted on a seven-step active larval indices surveillance system where PCU officials were additionally involved in coordinating, teaching, coaching and supporting the village health volunteers (VHVs) for dengue prevention activities. The high dengue risk PCUs, on the other hand, only followed a basic larval indices surveillance system with no follow-up support. Findings The outcomes of using intervention systems showed that the VHVs’ dengue knowledge and larval indices understanding in both PCUs increased significantly (p<0.01). Furthermore, the low dengue risk PCUs had a higher larval indices level than the high dengue risk PCU (p<0.01). Originality/value This study showed that the low dengue risk PCU followed an active larval indices surveillance system at the sub-district level which is appropriate for villages. This study also revealed that VHVs are needed to strengthen the capacity in terms of knowledge and skills of developing such a system to ensure reduced levels of dengue in the community.

Real-Time Advisory System Mitigates Drilling Vibrations in a Lateral Section

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 188942, “Mitigating Drilling Vibrations in a Lateral Section Using a Real-Time Advisory System,” by J.R. Bailey, SPE, and G.S. Payette, SPE, ExxonMobil; M.T. Prim, J. Molster, and A.W. Al Mheiri, Zakum Development; P.G. McCormack, SPE, Halliburton; and K. LeRoy, Pason Systems, prepared for the 2017 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, 13–16 November. The paper has not been peer reviewed. A real-time drilling-data analysis and recommendation system that leverages surface drilling data was deployed in a lateral section of a well from an artificial island in Abu Dhabi. A key objective of this technology was to provide the driller with an easy-to-use display of a novel drilling-performance map. This paper presents data from the demonstration run, illustrates the features of this technology, and provides general observations on optimization of drilling parameters in this hole section. Background A research prototype drilling advisory system (DAS) was set up on an island rig with a wellsite information transfer specification (WITS) data feed from the mud-logger cabin over a fiber-to-serial cable to the computer in the driller’s cabin. The DAS helps the driller make decisions for managing controllable drilling parameters to enable a high rate of penetration (ROP) and low vibrations. The system uses surface data only (i.e., data obtained from sensors instrumented on surface equipment) from the mud logger. The platform then analyzes the data and displays basic surveillance information, including heat maps that vary with the controllable drilling parameters. On the basis of this data and processing algorithms, the system makes recommendations for the controllable parameter values. Data from three intervals were analyzed, and two of the three saw contrasting trends of stick/slip [torsional severity estimate (TSE)] and mechanical specific energy (MSE) with increasing rotary speed, whereas one interval did not see such a tradeoff. The complex interplay between these dysfunctions requires an application-specific real-time advisory system to provide optimal drilling performance. The control variables for this drilling application were ROP and rotary speed. Intervals for Data Analysis The 8½-in. drilling interval started from the 9 5/8-in. casing shoe at 13,916 ft, and section total depth was called at 23,974 ft. Drilling data from this interval was subdivided into seven intervals corresponding to drilling tests, with parameter recommendations from the DAS analysis. Examples of Drilling-Parameter Optimization To initiate the DAS, the driller conducts a drilling test by starting the calibration mode on the advisory system to reset the system memory. Parameter set-point values then must be maintained relatively constant for a time sufficient to determine good average values for the drilling response. The advisory system requires a statistically significant sampling of data at stationary parameter values. When several such calibration points have been recorded, the system then provides automated analysis of the drilling test for the span of operating parameters. If the formation changes over this interval substantially, the calibration process should be repeated.

Development of a molecular serotyping scheme and a multiplexed luminex-based array for Providencia

Providencia is an opportunistic human pathogen that belongs to the Enterobacteriaceae family. The bacterial cell surface O-antigen is one of the most structurally variable cell constituents and serves as a basis for serotyping gram-negative bacteria. In this work, the genomes of 12 Providencia strains were sequenced, and genes driving O-antigen biosynthesis were analyzed. The O-antigen-synthesizing genes of Providencia are located in the O-antigen gene cluster (OGC) between the cpxA and yibK genes. The gene functions predicted in silico agreed with the known O-antigen structures. All clusters were found to contain both wzx and wzy and exhibit a high degree of heterogeneity. Based on the sero-specific genes, we developed a molecular serotyping system to detect 23 serotypes (from the present and previous studies) for the first time. Five Proteus strains, five Morganella strains, five uropathogenic Escherichia coli (UPEC) strains and 32 Providencia strains with other serotypes were used to assess the specificity of our multiplexed Luminex-based array. Five serogroups (O3, O8, O19, O38 and O52 strains) were used to determine the sensitivity of the suspension array. The detection sensitivity was 0.1 ng genomic DNA, 103 CFU/ml in pure culture, or 104 CFU/ml in mock urine specimens. Furthermore, 29 publicly available Providencia genomes (which have not been serotyped) were analyzed, and 23 novel putative OGC types were identified. In total, we identified 35 new OGCs and developed a molecular serotyping system based on the sero-specific genes. The established classification system can support promising applications in basic research, clinical diagnosis, and epidemiological surveillance.

English

Epidemiologic and traceback evidence of Salmonella infection is not much in many developing countries including Burkina Faso. This study investigates the antimicrobial resistance and distribution of Salmonella serotypes isolated from diverse sources in Burkina Faso. 615 Salmonella serotypes isolated from beef meat, poultry carcasses, poultry, swine, cattle, hedgehog, fish, salad, channel and humans from 2009 to 2011 were analyzed to identify their diversity and distribution among the samples. The Salmonella strains were subjected to antimicrobial sensitivity tests using disk diffusion methods, were analyzed and classified into 110 serotypes, with the most prevalent serotype being Derby (91/615) found in beef meat, poultry carcasses, poultry and fish; Muenster (48/615) found in cattle, swine, hedgehog, poultry, human and fish; Chester (38/615) found in poultry carcasses, swine and poultry feces; Hato (32/615) found in beef meat, poultry carcasses, cattle and poultry; Drac (30/615) found in cattle, hedgehog and fish; and Typhimurium (21/615) found in cattle, poultry, human and fish. Among the 615 Salmonella strains, 94% (581/615) were resistant to one or more antibiotics; resistance to streptomycin was the most common. The resistance pattern, Str-Sul-Tet, Str-Tet and Str-Sul was dominant and found in 80% of the strains. About 3% of the strains were resistant to 5 or 6 antibiotics; their resistance pattern is amp-str-sul-tet-tmp or amp-chl-str-sul-tet-tmp. One Salmonella strain, S. Kentucky isolated from human stool was resistant to eight antibiotics; the resistance pattern is amp-str-sul-tet-cip-gen-nal-mec. Findings from this study can help define the guidelines for basic surveillance system of Salmonella and other enteropathogenic bacteria circulating among humans, animals, food and environment. Key words: Salmonella, environment, human, risk.

Rationale and design of ASPIRE-ICU: a prospective cohort study on the incidence and predictors of Staphylococcus aureus and Pseudomonas aeruginosa pneumonia in the ICU

BackgroundThe epidemiology of ICU pneumonia caused by Staphylococcus aureus (S. aureus) and Pseudomonas aeruginosa (P. aeruginosa) is not fully described, but is urgently needed to support the development of effective interventions. The objective of this study is to estimate the incidence of S. aureus and P. aeruginosa ICU pneumonia and to assess its association with patient-related and contextual risk factors.MethodsASPIRE-ICU is a prospective, observational, multi-center cohort study nested within routine surveillance among ICU patients in Europe describing the occurrence of S. aureus and P. aeruginosa ICU pneumonia. Two thousand (2000) study cohort subjects will be enrolled (50% S. aureus colonized) in which specimens and data will be collected. Study cohort subjects will be enrolled from a larger surveillance population, in which basic surveillance data is captured. The primary outcomes are the incidence of S. aureus ICU acquired pneumonia and the incidence of P. aeruginosa ICU acquired pneumonia through ICU stay.The analysis will include advanced survival techniques (competing risks and multistate models) for each event separately as well as for the sub-distribution of ICU pneumonia to determine independent association of outcomes with risk factors.. A risk prediction model will be developed to quantify the risk for acquiring S. aureus or P. aeruginosa ICU pneumonia during ICU stay by using a composite score of independent risk factors.DiscussionThe diagnosis of pathogen-specific ICU pneumonia is difficult, however, the criteria used in this study are objective and comparable to those in the literature.Trial registrationThis study is registered on clinicaltrials.gov under identifier NCT02413242.

Subepithelial esophageal tumors: a single-center review of resected and surveilled lesions

Subepithelial esophageal tumors (SETs) are frequent incidental findings. Although symptomatic tumors are surgically or endoscopically resected, there is no consensus on the management of asymptomatic esophageal leiomyomas. Appropriate International Classification of Diseases, Ninth Revision codes followed by medical record review were used to identify patients with SETs from January 1992 to March 2017, with abstraction of basic demographics, surveillance intervals, and mortality. Patients were contacted to complete a phone questionnaire to assess follow-up as well as the validated Brief Esophageal Dysphagia Questionnaire (BEDQ). Eighty-four leiomyomas, 5 leiomyosarcomas, 13 GI stromal tumors (GISTs), and 4 granular cell tumors were found. Among patients with leiomyomas, 58 (69%) were resected and 26 (31%) were followed under surveillance. Resected esophageal leiomyomas were larger than those under surveillance (49.7mm vs 17.9mm, P< .003). Esophageal leiomyoma growth during surveillance was only .5mm over a mean 70-month follow-up (range, 4-288). No malignant transformation was seen, and only 2 patients required subsequent resection. The phone survey was completed by 35 patients and revealed minimal symptom burden, with only 2 patients (15%) under esophageal leiomyoma surveillance reporting symptoms (BEDQ score≥10) over a mean 96.7-month follow-up. EUS had high diagnostic accuracy with a positive predictive value of 68% and a negative predictive value of 100% for leiomyomas or GISTs compared with surgical pathology. EUS demonstrated high diagnostic accuracy in resected SETs. Esophageal leiomyomas demonstrate minimal growth or symptomatic progression. Therefore, long-term EUS surveillance of small asymptomatic esophageal leiomyomas may be unnecessary.

An MPC‐based position controller for a tilt‐rotor tricopter VTOL UAV

SummaryThis study presents a novel framework, namely, the fusion of a conventional controller and a linear model predictive controller, for the position control of a tilt‐rotor tricopter. While the conventional controller in the outer loop is responsible for the position control, the inner‐loop model predictive control–based controller handles the angular dynamics and vertical body velocity. Furthermore, a novel control allocation algorithm for the proposed controller is introduced. In addition, this study also covers mathematical modeling and trim analysis of the tilt‐rotor tricopter dynamics. An evaluation of the designed control system is accomplished with a nonlinear 6‐degree‐of‐freedom simulation model of the tilt‐rotor tricopter in which realistic actuator limitations are considered. The efficiency of the proposed control algorithm is elaborated for a trajectory tracking problem where basic surveillance operation is considered. The simulation results show that the proposed model predictive controller is able to provide a satisfactory trajectory tracking performance under the realistic actuator limits.