Evidence about the impact of the pandemic of COVID-19 on the incidence rates of blood cultures contaminations and bloodstream infections in intensive care units (ICUs) remains scant. The objective of this study was to investigate the nationwide epidemiology of positive blood cultures drawn in ICUs during the first two pandemic waves of COVID-19 in Switzerland.We analyzed data on positive blood cultures among ICU patients, prospectively collected through a nationwide surveillance system (ANRESIS), from March 30, 2020, to May 31, 2021, a 14-month timeframe that included a first wave of COVID-19, which affected the French and Italian-speaking regions, an interim period (summer 2020) and a second wave that affected the entire country. We used the number of ICU patient-days provided by the Swiss Federal Office of Public Health as denominator to calculate incidence rates of blood culture contaminations and bloodstream infections (ICU-BSI). Incidence rate ratios comparing the interim period with the second wave were determined by segmented Poisson regression models.versus interim period), we observed an increased incidence of blood culture contaminations  and ICU-BSI .A total of 1099 blood culture contaminations and 1616 ICU-BSIs were identified in 52 ICUs during the study. Overall, more episodes of blood culture contaminations and ICU-BSI were observed during the pandemic waves, compared to the interim period. The proportions of blood culture contaminations and ICU-BSI were positively associated with the ICU occupancy rate, which was higher during the COVID-19 waves. During the more representative second wave (An increase in blood culture contaminations and ICU-BSIs was observed during the second COVID-19 pandemic wave, especially in months when the ICU burden of COVID-19 patients was high.The online version contains supplementary material available at 10.1186/s13054-021-03814-z. The pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-related infection COVID-19) is affecting health systems worldwide. In Switzerland, a first wave of the COVID-19 pandemic predominantly involved the French and Italian-speaking regions over the period February to May 2020, while a second wave started in October 2020 and affected the entire country until May 2021. During these months, hospitals, and in particular intensive care units (ICUs) had to deal with several challenges, such as patient overflow, staff reinforcements by physicians and nurses with limited or no experience in intensive care practices, and, especially during the first wave, transient or sustained shortages in personal protective or supportive equipment 9 is affe–9, especWe analyzed national, epidemiological and microbiological data on positive blood cultures among ICU patients prospectively collected by the Swiss Centre for Antibiotic Resistance (ANRESIS) and epidemiological data provided by the COVID-19 surveillance conducted by the Swiss Federal Office of Public Health (FOPH) from March 30, 2020, to May 31, 2021.https://eucast.org) or Clinical and Laboratory Standards Institute  guidelines. All laboratories are participating in at least one external quality program of either the Swiss quality control program issued by the Institute for Medical Microbiology, University of Zürich (http://www.imm.uzh.ch/services/qc.html), or the National External Quality Assessment Service . We included data on ICU isolates from those Swiss hospitals that sent information on a regular basis during the entire study period. Included hospitals are listed in Additional file versus university) and location (city and canton).ANRESIS regularly receives information on all positive blood cultures from over 30 Swiss microbiology laboratories, some of them collecting data from multiple hospitals. Hospitals are distributed across the country and represent at least 80% of annual hospitalization days . Specieshttps://www.covid19.admin.ch).Starting March 30, 2020, the FOPH collected detailed data on Swiss hospital’s occupancy regarding patients with and without COVID-19. Aggregated data on the daily number of hospitalized ICU patients (with and without COVID-19) as well as ICU capacity and occupancy (in percent) in each center were recorded by the cantonal health authorities and then transmitted to the FOPH. Data are freely available on the website of the FOPH (blood culture contamination or ICU-BSI. Possible skin contaminants were identified according to the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) Patient Safety Component Manual  for blood culture contaminations, ICU-BSI and specific microorganisms between the interim and second wave were evaluated by segmented Poisson regression models using aggregated monthly data, and patient-days as off-set. Since the surveillance of the FOPH on the hospital occupation during the COVID-19 pandemic started on March 30, 2020, data about the first wave were incomplete and were therefore excluded from this analysis. Overdispersion was tested using the likelihood ratio test with subsequent fitting of a negative binomial model, if required. Finally, we performed a confirmatory analysis for blood culture contamination using a Poisson regression model investigating the effect of the second wave and introducing the time and the interaction between time and second wave.The statistical analysis included five steps. First, baseline characteristics of the patients related to the episodes depending on pandemic period were compared with chi-square and Kruskal–Wallis tests, as appropriate. Second, we performed descriptive analyses of the whole study period focusing on monthly total number and incidence  and SAS (version 9.4).  studies .As the analysis has been performed on anonymized non-genetic surveillance data, ethical consent was not required according to the Swiss law for research on humans .N = 237) or from patients abroad (N = 50). Of the 2′715 remaining episodes collected in 52 ICUs, 1099 were considered as blood culture contaminations and 1616 as ICU-BSIs, according to the aforementioned definitions  were more frequently detected in older patients hospitalized in university hospitals. At the same time, blood culture contamination proportions (contrary to ICU-BSI proportions) were higher in the two waves than in the interim period.During the study, 29′270 blood culture episodes were reported to ANRESIS, of which 2′912 were collected among ICU patients. A total of 287 episodes were excluded, either because identified among children under 16 years of age  and ICU-BSI  during the second wave compared to the interim period  was observed during the second wave, whereas other microorganisms responsible for ICU-BSI did not show significant trends. A confirmatory analysis on secular trends of blood culture contamination using a Poisson regression model investigating the effect of the second wave and introducing the time and the interaction between time and second wave showed similar results , mainly driven by samplings from peripheral veins . In anot to 16.5%Our results support these findings by means of a large dataset that includes 2′715 episodes of positive blood cultures collected in 52 ICUs at a national level. The vast majority of these episodes were caused by CoNS. Possible factors behind this increase include: the oversight of basic infection control practices by reallocated staff with limited or no experience in intensive care; an inadequate diligence with aseptic techniques due to ICU overcrowding; the urgency of blood sampling among critically ill patients; the implementation of ad hoc standardized protocols that envision the sampling of otherwise unneeded blood cultures; and the inexperience in wearing personal protective equipment (PPE). Contamination of blood cultures has been associated with increased antibiotic exposure, prolonged venous access, additional consultations, laboratory and diagnostic requests, prolonged hospitalizations, costs and intra-hospital mortality , 18. Thei.e., when the entire country was affected), although to a lesser extent than blood culture contamination. When we examined specific pathogen classes, we found a significant increase in candidemia. This may reflect the role of immunosuppressive drugs among COVID-19 patients, mainly used during the second wave, as previously suggested [We found that ICU-BSI rates significantly increased during the epidemiologically more relevant second wave  were not available in both datasets. Moreover, data on COVID-19 status for each patient with a bacteremia episode were not available. Second, since the date of hospital admission was unavailable in a substantial number of episodes, the true proportion of healthcare associated infections (HAI), as well as of early and late ICU-BSI is unknown. Third, data on the number of negative blood cultures were not available, which could influence the total number of contaminations. To overcome this possible sampling bias, we used data on patient days – which may represent a surrogate of the impact of the pandemic on the ICU occupancy —as denomThese limitations notwithstanding, we believe that our analysis of nationwide data is representative and provides results that may be relevant for quality management during future pandemics. Efforts to maintain infection prevention and control measures at the highest standard even in challenging settings are paramount and could safe patient lives.An increase in blood culture contaminations and ICU-BSIs was observed during the second COVID-19 pandemic wave, especially in months when the ICU burden of COVID-19 patients was high. Our results highlight the fact that compliance with basic infection prevention and control measures should not be ignored even in challenging a challenging setting such as a pandemic.Additional file 1. Figure S1. Swiss map with the included ICU sites. Figure S2. Flowchart of the included blood culture episodes during the study after exclusion of episodes identified outside ICU, among children under 16 years of age or from patients abroad. Figure S3. Correlations of the ICU occupation due to all patients with blood culture contaminations incidence (A), ICU-BSI incidence (B) and percentage of blood culture contaminations (C). Figure S4. Weekly count of blood culture episodes reported to ANRESIS over the period 01.01.2018 –31.05.2021. Figure S5. Confirmatory analysis on secular trends of blood culture for the intermediate and second pandemic period using a Poisson regression model.


The CRISPR/Cas9-based system for targeted mutagenesis has become an indispensable tool for functional genetics in plants. CRISPR/Cas9 allows users to generate loss-of-function alleles in genes of interest with precision and in a simple-to-use system. This manuscript outlines important points to consider for experimental design and utilization of CRISPR/Cas9 in targeted mutagenesis in maize. It also introduces the pRGEB32-BAR vector modified for use in maize that allows simultaneous delivery of multiple gRNAs using a simple assembly. Vector selection, gRNA design, genetic strategies, and genotyping approaches are discussed, with an emphasis on achieving isolation of homozygous mutant plants in a time- and cost-efficient manner. The emergence of precision DNA nuclease tools, and CRISPR/Cas9 in particular, has made gene editing for targeted gene disruption accessible for even small laboratories. The simplicity of vector design and assembly means that researchers with little technical experience in molecular cloning or genetic engineering can generate targeted mutations in genes of interest for use in functional genetic characterization. The increased access and feasibility of using CRISPR for functional genetics does not mean that the process is necessarily rapid, simple, or inexpensive, however. One major bottleneck for using CRISPR-based gene disruption in maize has been access to transformation protocols or services, but rapid expansion in these areas is occurring. Other points of constraint are centered around the cost, time, and space required to isolate useful CRISPR-generated alleles in the needed combinations and appropriate genetic backgrounds for functional analyses. These less-considered, but important, constraints are discussed here, and recommendations are offered for streamlining the development of experiment-ready plants for functional genetic studies.First demonstrated as a functional tool in mammalian cells in 2012 , the varSome basic concepts regarding CRISPR biology and use need to be introduced to facilitate this discussion. The CRISPR/Cas9 toolset is a two-component system composed of a DNA nuclease (Cas9) that uses a separate single-stranded guide RNA (gRNA) to recognize and cut specific DNA sequences. By stably or transiently expressing Cas9 and gRNAs designed to bind target DNA sequences, it is possible to cause double-stranded cuts precisely at desired locations. As DNA repair machinery in a cell “fixes” the DNA break through non-homologous end joining, small deletions or insertions that lead to gene disruption result. To utilize CRISPR for functional genetics, gRNAs are designed to recognize the target gene(s) and expressed alongside Cas9. If successful, mutations in the target gene(s) result, providing loss-of-function alleles for genetic characterization.Importantly, the use of CRISPR for functional genetics in a system like maize is a time- and resource-intensive undertaking, largely due to the demands of growing generations of plants and the genotyping needed to isolate desired alleles in relevant combinations for experimentation. Identification and isolation of effective alleles in inbred backgrounds and in the desired combinations can require multiple generations and a daunting amount of genotyping to track alleles. Multiple loss-of-function alleles for each gene target are needed so that observed phenotypes can be confidently associated with gene disruption rather than linked loci. Before properly-controlled experiments can take place, the Cas9-expressing transgene should be eliminated by genetic selection and mutant alleles should be isolated as homozygotes in inbred backgrounds. Conducting plant transformation in inbred lines (like B104 in maize) is highly desirable so that wildtype control plants are available for phenotypic comparisons to mutants.Streptococcus pyogenes driven by the rice ubiquitin promoter; (2) a custom polycistronic gRNA assembly (precursor for one or more gRNAs) driven by the rice U3 snoRNA (Pol III) promoter; and (3) HPTII (hygromycin resistance) driven by the 35S promoter. Advantages of expressing multiple gRNAs in a single transcript include simplicity of vector design and construction and the use of only a single gRNA-expressing promoter. The pRGEB32 vector used here was modified by replacing the hygromycin selectable marker with the BAR gene (confers glufosinate-ammonium resistance), facilitating this vector’s use in maize. The modified vector is available on Addgene.com under pRGEB32-BAR  targeting potentially redundant genes; and (2) saving on transformation costs. By targeting all members of a gene family using a single transgene, double, triple, or higher-order mutants can be obtained more quickly than by stacking multiple independently-derived mutants through crossing and selection. In many crop species, and particularly in maize with its relatively recent genome duplication ,14, genechopchop.cbu.uib.no [cirspr.hzau.edu.cn/CRISPR2/ [One of the advantages of using CRISPR/Cas9 lies in the flexibility regarding potential target sites. Generally, any 20-nucleotide sequence followed by an NGG protospacer adjacent motif (PAM) is a viable target, so there are effectively never cases where CRISPR cannot target genomic regions. Important considerations for gRNA design include location within the target gene, presence of targeted regions in gene splice variants, multi-gene targeting for single gRNAs, and potential off-target binding sites. To improve the chances of obtaining complete loss of function alleles, gRNAs are usually targeted near the 5-prime region of genes and in coding sequence retained in all splice variants. Redundant genes can often be targeted in conserved regions by a single gRNA, though 100% sequence identity along 23 nucleotides that terminate in an NGG is a major constraint. There are a variety of web-based, free-to-use tools available to assist in design and selection of gRNAs in plants, including CHOPCHOP  and CRISPR2/ ,18), botCRISPR2/ ,12. Whil0) plants by PCR and Sanger sequencing revealed the occurrence of edits for the majority of gRNA binding sites. Only 4 out of 30 gRNAs did not result in detected edits in T0 plants. The efficiency rates for the 30 gRNAs is shown in For the purposes of this communication, a summary of 30 gRNAs success rates and efficiencies are presented, though the target genes are not discussed as functional analyses for these genes are ongoing. The web-based tool CHOPCHOP (v3) was used to select best-suited gRNAs for targeted mutagenesis of 20 candidate genes and Agrobacterium-based plant transformation was conducted in B104 embryonic callus at Iowa State University Plant Transformation Facility. Screening of first generation transgenic  usually results in numerous alleles in each of the target genes. At least two effective alleles, usually the largest deletions in non-multiples of three, are selected for future isolation as homozygotes and experimentation. The T0 plants carrying the selected alleles are back-crossed to the wildtype inbred and the resulting F1 seed provides the basis for allele isolation in the next two generations. In cases where suitable alleles for functional characterization are not identified in T0 plants, additional screening for mutant alleles in F1 plants can be conducted. Occasionally gRNAs have low efficiency rates and it is necessary to genotype many plants to find suitable alleles.To isolate CRISPR-derived alleles as homozygous and transgene-free, three generations of plants are usually required after Cas9-driven allele generation in T0 plants. Genotyping F1 plants by PCR for the presence of the transgene, followed by genotyping for the chosen alleles in the target genes, allows for identification of transgene-free plants containing the desired alleles. It is critical to remove the transgene before progressing to mutant isolation as expression of Cas9 and gRNAs may continue to cause new mutations in F1 or later generations, which can complicate genotyping and confuse future experiments. Self-pollination of transgene-free plants produces F2 segregating families wherein homozygous, non-transgenic mutants in the desired combinations can be identified. The most important consideration in determining the number of F1 plants needed is the number of genes targeted by the transgenic construct. For a single allele, and assuming normal gamete transmission, 25% of plants are expected to have the desired combination of transgene-free and target allele positive. If more alleles were targeted simultaneously and need to be isolated separately as single mutants or stacked , the number of needed F1 plants increases exponentially. For example, if alleles in three different target genes are all present in a T0 plant, F1 plants from a backcross of that plant are expected to contain any specific combination of alleles at a rate of 1:16, so more F1 plants need to be grown and genotyped.F1 offspring of plants containing selected alleles for characterization are genotyped to identify plants containing the desired alleles and not containing the Cas9-expressing transgene. The F1 plants are expected to segregate 1:1 for transgene absence or presence because the initial transgene is usually present as a single-copy heterozygote in TSegregating F2 families containing selected alleles and absent the transgene are genotyped for the desired allele combinations, usually homozygous mutations in the target genes. Again, the number of plants needed to obtain the desired combination of alleles scales with the number of target genes present in a given line. If more than a few gene mutants are being stacked to create triple, quadruple, or higher-order mutants, it is unlikely that the homozygous mutants will be identified in the initial F2 family. In these cases, planting self-pollinated ears from individuals containing all desired alleles and fixed as homozygous in as many possible will allow isolation of correct combinations in later generations.0 plants are bi-allelic (containing different mutations in one or both gene copies) and PCR amplification results in two similar, but not exact, products that cannot be separated on an agarose gel. In most cases, bi-allelic PCR products can still be interpreted by careful examination of Sanger sequencing chromatograms, despite two distinct DNA fragments being present  and time-consuming, it is the most reliable method for tracking alleles and provides certainty that the intended allele is being tracked. Some alleles, particularly large (>30 bases) deletions or insertions can be distinguished on agarose gels, which can save time and expense when alleles need to be tracked across many individuals and multiple generations. It may be worthwhile to screen many transgene-positive F1 plants for uncommon, large, easy-to-genotype alleles before advancing to isolation of alleles in desired combinations for functional studies. For mutations that cannot be distinguished on agarose gels, higher-throughput and less expensive methods compared to Sanger sequencing of PCR products are available, including high-resolution melting curve analysis , fluores0 plants or tracking alleles in segregating populations [In cases where very large numbers of transgenic plants or gRNA targets need to be genotyped, high-throughput sequencing approaches can be most efficient for initial allele identification in Tulations ,24,25. TBy using the CRISPR/Cas9 system, researchers can target any gene or gene family for mutagenesis, representing an incredible leap forward for functional genetics. The technology is powerful, simple to use, and accessible, providing a precise and flexible tool for researchers that far surpasses mutagenesis resources of the past. Still, it is important to have realistic expectations regarding costs, timelines, and likely outputs for CRISPR-based mutagenesis. Considering the points discussed herein prior to initiating CRISPR-based projects will increase efficiency and help prevent unnecessary mistakes.


High-speed, optical-sectioning imaging is highly desired in biomedical studies, as most bio-structures and bio-dynamics are in three-dimensions. Compared to point-scanning techniques, line scanning temporal focusing microscopy (LSTFM) is a promising method that can achieve high temporal resolution while maintaining a deep penetration depth. However, the contrast and axial confinement would still be deteriorated in scattering tissue imaging. Here, we propose a HiLo-based LSTFM, utilizing structured illumination to inhibit the fluorescence background and, thus, enhance the image contrast and axial confinement in deep imaging. We demonstrate the superiority of our method by performing volumetric imaging of neurons and dynamical imaging of microglia in mouse brains in vivo. Optical-sectioning capability is highly desired in biomedical imaging, as biological cells and tissues are generally in three-dimensions. To achieve optical-sectioning, confocal laser-scanning microscopy was proposed to spatially filter out out-of-focus information with a conjugated pinhole ,2,3. In Line-scanning two-photon microscopy (LSTPM) can improve temporal resolution by shaping the excitation beam into a thin line, which thus simplifies two-dimensional scanning into one-dimensional scanning. However, the improvement of temporal resolution in LSTPM is at the cost of axial resolution, since the beam is focused only along one spatial dimension . Thus, lTo overcome the effects of tissue scattering on the excitation and/or the emission beams in wide-field two-photon imaging, one can employ either adaptive optics (AO) ,20,21 orStructured illumination-based optical-sectioning microscopy was developed to relieve the scattering issues in wide-field imaging, including structured illumination microscopy (SIM-OS) ,25 and HHere, we propose the HiLo-based LSTFM, which not only ensures high temporal resolution with one-time imaging, but also further depresses scattering through HiLo method. Benefiting from the fact that the HiLo method does not need well-defined excitation patterns, we can take the Gaussian intensity distribution of the illumination line as a naturally structured modulation. In this way, HiLo-based LSTFM does not need to take an additional structured illumination image and thus save the temporal resolution. We demonstrate the superiority of our method by volumetric imaging of neurons and dynamical imaging of microglia in mouse brains in vivo.f = 60 mm) and lens 2 , the laser beam was expended and projected onto the surface of a 1D galvo-scanner  with a 5-mm diameter. A laser line was then formed on the surface of a diffraction grating  after passing through a cylinder lens . The spectral components of the femtosecond pulses were then spatially dispersed due to grating diffraction. After passing through the lens 3 , dichroic mirror , and objective , the spatio-temporal focused line with Gaussian distribution along the scanning direction /positions, and used gray squares to indicate sampling camera pixels. As shown in Different from conventional HiLo microscopy, the two images required to reconstruct an optical-sectioning image, namely uniform illumination image and structured illumination image  to the weighted uniformly-illuminated image:The in-focus low-frequency components then can be constructed by applying a low-pass filter , which is recorded by operating the camera at a sub-array of 200 lines to perform extended detection [x axis, indicated by the dashed line in 2 fitted curve is also shown as a blue curve. It suggests that the intensity difference between the center and two adjacent values is negligible, and the fitting of Gaussian2 distribution agrees well with expectations.It should be noticed that the intensity difference between the central line and its adjacent line in the camera recorded raw image is negligible, which thus will not affect the uniformity of uniform illumination image. However, when deviating from the central line, the intensity difference becomes evident, which ensures a deep modulation depth of the structured illumination image. To verify the claim above, we performed in vivo imaging of neurons in Thy1-YFP mouse, at a depth of 80 µm under the dura. Considering the illumination line is of Gaussian distribution, the two-photon excited fluorescence should follow the distribution of Gaussian square  in vivo. After craniotomy, acute imaging of neurons in the cerebral cortex in the living mice under anesthesia were performed, as described in . The imaWe further investigated the axial confinement enhancement of our proposed method. Solid lines in We then perform volumetric imaging of microglia cells in living CX3CR1-GFP mice (JAX No. 005582) in vivo to demonstrate the superiority of our method. The procedure of acute imaging of CX3CR1-GFP mice in vivo is similar as above. The imaging depth is 120–130 μm under the dura, and axial interval is 2 μm. The exposure time for each acquisition is 100 ms. We also performed dynamic imaging of microglial cells in CX3CR1-GFP mouse brains at a depth of 100–130 μm, under the dura. We set the axial interval as 2 μm, and exposure time for each acquisition as 100 ms. Specifically, we recorded the images in a stack of 30 μm thickness over 48 min. In To depress tissue scattering and ensure high temporal resolution in wide-field, optical-sectioning imaging, here we propose a HiLo-based LSTFM, which can enhance the image contrast and axial confinement. We demonstrate the superiority of our method by volumetric imaging in vivo. We compare the contrast and axial confinement of images achieved by the virtual confocal slit detection method, extended detection followed by computational reconstruction method, and our proposed HiLo based method. It shows that the latter two methods can improve image contrast and axial confinement, however, the extended detection method may introduce artifacts in computational reconstruction (deconvolution). To further demonstrate the robustness of our method, we also perform dynamical imaging of microglial cells in CX3CR1-GFP mice.Different from conventional HiLo microscopy, only one-time imaging is necessary in our HiLo based method. We take the Gaussian intensity distribution of illumination line as a naturally structured modulation; thus, the uniform illumination image and structured illumination image can be achieved by sampling the camera recorded images in different ways. Compared to LSTFM based on extended detection and computational reconstruction, the reconstruction here is more efficient. With a laser of higher pulse energy, the imaging depth can be increased further. We expect its broad applications in high-speed volumetric imaging of biological dynamics.


Background: A growing body of evidence from high-income contexts suggests a strong association between sexual violence victimisation and self-harm and eventual suicide. However, both sexual violence and self-harm among adolescents are still less researched in sub-Saharan African countries, including Ghana.Objectives: To estimate the 12-month prevalence of self-harm, and to describe the associated factors and reported reasons for self-harm among school-going adolescent survivors of sexual violence victimisation during the previous 12 months in urban Ghana.Methods: Analytic data came from a regional-based representative cross-sectional survey including in-school youth  conducted in 2017 within the Greater Accra Region of Ghana. Of these, 297 (17.2%) self-reported sexual violence victimisation in the previous 12 months; this proportion of the participants (n = 297) was the focus of the current study. Items measuring sexual violence victimisation, self-harm, and correlates were adopted from the 2012 Ghana WHO–Global School-based Student Health Survey and the Child and Adolescent Self-harm in Europe Study. Data analysis involved multivariable logistic regression models.Results: The estimate of self-harm ideation during the previous 12 months was 45.8% (95% CI: 40–52), whereas the estimate of self-harm behaviour was 38.7% (95% CI: 33–44). About two in five of the participants who reported self-harm wanted to die by their last episode of the behaviour. While bullying victimisation was associated with increased odds of self-harm ideation  and behaviour , weekly alcohol use , conflict with parents , and physical abuse victimisation  showed strong associations with increased odds of self-harm behaviour in the past 12 months.Conclusions: The evidence underscores the need for both universal and targeted multi-level intervention and prevention programmes to mitigate the offence of sexual violence and reduce the chances of self-harm among adolescent survivors of sexual violence in urban Ghana. According to the World Health Organisation (WHO), sexual violenceBesides poor academic outcomes and negative social and interpersonal problems, sexual violence victimisation among adolescents is associated with a wide-range of negative mental and physical health outcomes, including HIV and other sexually transmitted infections, broken bones, head trauma, depression, anxiety, and post-traumatic stress disorder  , family dysfunctions , and mental health problems  are at an elevated risk of self-harm and even suicide  single-item: “Has anyone forced you  to engage in sexual activities against your will during the past 12 months?” Two hundred and ninety-seven (297) of the 1,692 adolescent participants reported sexual violence victimisation during the 12 months preceding the survey—this represented the analytic sample for the current study .The questionnaire for the survey was in English, the language of instructions in schools in Ghana and the official language and lingua franca of the country. The measures included in this study covered demographic variables, lifestyle and social adversity factors, and outcome variables. The list of variables and specific questions used to assess them in the survey are provided in the weekly alcohol use , parental separation/divorce (Have your parents separated or divorced during the past 12 months?), conflict with parents (Have you had any serious arguments or fights with either or both of your parents during the past 12 months?), conflict between parents (Have your parents had any serious arguments or fights during the past 12 months?), bullying victimisation , and physical abuse victimisation —see Nine binary (No or Yes) response rated lifestyle factors and variables assessing the experience of social and interpersonal adversities, adopted mainly from the 2012 WHO–Global School-based Student Health Survey (WHO-GSHS) questionnaire used in Ghana WHO,  were incNine socio-demographic variables were included: gender , age, family structure (measured by father's number of wives), living arrangement, primary caretaker, caretaker's employment status, religious group, romantic relationship status, and sexual orientation—see Self-harm during the previous 12 months was the main outcome variable in this study. This was assessed with a dichotomous (No = 0 or Yes = 1) response rated single item: “Have you, actually, intentionally harmed yourself  during the past 12 months?” This study also assessed the experience of self-harm ideationSimilarly, a 15-item checklist of frequently reported reasons or motivations for self-harm were adopted from the WHO/EURO Multicentre Study on self-harm . In keeping with the research ethics of the Ghana Education Service, permissions were sought from the heads and management of all the participating schools. Prior to responding to the survey, each participant signed an actual written consent; parents and guardians of underage participants provided consent, while participants aged 17 years and younger assented prior to taking part in the study.pb) test . Missing responses were deleted list-wise during the analysis, as the loss of cases due to missing data was <5% Graham, . The Supp < 0.05 was used to determine statistically significant results.Adjusted and unadjusted multivariable logistic regression models were used to explore the possible associations between the exposures and the binary outcome variables, self-harm ideation and behaviour in the past 12 months. Variables included in the logistic regression models were considered regardless of the statistical significance of their bivariate relationships with the outcome variables ; the participants were aged between 14 and 19 years . There were more females  than males . Most participants  reported having a father who had more than one wife.p = 0.001]. Bullying victimisation [p = 0.002], physical abuse victimisation [p = 0.004], and alcohol use [p = 0.004] showed significant bivariate relationships with self-harm ideation.The estimate of self-harm ideation during the previous 12 months was 45.8% (95% CI: 40–52), whereas the estimate of self-harm behaviour was 38.7% (95% CI: 33–44). As shown in p < 0.001]. Participants who experienced bullying victimisation [p < 0.001], reported alcohol use [p < 0.001], and physical abuse victimisation [p = 0.001], and those who identified as non-heterosexual [p = 0.001] were also likely to report self-harm behaviour during the previous 12 months. Age showed no statistically significant bivariate relationship with neither self-harm ideation  nor self-harm behaviour .Similarly, adolescent survivors of sexual violence victimisation who reported conflict with their parents were likely than those who reported no conflict with their parents to report self-harm behaviour ) is higher, relative to the estimates of self-harm among the general population of adolescents across the region of sub-Saharan Africa   emotional well-being, cognitive development, and mental health of the individual  and adverse social experiences  have strong associations with increased odds of self-harm. This evidence is consistent with findings from a longitudinal study from South Africa , family context , and the school environment . At the macro-level, it is strongly recommended that the government of Ghana and its stakeholder agencies  continue to give full cooperation to the support lend by UNICEF toward the effective implementation of various child protection policies and social intervention programmes  were females. While this disproportionate distribution potentially skews the results to be more applicable to females, it also precluded meaningful stratification and sub-group analysis of the data in terms of gender. Notably however, this observation is not intended to mean that the effects of sexual violence victimisation on females is more harmful than on males; sexual violence victimisation is troubling for both females and males in the immediate and long-terms.Furthermore, in this cross-sectional survey both the outcome and exposure variables were measured at the same point in time; this means that the findings reported in this study cannot support causal interpretations. It is also important to point out that the current study failed to include some key variables related to mental health—for example, depression, hopelessness, and anxiety—which have been found to mediate the association between sexual violence victimisation and self-harm . Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin.The author confirms being the sole contributor of this work and has approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


SARS-CoV-2 infection rates in children and adolescents are often underestimated due to asymptomatic or oligosymptomatic infections. Seroprevalence studies can reveal the magnitude of “silent” infections in this age group and help to assess the risk of infection for children but also their role in spreading the disease. In total, 2045 children and their parents from the Ruhr region were finally included after the exclusion of drop-outs. Seroconversion rates among children of all age groups increased from 0.5% to 8% during the study period and were about three to fourfold higher than the officially registered PCR-based infection rates. Only 41% recalled symptoms of infection; 59% were asymptomatic. In 51% of the infected children, at least one parent also developed SARS-CoV-2 antibodies. Depending on local incidences, the rates of seroconversion rose to different levels during the study period. Although the dynamics of infection within the study cohort mirrors local incidence, the figure of SARS-CoV-2 infections in children and adolescents appears to be high. Reported contact with SARS-CoV-2-infected individuals in the same household carries a high risk of infection. SARS-CoV-2 infections in children are diagnosed less frequently than in adults ,2. ReasoSeroconversion studies, however, show that the infection rate in children and adolescents is probably similar to adults. Population-based approaches have shown very different percentages of seroconversion in different parts of the world and vary within countries ,5,6. The® IgM and IgG qualitative antibody assay (directed at the nucleocapsid antigen (N—antigen)).Asymptomatic children and adolescents (and their parents) who attended outpatient pediatric practices from June 2020 to February 2021 in the Ruhr region, located in Western Germany, for scheduled mandatory routine examinations (U—untersuchungen) from 6 months to 18 years of age were invited to participate in the study. None of the participants were vaccinated against SARS-CoV-2 at the time of the study. The participants and their parents were asked to fill in a tablet-based questionnaire available in 5 different languages. The questionnaire included questions about former SARS-CoV-2 infection and exposure to SARS-CoV-2-infected individuals. Serum samples were analyzed for SARS-CoV-2 IgM and IgG antibodies using the Roche ElecsysCase counts of acute SARS-CoV-2 infections defined by positive PCR were registered in Germany on a weekly basis by the Robert-Koch Institute (RKI) and stratified by age and county . Here, tTo directly compare the observed seroprevalence in the CorKid cohort with the confirmed cases reported by the Robert-Koch Institute (RKI), an age-standardization procedure was used. Both seroprevalence as well as confirmed cumulative cases were given monthly per year of life. Population data were retrieved for the three counties represented the most in the CorKid cohort and were used to calculate age-stratified per capita registered cumulative case counts. Then, using the age distribution of the CorKid cohort as weights, standardized total per capita counts were calculated to allow for a direct comparison with the observed total seroprevalence.Confidence intervals (CIs) for the monthly observed total seroprevalence were computed as exact 95% CIs for proportions to obtain a monthly confidence band. Furthermore, the ratio of the total seroprevalence to the standardized cumulative cases was calculated per month using the lower and upper limits of the confidence band for the seroprevalence to obtain a confidence band for the ratio.Alternatively, a logistic function, b and e serve as dummy parameters without significance for the purpose of total curve evaluation. The package also offers the computation of confidence bands based on the delta method, which was used here to quantify the precision of the estimated ratio of total seroprevalence to standardized cumulative cases.Mathematical analysis was performed using statistical programming language R . ParticuThe majority of the 2184 children tested for SARS-CoV-2 antibodies within the scope of the CorKid survey come from Gütersloh, followed by Herne, Bochum and two further minor represented counties cf. . The incThe observed seroprevalence is described in monthly intervals from June 2020 through February 2021 (the study period), to assess the temporal behavior. The same holds for the cumulative case numbers publicly reported by the Robert-Koch Institute (RKI) for the three most represented counties. The overall proportion of seropositive children (index children) observed in a first examination in the CorKid survey amounts to 2.5% (52/20930) (note the drop-out due to failures of testing). Thereof, 36 children were examined a second time after a median term of 197 days. Thereby, an additional number of 3 children tested seropositive, such that total seropositivity amounts to 2.6% (55/2090). However, an approximately exponential increase in seroprevalence from about zero to roughly 8% within the CorKid cohort during the study period can be observed .The cumulative number of cases reported by the RKI  were ageThe comparison of the seroprevalence obtained in the CorKid survey with the RKI-confirmed cumulative cases was either based on a direct ratio of the observed seroprevalence to the reported cumulative cases or on the ratio between the predicted seroprevalence from a nonlinear regression curve to the cumulative cases. While nonlinear regression has theoretical evidence and is, therefore, the preferred method of choice, we opted to show the results side by side  to allowSARS-CoV-2 infections in children and adolescents have been reported with varying frequencies throughout the pandemic, ranging from 0.5 to 5% of the total infection rate ,2,7 deteThe reported frequency of symptomatic SARS-CoV-2 infections in children and adolescents ranges from 16 to 55%, suggesting that at least half of the actual infection events pass unnoticed ,10,11.Asymptomatic children and adolescents were more likely to not be tested for SARS-CoV-2 before routine testing was introduced roughly from winter 2020 onward or earlier, depending on the country in Europe, and, therefore, infection chains largely remain unclear. Nevertheless, several studies describe household transmission as a major risk factor ,12. In lThe limitations of the study include a selection bias caused by different clientele in the pediatric practices which participated in the study. Furthermore, waning immunity can play a role in participants with delayed serological tests after infection, which may give rise to an underestimated seroprevalence. Finally, we assumed a sufficiently high precision of the antibody tests used. Presumably high specificity does not entail a serious limitation; however, non-optimal sensitivity, as described in other cohorts with PCR-confirmed SARS-CoV-2 infections , may leaSeroconversion rates reveal a high percentage of undetected SARS-CoV-2 infections in children and adolescents. This substantial number of unreported cases among children should be considered in policies of preventive measures.


The clinical validation of the NADAL COVID-19 antigen test  started in eight Slovenian long-term health care facilities in October 2020. The purpose of clinical validation is to implement the test into the everyday working process in long-term care (LTC) facilities and demonstrate how it can be used to mitigate the spread of the virus in these environments. The facilities compared the results of antigen tests to the results obtained using Cobas 6800 SARS-CoV-2 real-time reverse transcription polymerase chain reaction (RT-PCR) . Sensitivity  and specificity  of the NADAL COVID-19 antigen test were good. Rapid antigen testing served well for early detection of infection and helped to prevent and control spread of the SARS Cov2 in six out of eight LTCs. Moreover, mini-outbreaks were quickly resolved in all six LTCs. Locally validated immunochromatographic SARS-CoV-2 antigen testing can be used to contain the spread of the virus in LTCs. Antigen tests also deliver accurate information very quickly if used early with a low threshold. The NADAL COVID-19 antigen test proved to be a good screening tool to detect SARS-COV-2 in LTCs. The COVID-19 pandemic continues to pose a major threat to public health in European countries. On 28 October 2020, European Commission Communication stated that “robust testing strategies and sufficient testing capacities are essential aspects of preparedness and response to COVID-19” . In Slovhttps://www.medcalc.org (accessed on 12 May 2021); 2019). We calculated diagnostic accuracy of the test and 95% confidence interval (95% CI).Eight LTCs started using NADAL COVID-19  on 15 October 2020 with the purpose to prevent the spread of the virus among LTC residents. The eight LTCs included in the survey take care for a total of 1237 residents, with the mean number of beds amounting to 155. The biggest LTC included in the survey has 205 beds. Elderly age group included in the study was 65–95 years. Under the supervision of a clinical microbiologist, the LTC staff validated the test against the Cobas 6800 RT-PCR test  as suggested by authorities [The study protocol was approved by the Institutional Review Board of General Hospital Jesenice (Nr. 2020-02) for all LTCs. All study participants for local clinical validation were enrolled by dedicated health care personnel and provided an oral informed consent.n = 55) and residents (n = 53) were tested more than once in the observed period. The administered antigen tests were positive for 3.75% (9) employees and 6.97% (26) residents. RT-PCR testing detected another 2.92% (7) infected employees and 1.61% (6) residents proved to be false positive in the antigen test. Only 0.42% (1) of the employees who were tested two times was tested positive on antigen tests and another one on an RT-PCR test. 11.61% (6) residents tested two times were positive on antigen tests and another 2.14% (8) tested positive on RT-PCR tests. None of the employees or residents who were tested more than two times were positive on the antigen test or on the RT-PCR test.After the validation of the test, LTCs performed the test on all employees who reported feeling ill before they were allowed to start their work. The elderly were tested if they had fever and at least one other sign of COVID-19. A subject was classified as presymptomatic if no symptoms were present for 14 days before a positive SARS-CoV-2 test, but typical or atypical symptoms developed during follow-up; when no symptoms developed during follow-up, the subject was classified as asymptomatic. If an elderly or employee tested positive by antigen test, a sample taken from contralateral nares was sent to RT-PCR testing. In addition, all other residents of the same LTC tract were tested. Other staff who worked in the same shift as the infected worker were also tested for SARS-CoV-2 using the NADAL COVID-19 antigen test. An additional 613 antigen tests were performed by the end of November in seven facilities. Some of the test subjects were also tested by RT-PCR. The antigen test proved to be sufficiently accurate to be used in specific settings of LTCs as POCT with very good diagnostic accuracy employees and residents . Data are presented in Through the use of antigen tests, six of the eight monitored LTCs prevented major uncontrolled outbreaks of COVID-19. The 1st LTC that was unable to control the outbreak has 154 residents and is located in the north-central part of Slovenia . The highest-performing test recorded sensitivity of 89% . One stuThere have only been a few studies conducted in LTCs or similar institutions. In colleges and campuses, SARS COV 2 antigen assay did not to prove to be the tool to prevent outbreaks . In the To prevent a rapid and widespread transmission of SARS-CoV-2 in nursing facilities where even more than half of residents who has tested positive were asymptomatic at the time of testing and most likely contributed to the transmission , a more Rapid and accurate results are extremely important in LTCs, considering that nursing homes were possibly the most vulnerable institutions already before the COVID-19 pandemic and the elderly with pre-existing conditions had a significantly higher risk of severe disease and death . Our stuOn the other hand, our report has certain limitations. As not all residents were swabbed for RT-PCR testing, there is a possibility that some cases of asymptomatic infections might have been missed. The validation study in LTCs began in highly prevalent SARS-CoV-2 conditions, resulting in very good sensitivity of the test that may not apply to low-prevalence situations. We were unable to pinpoint the exact index cases in all LTCs.Our results show that validated SARS-CoV-2 antigen test fulfil the criteria as defined by World Health Organization with 80% sensitivity and 97% specificity in different LTCs . We had


Health care personnel (HCP) are at high risk for exposure to the SARS-CoV-2 virus. While personal protective equipment (PPE) may mitigate this risk, prospective data collection on its use and other risk factors for seroconversion in this population is needed.The primary objectives of this study are to (1) determine the incidence of, and risk factors for, SARS-CoV-2 infection among HCP at a tertiary care medical center and (2) actively monitor PPE use, interactions between study participants via electronic sensors, secondary cases in households, and participant mental health and well-being.To achieve these objectives, we designed a prospective, observational study of SARS-CoV-2 infection among HCP and their household contacts at an academic tertiary care medical center in North Carolina, USA. Enrolled HCP completed frequent surveys on symptoms and work activities and provided serum and nasal samples for SARS-CoV-2 testing every 2 weeks. Additionally, interactions between participants and their movement within the clinical environment were captured with a smartphone app and Bluetooth sensors. Finally, a subset of participants’ households was randomly selected every 2 weeks for further investigation, and enrolled households provided serum and nasal samples via at-home collection kits.As of December 31, 2020, 211 HCP and 53 household participants have been enrolled. Recruitment and follow-up are ongoing and expected to continue through September 2021.Much remains to be learned regarding the risk of SARS-CoV-2 infection among HCP and their household contacts. Through the use of a multifaceted prospective study design and a well-characterized cohort, we will collect critical information regarding SARS-CoV-2 transmission risks in the health care setting and its linkage to the community.DERR1-10.2196/25410 As of October 2020, the global COVID-19 pandemic accounts for more than 43 million confirmed infections and 1.1 million deaths, along with unprecedented disruption to social networks and economic systems . The serInfected HCP may also contribute to disease transmission, both in the hospital setting and in the community. When infection results in overt clinical symptoms, identifying and isolating infected HCP is relatively straightforward. However, many SARS-CoV-2–infected individuals are asymptomatic or develop only mild symptoms -10. In tMost studies of SARS-CoV-2 seroprevalence among HCP have been cross-sectional or case series analyses . AlthougThe overarching goal of the study was to quantify and describe the risk of SARS-CoV-2 infection among frontline HCP, ancillary support staff, and their household contacts amidst the ongoing COVID-19 pandemic. To accomplish this goal, we designed a layered prospective cohort study of HCP and their household contacts. We enrolled frontline HCP, including physicians, nurses, and ancillary staff, providing and supporting emergency room, respiratory diagnostic testing, and inpatient care at a large, academic, tertiary care medical center. We collected survey data, venous blood samples, and a nasal swab for detection of SARS-CoV-2 every 2 weeks for 3 months and then monthly thereafter for a period of up to 6 months. We also tracked individuals’ interactions using Bluetooth sensors that were linked to a smartphone app for each participant and also attached to various locations within their workplace. Our central hypothesis was that preventive behaviors outside of work, interactions in the workplace, and use of protective equipment would predict the risk of infection in HCP and their household contacts.We conducted a prospective, observational study of SARS-CoV-2 among HCP and their household contacts during a global pandemic at a large, regional, southern US medical center. The setting was a tertiary care facility with over 900 beds. The SARS-CoV-2 response at the medical center involved the cohorting of suspected and infected patients on particular floors see  and locaBased on sample size calculations , we sought to enroll 300 HCP providing care and services in inpatient, ED, and testing center settings during the COVID-19 pandemic. Of note, HCP were not routinely screened for SARS-CoV-2 infection at this institution. Eligibility criteria for HCP included the following: (1) provided patient care or support services at the University of North Carolina Medical Center (UNCMC) or the Respiratory Diagnostic Center (RDC) during the COVID-19 pandemic, (2) planned to remain employed by the University of North Carolina (UNC) for the duration of the study, (3) willing and able to provide informed consent or assent, and (4) had access to stable internet, email, and a computer at home. The only exclusion criterion was an inability to provide informed consent. As described in detail below, HCP and ancillary staff were surveyed regarding potential occupational exposures and patient care activities. Venous blood, nasal swabs, and nasal epithelial lining fluid (NELF) were collected every 2 weeks. HCP participants who developed clinical symptoms at any point during the study and were not self-identified as SARS-CoV-2 positive were referred to Occupational Health for evaluation. Additionally, proximity contacts between individual HCP participants and between HCP participants and high-risk locations in the hospital were collected via a mobile app using Bluetooth technology.Finally, we enrolled a subset of the household members of HCP participants to assess transmission dynamics outside of the hospital environment. For household members to be considered eligible, they had to (1) cohabitate for an average of at least 40 hours per week with an HCP participant, (2) have the ability to use a collection device for serum collection on one’s own or with assistance from another household member, and (3) be willing and able to provide informed consent or assent or parental consent. Those younger than 18 months of age and those who were unable to provide informed consent, or parental consent if under 18 years of age, were excluded from the household study. This study was approved by the Institutional Review Board of the UNC at Chapel Hill (20-0942).To recruit HCP, study leaders met with administrative leadership for divisions within the Department of Medicine  and other departments within the School of Medicine , nursing leadership for hospital units, respiratory therapy administrators, and leadership for ancillary and support services  to present and discuss the study. Various additional approaches for recruitment were used as well, including (1) direct communication to personnel through email or face-to-face encounters; (2) presentation or discussion about the study at virtual or in-person staff meetings; (3) flyers, posters, or other public displays; and (4) small gifts on which the study logo was printed, such as miniature hand sanitizer bottles, pens, and stress balls. Interested individuals were referred to a study-specific website where they were able to learn more about the study, ask questions through a study-specific email address, and submit an online prescreening survey to communicate their interest to the study team. The study team then scheduled a time to discuss the study with participants by phone and complete an electronic consent form, a copy of which was emailed to the participant. HCP participants were able to opt out of electronic contact tracking and collection of NELF samples on the consent form but still participate in the other study procedures. Once enrolled, a unique participant identifier was generated for linkage of data sources. HCP recruitment and enrollment began in July 2020 and is ongoing as of January 2021.Due to logistical and financial constraints, we could not include all households of participating HCP in the study. Therefore, to recruit household members of HCP participants, we selected a random sample of high- and low-risk HCP participants for household investigation every 2 weeks. HCP were considered high risk if any of the following occurred:HCP self-reported contact with suspected or confirmed patient with SARS-CoV-2 infection without proper PPE, defined as N95 respirator, gown, gloves, and eye protection.HCP self-reported errors and/or malfunction of PPE during patient encounters.Positive SARS-CoV-2 rapid serology test result: either immunoglobulin (Ig) M or IgG.Suspected or confirmed SARS-CoV-2 infection.If none of the above criteria applied, the HCP was considered low risk. Once participants were stratified into high- and low-risk categories, a third-party biostatistician performed probability-based sampling to select 6 to 10 households for investigation (3 to 5 households per risk category). Study staff were masked to the assigned risk categories for the selected households. The HCP were approached to provide emails and ages for all household contacts. If the HCP participant agreed to the household investigation, the study team contacted their household members about study participation by phone. The study team reviewed the study documents, electronic consent form, and the process for at-home sample collection with the household member. If the household member agreed to participate, they signed the consent form electronically. Each household member was provided a handout about when to seek care for potential SARS-CoV-2 infection and when to contact the study staff by email. Household member recruitment began in July 2020 and is ongoing as of January 2021.The overview of the study design is shown in At baseline, HCP participants received an electronic questionnaire regarding demographics, occupational duties, current symptoms, known exposures to SARS-CoV-2-infected persons, and PPE usage. This initial questionnaire also gathered data about the participant’s household  and included basic mental health assessments for depression, anxiety, and posttraumatic stress disorder (PTSD).Once the first in-person study visit was completed (see Study Visits and Sample Collection section below), daily electronic surveys were sent to participants for the first 12 weeks of study participation via an automated email reminder. Questions included a clinical symptom assessment, with self-recorded temperature if symptomatic; hours worked at the medical center; number of contacts with patients with suspected or confirmed SARS-CoV-2; and occupational activities performed during interactions with patients.The participant received a longer electronic survey by email every 2 weeks containing questions concerning current symptoms, known exposures to SARS-CoV-2-infected individuals, PPE availability and usage since they completed the last 2-week questionnaire, and pandemic-related stress.Throughout the study, if a participant indicated symptoms consistent with SARS-CoV-2 infection, they were referred to the medical center’s Occupational Health Department for evaluation and testing. Additionally, if a participant indicated that they were having thoughts of self-harm more than half of the days in the last 2 weeks, they were sent an email referral to an institutional mental health hotline that was developed to address the mental health support of all HCP as well as other local and national mental health support resources.After completion of the baseline questionnaire, a research assistant met the participant at one of three designated sites in or near the medical center for the baseline study visit, during which the following study procedures took place:Venous blood was collected in an EDTA tube by trained phlebotomists for SARS-CoV-2 IgM/IgG rapid diagnostic testing and preparation of dried blood spots (DBS) for storage. Venous blood was also collected in two 8 mL cell separator tubes for peripheral blood mononuclear cell (PBMC) isolation and storage, using the BD Vacutainer Mononuclear Cell Preparation Tube (CPT), Sodium Citrate (BD Biosciences). Plasma was isolated from the cell preparation tubes for SARS-CoV-2 antibody testing by enzyme-linked immunosorbent assay (ELISA).We asked a subset of participating HCP  to have blood drawn for SARS-CoV-2 antibody testing by ELISA using the Tasso serum self-collection kit  in parallel with venous phlebotomy as part of a substudy. Tasso devices were used per the manufacturer’s instructions. Briefly, individuals washed their hands and prepped their skin by rubbing until warm and wiping with alcohol to sterilize. The device was then adhered to the skin for 5 minutes to collect the sample and removed.Participants self-collected a mid-turbinate nasal swab (MTNS) using the protocol described in previous studies ,16. We eParticipants self-collected NELF using absorbent strips inserted into the nose—if they opted into this part of the study—as described previously see  17]. Br. Br17]. Each individual was given a digital thermometer to track and report their temperature at home.Participants who opted into downloading an app to track their interactions in the workplace were given a Bluetooth Low Energy (BLE) beacon for contact tracking to attach to their hospital-issued ID badge or lanyard. They were also instructed on how to download and set up the Ethica (Ethica Data) smartphone app (see Network Data Collection section).Every 2 weeks for the first 12 weeks and then monthly for the remainder of the study, participants again presented to one of three designated sites for an in-person, follow-up study visit see . Venous The overview of the study design is shown in At the time of enrollment, each household member received a survey regarding demographics, relationship to the HCP participant, occupation, medical history, and any recent clinical symptoms, SARS-CoV-2 exposures, or past SARS-CoV-2 testing.Enrolled household members completed weekly questionnaires about possible symptoms of SARS-CoV-2 infection and any testing since the previous survey.At the end of their study participation, 21 days after their first sample collection, household members completed a final questionnaire asking about any changes in occupation since the baseline survey and any SARS-CoV-2 symptoms, exposures, and/or testing since the previous weekly survey.Throughout their participation in the study, if a household member reported fever and either cough or shortness of breath, they were referred to the testing center or their primary care provider’s office for testing.Samples were collected at baseline and at day 21. Within 3 days of enrollment, the study team mailed a kit for at-home baseline sample collection to each consented household member; the kit included the following:Tasso at-home serum collection kit for SARS-CoV-2 antibody testing by ELISA. The Tasso device was provided in a box labeled with the date and patient identifier; the box contained written instructions and a link to the website that demonstrates use of the collection device . Once coNasal swab and DNA/RNA Shield Collection Tube for MTNS collection for SARS-CoV-2 PCR testing. The nasal swab was provided with an instruction sheet and link to an online video with instructions for nasal swab specimen collection. After specimen collection, the participants placed the sealed tubes containing the swabs in sealable biohazard bags.Completed at-home collection kits were then packaged in a preaddressed, preposted box and mailed back to the laboratory to minimize face-to-face contact between the study team and household members. The same at-home sample collection process was then repeated 21 days after baseline sample collection.HCP participant–participant and HCP participant–environment interactions were collected electronically via BLE with the Ethica (Ethica Data) smartphone app see . We follBLE beacons are devices used to broadcast a set of identifiers at a predetermined rate. For our app, BLE beacons were programmed with a unique combination of UUIDs, major values, and minor values as assigned by the Ethica system. While other devices can see the broadcast beacon identifiers, the beacon identifiers are not linked to the other participants’ information or data sources, aside from a linkage within Research Electronic Data Capture (REDCap), the electronic data management system used for the study . BLE beaDuring the consent process, HCP had the option to opt into the proximity contact data collection. HCP who consented to use the Ethica app were given instructions on installing the app on their smartphone. Environmental BLE beacons were placed at locations within the ED, the RDC, the Medical Intensive Care Unit (MICU), pediatric intensive care units, elevators, and floor COVID-19 units for adults and children see . BLE proTo document trends in the use of PPE, members of the research team were stationed in the areas in which care for patients with suspected or confirmed SARS-CoV-2 infection most often took place. At least one team member observed each of the following areas once weekly for 2 to 3 hours each time: the ED bay where patients suspected of having SARS-CoV-2 infection were cohorted, the inpatient ward for SARS-CoV-2-infected patients, and the MICU. The observations were collected on an electronic form, including unit-level PPE use and availability and individual HCP-patient interactions; specifically, appropriateness of hand hygiene and PPE use and procedures performed by the provider. This observational data collection will supplement the self-reported daily PPE usage information by the HCP.The collection, processing, and storage of samples followed national and international guidelines, and all processes were approved by Environmental Health Services at UNC . Please The rapid diagnostic test (RDT) followed the manufacturer's guidelines (Elabscience) . BrieflyApproximately 200 μL of blood was used to make four DBS per patient time point. Blood was spotted on appropriately labeled Whatman 904 cards. Each card was dried for 15 minutes, or until completely dried, before packaging in individual Ziploc bags with desiccant. Blood spots were stored at –80 °C for future research.Using both the plasma collected from HCP participants during their in-person study visits and the household participants’ self-collected serum samples, we performed an ELISA using the recombinant spike protein antigen to detect total SARS-CoV-2 Ig in plasma . The cut°C for future research.Cell preparation tubes were processed and PBMCs isolated as previously described and as detailed in MTNS were used for SARS-CoV-2 PCR testing. The DNA/RNA Shield medium in which the swabs were collected inactivates all viral particles. RNA was extracted from 200 μL of DNA/RNA Shield medium using a Qiagen HT system. Samples were screened for SARS-CoV-2 infection using the Thermo Fisher Scientific COVID-19 multiplex real-time PCR assay including the MS2 phage spike during extraction. All samples that tested positive by this initial test underwent confirmation testing with the CDC assay and viral copies were quantified . PCRs weAbsorbent strips for capturing fluid from the nasal epithelium were frozen at –80 °C for storage and batched for processing. One strip was utilized for protein analysis via multiplex ELISA for cytokines and chemokines, and the second strip was utilized for viral PCR testing. Samples were inactivated prior to analysis via approved protocols, which included heat and chemical treatment. Processing for protein analysis and PCR analysis occurred as described previously . The remAll data were stored in a Health Insurance Portability and Accountability Act–compliant database using REDCap .Given the rapid emergence and evolving situation regarding the COVID-19 pandemic, limited data were available at the time of study design on which to base sample size estimates. Preliminary data from northern Italy suggested an infection rate approaching 20% or higher ,29, but Our primary exposure of interest was employment in a department or unit involved in frontline health care of confirmed or suspected SARS-CoV-2-infected patients. Results from this group will be compared to a group of HCP and ancillary staff employed in a department or unit that is not involved in care of patients infected with SARS-CoV-2. Secondary variables of interest also included other occupational factors  and preventative behaviors outside of work .Our primary outcome of interest was the incidence of SARS-CoV-2 infection defined as either development of SARS-CoV-2-specific antibodies as determined by ELISA  or clinical infection with SARS-CoV-2 confirmed by PCR testing. Secondary outcomes of interest included the following: (1) demographic, clinical, and occupational factors associated with SARS-CoV-2 infection; (2) proportion of confirmed infections that are subclinical and/or asymptomatic; (3) risk of secondary transmission and serial interval within household contacts; (4) analysis of the Bluetooth contact networks to assess the efficacy of community mitigation policies; and (5) agreement between serological testing results obtained from venous blood collection, DBS, and Tasso device. Exploratory outcomes included the characterization of the immune response in the nasal epithelium at various points during SARS-CoV-2 infection and genotypic analyses of the SARS-CoV-2 viral isolates.To account for common causes of department employment and SARS-CoV-2 infection, information on demographics , occupational factors , behaviors outside of work , and mental health  were collected. Since risk of infection is affected by the characteristics and behaviors of others, we also collected information on locations worked  and proximity contacts as measured through the Bluetooth beacons.Demographic, clinical , and occupational characteristics of the HCP and household member cohorts will be described using standard summary statistics. The risk ratio and risk difference of SARS-CoV-2 infection among HCP participants working in COVID-19 areas versus non-COVID-19 areas, while accounting for identified confounders, will be estimated using Bayesian additive regression trees . We willWe will determine the test performance  of the SARS-CoV-2 IgM/IgG RDT using the ELISA antibody test as the reference assay. To validate serological results obtained using the Tasso at-home collection device, we will also assess for concordance between ELISA antibody testing results from samples collected by the Tasso self-collection kit and venous phlebotomy, which is considered the standard specimen-collection procedure, through calculation of the Cohen κ coefficient.NELF samples will be analyzed using multiplex ELISAs to quantify (1) the expression of cytokines and chemokines important in the upper respiratory tract antiviral immune response and (2) quantitative SARS-CoV-2 viral load. In conjunction with NELF collected from cohorts of patients with SARS-CoV-2 infection from other ongoing research studies, we will evaluate the association of the measured inflammatory mediators and COVID-19 disease severity as defined by the World Health Organization . We willThe information collected from the Bluetooth beacons will be summarized and visualized using network analysis tools, providing insight into the patterns of movement of study participants within the hospital. Because BLE signals can travel through objects , proximity contacts will be filtered by RSSI values determined by internal assessments of the beacons when used in conjunction with the Ethica app. Furthermore, individual-level likelihood-based methods will be used to study the dynamics of epidemic spread as it relates to the network of individual contacts and potential explanatory variables .Recruitment for this study is currently ongoing and has occurred in phases. When the study began, the types of HCP interacting with patients known to be positive for SARS-CoV-2 were limited per hospital policy, so the groups that were providing direct in-person care were targeted for recruitment first . As the pandemic continued, hospital policies shifted, and ancillary staff  were again entering patient rooms, so our recruitment efforts also shifted to include these groups. Specifically, we used the same recruitment strategies described above but targeted them to the support staff employee groups. In addition, we performed additional outreach to the environmental services group, attending shift huddles and rounding with management multiple times in person.As of December 31, 2020, we have enrolled a total of 211 HCP participants. Of these, 65 (30.8%) are male and 146 (69.2%) are female. We have also enrolled 53 household participants from 37 households. Of those 53 household participants, 16 (30%) are under 18 years old. Many types of HCP have enrolled in the study see , with thA total of 86.3% (182/211) of participants have opted into the Bluetooth contact tracking, while 90.0% (190/211) of participants have opted into the NELF sample collection substudy. Thus far, 45 participants have withdrawn prior to 12 weeks of participation due to schedule constraints.In this article, we describe the protocol for a multifaceted, longitudinal, observational cohort study to obtain crucial information about the risk of SARS-CoV-2 infection among HCP and their household contacts. There are several novel aspects to the study design that will maximize its impact. First, the cohort of HCP will be very well-characterized because of (1) frequent sampling, especially during the first 12 weeks, to assess for infection and/or seroconversion and (2) the depth and breadth of information collected through electronic questionnaires regarding clinical symptoms, potential exposures to SARS-CoV-2, occupational activities, PPE access and use, perceptions of the epidemic, and mental health. As we intentionally designed the study to include many different types of HCP to maximize the generalizability of our results, we have applied careful measurement where we can to identify occupational roles and activities so these can be accounted for in our analyses. Second, the use of Bluetooth beacon contact tracking is a robust methodology that will complement the self-reported exposure data. Finally, our study is unique in that it is enrolling both HCP and a randomly selected subset of linked households.There are a few potential limitations to our study. First, this study design employs frequent in-person study visits and electronic contact throughout the study period. We designed the study this way intentionally, seeking to obtain highly granular and detailed information about risks and exposures among our study participants. There is a chance that this level of participation may limit our ability to reach our recruitment goal of 300 individuals. To offset this burden, after the first 12 weeks of the study, participants transition to having only monthly study visits and one survey every 2 weeks. Second, it is possible that the people who chose to enroll in this type of longitudinal study may be more attuned to the COVID-19 pandemic and, therefore, more focused on preventative measures. This could induce selection bias. We plan to compare characteristics of our study population to those that are available for our target population—all HCP at UNCMC—and consider weighting, if appropriate, based on that evaluation.Through this study, we will generate important data about the incidence of SARS-CoV-2 infection among frontline HCP, their workplace contact network, transmission to their household members, and trends in incidence over time. We will also evaluate the accuracy and feasibility of using a minimally invasive, point-of-care rapid test to assess for seroconversion. Together, this information will be invaluable in determining the effectiveness of active surveillance programs to reduce nosocomial transmission and the need for additional nonpharmaceutical interventions to protect HCP and their families.


Objective: To explore whether the pretreatment dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) and radiomics signatures were associated with pathologic complete response (pCR) to neoadjuvant therapy (NAT) in breast cancer. Method: A retrospective review of 70 patients with breast invasive carcinomas proved by biopsy between June 2017 and October 2020 . Within the pre-contrast and five post-contrast dynamic series, a total of 1037 quantitative imaging features were extracted from in each phase. Additionally, the Δfeatures (the difference between the features before and after the comparison) were used for subsequent analysis. The least absolute shrinkage and selection operator (LASSO) regression method was used to select features related to pCR, and then use these features to train multiple machine learning classifiers to predict the probability of pCR for a given patient. The area under the curve (AUC), accuracy, sensitivity, and specificity were calculated to assess the predictive performances of the radiomics model for each of the five phases of time points. Result: Among the five phases, each individual phase performed with AUCs ranging from 0.845 to 0.919 in predicting pCR. The best single phases performance was given by the 3rd phase . 5 of the features have significant differences between pCR and non-pCR groups in each phase, most features reach their maximum or minimum in the 2nd or 3rd phase. Conclusion: The radiomic features extracted from each phase of pre-treatment DCE-MRI possess discriminatory power to predict tumor response. Neoadjuvant therapy (NAT) has been widely used in the treatment of local late breast cancer and has become an important part of comprehensive treatment of breast cancer ,2. It caDynamic contrast enhancement magnetic resonance imaging (DCE-MRI) is increasingly being used to evaluate the NAC response because of its high sensitivity and accuracy ,11. It nRadiomics is a new emerging non-invasive method that extracts high-dimensional features of image to reflect the heterogeneity of the entire tumor ,16. DiffIn this study, we extracted the radiomics features from all phases of post enhancement images in DCE-MRI, and aimed to evaluate the predictive performance of different combinations of feature selection in different time points.We conducted a retrospective review of 70 patients with breast-invasive carcinomas proven by biopsy between June 2017 and October 2020. All the patients met the following inclusion criteria: pathologically confirmed invasive carcinoma; underwent breast MRI before NAT; received at least 6 cycles of NAT; surgical resection was performed after neoadjuvant chemotherapy, and the final pathological results were obtained. Exclusion criteria: images with poor quality or severe artifacts; distant metastasis during NAT. Finally, 70 patients were included in the data analysis. All cases were female, aged 28–69 years, with an average age of 47.11 ± 9.59 years.The clinical and histological data including age, menstrual status, histological grade, the expression status of estrogen receptor (ER), progestogen receptor (PR), HER-2 and Ki-67 were collected.All the examinations were performed in SIEMENS Verio 3.0T MR imaging system with the patient in a prone position using a 4-channel breast surface coil. The MR imaging examination consisted of the following protocol: T2 turbo inversion recovery magnitude ; axial 3D FLASH T1 ; T2-weighted turbo spin-echo . DCE imaging was performed with one pre-contrast and five post-contrast dynamic series using axial 3D FLASH T1 with fat suppression . A 0.1-mmol/kg bolus of Gadobenate  was injected using high pressure injector, then followed by a 15 mL saline flush.n = 26) and non-pCR group (n = 44). pCR was defined as the absence of residual invasive cancer with or without ductal carcinoma in situ in the breast tissue and the absence of any tumor deposits in the sampled axillary nodes.According to Miller&Payne system patients were divided into pCR group  on axial fat suppression T1-weighted images obtained in a 6-image series, including pre-contrast image and 5 phases after contrast material injection. The region of interest was manually drawn on each slice along the contour of the tumor on the first postcontrast of DCE images to get the 3D segmentation of the whole tumor. The region of interest (ROI) should cover all the tumor, including the areas of necrosis and hemorrhage, but avoid edema, blood vessels, and the normal fibroglandular tissue. Then, the 3D segmented contouring based on the 1st postcontrast phase images were propagated to pre-contrast and other four post-contrast phases of DCE images. Finally, all ROIs were reviewed by another breast radiologist (with 15 years of experience).Segmentation was performed using ITK-snap  was used to calculate the MR image features of 6 phases (pre-contrast and five post-contrast phases), with a total of 1037 quantitative imaging features in each phase. Additionally, the bin width was set to 5 due to the characteristics of MR images according to the image biomarker standardization initiative (IBSI). The features can be classified into four groups, including shape- and size-based features, first-order statistical features, texture features and wavelet features.The shape-based features were independent from the gray level intensity distribution in the image and were measured using the shape descriptors of three-dimensional size and shape of the ROI. First-order statistical features were used to describe the distribution of voxel intensities. Texture features used a matrix to represent the spatial heterogeneity of the intensity level. To further investigate the intra-ROI heterogeneity, wavelet filters were applied to the original images to convert original images to versions focused on information at different scales. wavelet decompositions with all possible combinations of high (H)- or low (L)-pass filter in each of the three dimensions  were applied. The delta-features were calculated to represent the feature changes of each post-contrast phase and to subsequent modeling analysis . We use As the reproducibility of radiomic features may be influenced by the manual delineation of ROI, the 30 patients including 150 ROIs were randomly chosen to take the secondly segmentation. Additionally, we calculated the interclass and intraclass correlation coefficients (ICC) of each feature for inter-observers and intra-observers. Any features with ICC < 0.8 was considered unreliable and discarded. The z-score method was used to standardize the features to decrease the influence of dimension. To further eliminate redundant features, the Max-Relevance and Min-Redundancy (mRMR) was performed. The remaining radiomic features may still have a larger size than the sample size, which may bring the risk of overfitting. Thus, we used the least absolute shrinkage and selection operator (LASSO) to select the most predictive features, and the Akaike information criterion (AIC) was applied in the step method. Finally, logistic regression was used to construct the model which was built as the weighted sum of the selected radiomic features.Models were evaluated by the ten-fold cross-validation method, which has been widely used as a reliable approach to evaluate a model’s true generalization performance. The diagnostic performance of the models was quantified by the area under the receiver operating characteristics (ROC) curve (AUC), and the 95%CI confidence interval (CI) of AUC were calculated. The optimal cutoff value was selected as the point when the sensitivity plus specificity was maximal. The sensitivity, specificity and prediction accuracy (ACC) of each model were also calculated in the cohort.https://www.R-project.org; accessed on 16 March 2021). p < 0.05 was considered statistically significant. The workflow of radiomic research is shown in Normal distribution data are presented as mean ± standard deviation, whereas non-normally distributed data are presented as median (25–75th percentiles). The two-sample t-test or Mann–Whitney U test was used to evaluate differences in the response. A repeated measures analysis of variance was applied to assess the differences in the selected parameters at different time points in the same group, followed by the Bonferroni correlation for post hoc pairwise comparisons. All statistical analyses were performed with R software . The number of patients with estrogen receptor (ER) positive/progesterone receptor (PR) positive in pCR group were significantly less than that in non-pCR group, and there were statistically significant differences between these two groups (p < 0.05). In pCR group, the largest proportion is triple negative type (34.6%), while in non-pCR group, the largest proportion is type Luminal B (63.7%). The molecular subtype distribution shows a significant difference between the two groups (p = 0.016).The clinical characteristics of patients were shown in A total of 1037 quantitative imaging Δfeatures in each contrast phase were included in the intra-class correlation. Features with ICC < 0.8 were excluded; 485 features were selected for further analysis. Before feature selection, the abnormal or missing values were replaced by the median, and features standardization was applied. Next, the mRMR and LASSO were used to select the most optimal features. After the redundant and irrelevant features were removed by mRMR, 50 features from each ROI were retained. Then, the LASSO was applied to decrease the feature redundancy with the Akaike information criteria. After the number of features was determined, the most predictive subset of features was chosen and the corresponding coefficients were calculated.p < 0.05).All the Δfeatures extracted from each phase were listed The ROC analysis was used to calculate the prediction performance of different combinations of feature selection for each of the five time point phases in radiomics. AUC under ROCs for each phase were shown in Of all 37 features in the 1st–5th phases, there was overlap in the features selection in different phases, of which eight features were selected repeatedly in more than two phases. All these features were texture features from GLSZM GLDM GLCM and GLRLM, and half of the features underwent wavelet transformation.Further analysis of these eight features, This study investigated the ability of machine learning model based on pretreatment multi-phase DCE-MRI to predict tumor treatment response of NAT. The results indicated that the radiomics features of the images in each post-enhancement phases have good performance for predicting pCR.Most of the previous research on breast cancer radiomics only focused on the features extracted from one single phase after enhancement ,26. The Additionally, the eight features repeatedly selected in multiple phases were all texture features. ZoneEntropy, GrayLevelNonUniformity and Small DependenceEmphasis weretexture features quantifying uncertainty or randomness of the image value, and may associated with tumor heterogeneity . In thisThere are still deficiencies in this study. This study is based on a limited number of patients. A larger sample size is needed to verify the validity and practicability of these classifiers. Additionally, we only analyzed the T1-weighted image after contrast material injection, T2-weighted image, DWI and other multiple sequences need to be analyzed in the later stage of the study to construct a multimodal MR radiomics model.The delta radiomic features extract from pre-treatment DCE-MRI could be the predictor of NAT response, and the radiomics model constructed in our study can effectively predict pCR.