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Background The closure of communities, including schools, has been adopted to control the coronavirus disease 2019 (COVID-19) epidemic in most countries. Operating schools safely during the pandemic requires a balance between health risks and the need for in-person learning. We use compartmental models to explore school reopening scenarios. Methods Using demographic and epidemiological data between July 31 and November 23, 2020 from the city of Toronto, we developed a Susceptible-Exposed-Asymptomatic-Infectious-Recovered-Hospitalized-Isolated model. Our model with age, household, and community transmission allow us to study the impact of schools open in September 2020. The model mimics the transmission in households, the community, and schools, accounting for differences in infectiousness between adults and children and youth and adults’ working status. We assessed the extent to which school opening may have contributed to COVID-19 resurgence in the fall and simulated scenarios for the safe reopening of schools up to May 31, 2021. We further considered the impact of the introduction of the new variant of concern. Findings Though a slight increase in infections among adults (2.8%) and children (5.4%) is anticipated by the end of the year, safe school opening is possible with stringent nonpharmaceutical interventions (NPIs) decreasing the risk of transmission in the community and the household. We found that while school reopening was not the key driver in virus resurgence, but rather it was community spread that determined the outbreak trajectory, brief school closures did reduce infections when transmission risk within the home was low. When considered possible cross-infection amongst households, communities, and schools, we found that home transmission was crucial for mitigating the epidemic and safely operating schools. Simulating the introduction of a new strain with higher infectiousness, we observed substantial increases in infections, even when both schools and communities are closed. Interpretation Schools can open safely under strict maintenance of strict public health measures in the community. The gradual opening of schools and communities can only be achieved by maintaining NPIs and mitigating household transmission risk to avoid the broader escape of infections acquired in schools into the community via households. If the new COVID-19 strain is more infectious for children, public spaces, including schools, should be closed, and additional NPIs, including the use of masks, should be extended to toddlers. Funding This research was supported by Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council of Canada, and York University Research Chair program. Research in context Evidence before this study The design of a gradual school reopening strategy remains at the heart of decision-making on reopening after shut-downs to control the epidemic. Although available studies have assessed the risk of school reopening by modelling the transmission across schools and communities, it remains unclear whether the risk is due to increased transmission in adults or children and youth.We used GoogleScholar and PubMed searches to identify previous published works. We used te following terms: “school closure”, “covid 19 school closure”, “reopening schools”, “reopening screening school”, “school household second wave model”. The search of the studies ended in January 2021. Papers in other languages than English and letters were excluded from the search. Two modelling studies examined the effects of screening and delayed school reopening, two other agent-based modelling studies explored the epidemic spread across different age groups. Added-value of this study We find that the resurgence of COVID-19 in Toronto in fall 2020 mainly resulted from the increase of contact rate among adults in the community, and that the degree of in-person attendance had the most significant impact on transmission in schools. To our knowledge, our work is the first to investigate the resurgence in infections following school reopening and the impact of risk mitigation measures in schools operation during the pandemic. Our novel and comprehensive model considers the age and household structure, but also considers three different settings, school, household and community. We further examined the effects of self-screening procedures, class size, and schooling days on transmission, which enabled us to compare scenarios of school reopening separately for both adults and children and youth, and model the cross-infection between them to avoid potential underestimation. We found that after schools opened, reducing household transmission was crucial for mitigating the epidemic since it can reduce cross-infection amongst households, communities and schools. Lastly, given the recent report of SARS-CoV-2 variant (VOC202012/01), we investigated the impact of the new variant that may be more infectious in children and youth. Implications of all the available evidence Our analysis can inform policymakers of planning the safe reopening of schools during COVID-19. We suggest that integrating strict NPIs and school control measures are crucial for safe reopening. When schools are open, reducing transmission risk at home and community is paramount in curbing the spread of COVID-19. Lastly, if children are more susceptible to the new COVID-19 VOC, both schools and community must be closed, the time children spend in essential services locations minimized, and NPI’s for those aged less than three years enforced.

Background: In many parts of the world, restrictive non-pharmaceutical interventions (NPI) that aim to reduce contact rates, including stay-at-home orders, limitations on gatherings, and closure of public places, are being lifted, with the possibility that the epidemic resurges if alternative measures are not strong enough. Here we aim to capture the combination of use of NPI’s and reopening measures which will prevent an infection rebound. Methods: We employ an SEAIR model with household structure able to capture the stay-at-home policy (SAHP). To reflect the changes in the SAHP over the course of the epidemic, we vary the SAHP compliance rate, assuming that the time to compliance of all the people requested to stay-at-home follows a Gamma distribution. Using confirmed case data for the City of Toronto, we evaluate basic and instantaneous reproduction numbers and simulate how the average household size, the stay-at-home rate, the efficiency and duration of SAHP implementation, affect the outbreak trajectory. Findings: The estimated basic reproduction number R_0 was 2.36 (95% CI: 2.28, 2.45) in Toronto. After the implementation of the SAHP, the contact rate outside the household fell by 39%. When people properly respect the SAHP, the outbreak can be quickly controlled, but extending its duration beyond two months (65 days) had little effect. Our findings also suggest that to avoid a large rebound of the epidemic, the average number of contacts per person per day should be kept below nine. This study suggests that fully reopening schools, offices, and other activities, is possible if the use of other NPIs is strictly adhered to. Interpretation: Our model confirmed that the SAHP implemented in Toronto had a great impact in controlling the spread of COVID-19. Given the lifting of restrictive NPIs, we estimated the thresholds values of maximum number of contacts, probability of transmission and testing needed to ensure that the reopening will be safe, i.e. maintaining an Rt

Purpose To describe the clinical presentation and outcomes of Acanthamoeba keratitis (AK) in rigid gas permeable (RGP) contact lens wearers and to identify modifiable risk factors. Design Case-control investigation. Participants Patients were RGP contact lens–wearing United States residents with a diagnosis of AK from 2005 through 2011. Controls were RGP contact lens wearers with no history of AK who were at least 12 years of age. Methods Patients were identified during 2 multistate AK outbreak investigations. Controls from the first investigation in 2007 were identified using a reverse address directory. In the second investigation, controls were recruited from participating ophthalmology and optometry practices. Patients and controls were interviewed by phone using a standardized questionnaire. Odds ratios (ORs) and Fisher exact P values were calculated to assess risk factors associated with infection. Main Outcome Measures Acanthamoeba keratitis, a rare eye disease primarily affecting contact lens wearers, is caused by free-living amebae, Acanthamoeba species. Results We identified 37 patients in the 2 investigations, 10 (27%) from the 2007 investigation and 27 (73%) from 2011. There were 17 healthy controls, 9 (53%) from 2007 and 8 (47%) from 2011. Among patients, 9 (24%) wore RGP lenses for orthokeratology or therapeutic indication; no controls wore RGP lenses for these indications. Significant risk factors for AK were wearing lenses for orthokeratology (OR, undefined; P = 0.02), sleeping while wearing lenses (OR, 8.00; P = 0.04), storing lenses in tap water (OR, 16.00; P = 0.001), and topping off contact lens solution in the case (OR, 4.80; P = 0.01). After stratifying by use of RGP lenses for orthokeratology, storing lenses in tap water and topping off remained significant exposures. Conclusions Nearly one quarter of patients were orthokeratology wearers. Using tap water to store RGP lenses and topping off solution in the lens case were modifiable risk behaviors identified in RGP wearers who wore lenses for both orthokeratology and nonorthokeratology indications. Rigid gas permeable wearers should avoid exposing their lenses to tap water and should empty their cases and use fresh lens solution each time they take out their lenses.

The potato (Solanum tuberosum) disease resistance protein Rx has a modular arrangement that contains coiled-coil (CC), nucleotide-binding (NB), and leucine-rich repeat (LRR) domains and mediates resistance to potato virus X. The Rx N-terminal CC domain undergoes an intramolecular interaction with the Rx NB-LRR region and an intermolecular interaction with the Rx cofactor RanGAP2 (Ran GTPase-activating protein 2). Here, we report the crystal structure of the Rx CC domain in complex with the Trp-Pro-Pro (WPP) domain of RanGAP2. The structure reveals that the Rx CC domain forms a heterodimer with RanGAP2, in striking contrast to the homodimeric structure of the CC domain of the barley disease resistance protein MLA10. Structure-based mutagenesis identified residues from both the Rx CC domain and the RanGAP2 WPP domain that are crucial for their interaction and function in vitro and in vivo. Our results reveal the molecular mechanism underlying the interaction of Rx with RanGAP2 and identify the distinct surfaces of the Rx CC domain that are involved in intramolecular and intermolecular interactions.

Background Newborn screening programs store—under varying conditions—residual dried blood spots (DBS). Residual DBS were used to investigate the contribution of congenital infection with Toxoplasma gondii to the etiology of hydrocephalus and as a key step, we assessed the effect of storage conditions on the stability of newborn screening biomarkers. Methods Infants with hydrocephalus (410 cases) were identified using population-based birth defects surveillance systems in California, North Carolina, and Texas. Infants without birth defects (448 controls) were randomly selected from the same geographic areas and time periods. California stores DBS with controlled temperature, while North Carolina and Texas store DBS under ambient conditions. After removal of personal identifiers, DBS were tested for Toxo-specific immunoglobulin-M (Toxo-IgM). Because of poor elution of DBS stored in ambient conditions, additional biomarkers were tested on a specimen subset. Results Among 858 DBS tested, Toxo-IgM was found in 3 cases and no controls from California ( N = 515) and in no specimens from North Carolina or Texas ( N = 343). Among the 98 specimens tested for selected biomarkers, statistically significant differences were found for California vs. combined North Carolina and Texas DBS (thyroid stimulating hormone, phenylalanine, methionine, leucine and citrulline p p Conclusions Storage conditions for residual DBS had an effect on the ability to extract, recover, and accurately measure Toxo-IgM and other biomarkers from the filter paper matrix.

Background Obsessive-Compulsive Disorder (OCD) is a common, disabling psychiatric disorder characterized by intrusive thoughts, images, or impulses that typically cause anxiety or distress (obsessions), and by repetitive mental acts or behaviors that one feels compelled to do (compulsions). Initial Genome-Wide Association Studies (GWAS) for OCD were underpowered to identify individual risk variants but clearly indicated that OCD is a heritable complex genetic trait and that increased sample size will yield significant loci. The use of existing Electronic Medical Records (EMR) in the US and other countries represents another rapid and cost-efficient strategy to increase ascertainment for OCD genomic studies. Methods BioVU is a repository of over 250,000 DNA samples extracted from discarded blood collected during routine clinical testing at Vanderbilt University Medical Center. The DNA samples obtained are linked to a de-identified Electronic Medical Record (EMR) datamart called the Synthetic Derivative containing clinical information extracted from over 2.2 million individuals in a searchable form covering the past 20 years. We thus undertook the task of building a diagnostic algorithm for OCD which could be applied to the EMR. To do this, we utilized ICD 9 and 10 codes (300.3 and F42.⁎) along with Natural Language Processing (NLP) to detect context-aware diagnostic keywords (e.g., Obsessive-compulsive, etc.), treatment keywords (e.g., cognitive-behavioral, etc.), and medications (e.g., fluoxetine, etc.) commonly prescribed for the treatment of OCD. Contextual information from 50 cases identified by the algorithm was then abstracted by trained non-expert reviewers and abstracted charts were reviewed by two domain experts to determine the Positive Predictive Value (PPV) of the algorithm. Results Our algorithm identified 7,547 OCD cases in the EMR and PPV was high (> 92%) across the two reviewers with high interrater reliability when all algorithm elements including ICD codes, diagnostic keywords, and treatment keywords were present in case charts. We then analyzed the PPV amongst the different ways in which the cases met criteria. Of these 7,547 potential cases, 1,528 have DNA available within the BioVU biobank. We are in the process of genotyping all of these OCD cases, along with matched controls, on the Illumina MEGA array, in preparation for GWAS. Results will be meta-analyzed with those from the PGC TS/OCD Working Group. Discussion We have designed and validated a phenotype algorithm for the ascertainment of OCD cases from electronic medical records. This algorithm can be deployed in any EMR and we will make it freely available in a forthcoming publication.