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Aims: Children and adolescents were affected in various ways by the measures due to COVID-19 pandemic. The aims of this study were to investigate and compare the effects on mental health across age, to identify latent class trajectories of emotional and behavioural problems over 12-months and to examine the association of classes of trajectories with baseline demographic and clinical predictors. Method(s): Children (n = 1854) and adolescents (n = 1243) from the general population were assessed baseline, at 6-, 9-, and 12-month follow-up. They were eligible if they were residents in Austria, Germany, or Switzerland, were parents/caregivers of a child aged between 7 and 10 years or adolescents >=11 years, had sufficient German language skills and provided informed consent. Results and Conclusion(s): Significant age-effects were found regarding type and frequency of problems. While children had the largest increase in aggressive behaviours, adolescents reported the largest increase in emotional problems. Sociodemographic variables, exposure to and appraisal of COVID-19, psychotherapy before COVID-19 and parental mental health significantly predicted change in problemscores (F >= 3.69, p <= .001). Using growth mixture modelling, a oneclass solution was detected for the trajectory of aggressive behaviours and a two- and three-class solution for withdrawn/depression and anxiety/depression. A substantial proportion of children and adolescents experienced age-related mental health problems during the different stages of the COVID-19 pandemic. These results suggest that psychological problems of specific sub-groups should be monitored over the longer-term and interventions to improve communication, emotion regulation, and appraisal style should be offered to risk groups.
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Objectives: We estimated the cost-effectiveness of non-pharmaceutical interventions (NPI), vaccines, and the combination of NPI and vaccines in managing the COVID pandemic. Method(s): A dynamic transmission model was constructed to simulate the incidence of COVID infections and deaths among community-dwelling Singapore residents. Using this model, we compared the cost and outcomes of NPI (border control measures, safe distancing and mask wearing) versus no NPI in an unvaccinated and a vaccinated population. The analysis was conducted from the societal perspective over a one year time horizon, with data based on the COVID situation in Singapore during Jan 2021 to Dec 2021. Costs of vaccination, adverse events, masks, self-testing using rapid antigen tests, test-trace-isolate (TTI), outpatient visits, hospitalization, productivity loss and reduced sales receipt from retail and food and beverages industries were included. Health loss from adverse events, TTI and COVID infection and deaths were also included. Result(s): Among the scenarios compared, vaccination combined with NPIs yield the lowest cost (S$7.6 billion), while no vaccination with NPIs had the highest costs (S$49.1 billion). The largest loss in QALYs from the population was seen from the scenario without vaccination or NPIs. Using a dominance approach, vaccination combined with NPIs is cost saving with an ICER of -S$213 billion per QALY, compared to no vaccination with lockdown measures. The results show that NPIs alone without vaccination only delays transmission, but does not significantly change the total number of cases observed in the population. Vaccination is both cost saving and health saving as the difference in cases averted from vaccination and their associated costs, is far greater than the additional costs required to vaccinate the public. Conclusion(s): Both vaccination and NPI are critical strategies for managing the COVID pandemic. In the presence of vaccine, NPIs continue to offer benefits in terms of reduced number of infections and deaths.Copyright © 2023
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Introduction: This work was devoted to an in silico investigation conducted on twenty-eight Tacrine-hydroxamate derivatives as a potential treatment for Alzheimer's disease using DFT and QSAR modeling techniques. Method(s): The data set was randomly partitioned into a training set (22 compounds) and a test set (6 compounds). Then, fourteen models were built and were used to compute the predicted pIC50 of compounds belonging to the test set. Result(s): Al built models were individualy validated using both internal and external validation methods, including the Y-Randomization test and Golbraikh and Tropsha's model acceptance criteria. Then, one model was selected for its higher R2, R2test, and Q2cv values (R2 = 0.768, R2adj = 0.713, MSE = 0.304, R2test=0.973, Q2cv = 0.615). From these outcomes, the activity of the studied compounds toward the main protease of Cholinesterase (AChEs) seems to be influenced by 4 descriptors, i.e., the total dipole moment of the molecule (mu), number of rotatable bonds (RB), molecular topology radius (MTR) and molecular topology polar surface area (MTPSA). The effect of these descriptors on the activity was studied, in particular, the increase in the total dipole moment and the topological radius of the molecule and the reduction of the rotatable bond and topology polar surface area increase the activity. Conclusion(s): Some newly designed compounds with higher AChEs inhibitory activity have been designed based on the best-proposed QSAR model. In addition, ADMET pharmacokinetic properties were carried out for the proposed compounds, the toxicity results indicate that 7 molecules are nontoxic.Copyright © 2023 Bentham Science Publishers.
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Background: Acute myocarditis corresponds to an acute inflammation of the myocardium whose origin is most often viral. Several viruses can be incriminated to note the parvovirus B19, the virus herpes of the group 6 and to a lesser degree the virus of the hepatitis C (VHC) [18,19]. Since 2019 and with the discovery of SARS COV2 some cases of myocarditis associated with covid have been noted, this last association is rare and is present in only 5% of cases [8]. The diagnosis of myocarditis is sometimes difficult and can lead to confusion with acute coronary syndrome, especially in cases of ST-segment elevation on the EKG, hence the interest of magnetic resonance imaging, which has made it possible in recent years to reduce the rate of unnecessary coronary angiography, especially in the case of young subjects with no cardiovascular risk factors. in this context we report the case of a 33 year old patient with no cardiovascular risk factors and no medical or surgical antecedents who was admitted to the emergency department for the management of acute chest pain related to acute post-covid myocarditis, the patient was initially admitted to the cardiology intensive care unit where he was put in condition and under analgesic treatment and under therapeutic protocal of covid 19 and under anticoagulation based on low molecular weight heparin at preventive dose with a good clinical evolution he was transferred thereafter to the clinical cardiology then declared outgoing under treatment of covid 19 with an appointment of control in 1 month.
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Intro: The concurrent reopening of schools, increasing levels of hybrid immunity, and the emergence of the Omicron variant have affected the trajectory of the pandemic in India. We address related questions using the model Indian state of Andhra Pradesh (pop: 53 million). Method(s): A compartmental model which describes the disease progression of COVID-19 with two dose vaccination is employed to understand the effect of vaccination, immunity due to infection and VOC Omicron. This is an age- stratified as well as a contact-structured model. The introduction of the Omicron variant is modelled. We studied disease dynamics in a background of seropositivity gained from an earlier wave of infection as well as an ongoing vaccination program, together called "hybrid immunity". We demonstrate the effect of school reopening as well as of the Omicron (BA.2) variant on cases across different age-groups. Finding(s): Reopening schools increases cases in children as compared to adults, although most such cases are asymptomatic or mild. The height of this peak reduced as the background infection-induced seropositivity was increased from 20% to 40%. At reported values of seropositivity of 64%, no discernable peak was seen. We find that in the absence of vaccination, even at such high levels of seroprevalence, the emergence of the Omicron variant would have resulted in a large rise in cases across all age bands. Discussion(s): In India, the decreasing prevalence of immunologically naive individuals of all ages helped reduce the number of cases reported once schools were reopened. In addition, hybrid immunity, together with the lower intrinsic severity of disease associated with the Omicron variant, contributed to low reported COVID-19 hospitalizations and deaths. Conclusion(s): Mathematical modelling provides a powerful way of addressing central questions regarding the trajectory of the pandemic in India, clarifying the role of hybrid immunity.Copyright © 2023
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Background: Much of the world's population had already been infected with COVID-19 by the time that the Omicron variant emerged at the end of 2021, but the scale of the Omicron wave was larger than any that had come before or since, and left a global imprinting of immunity which changed the COVID landscape. In this study, we explore the changing value of vaccines in a landscape of dynamic immunity and rapidly evolving variants of concern. Method(s): We use Covasim, an established agent-based model of COVID-19 enhanced with detailed intra-host dynamics. First, we simulate a vaccine trial over March 2020 - April 2022 within a population resembling that of South Africa, and estimate how both vaccine efficacy (reduction in the risk of severe disease for vaccinated vs unvaccinated individuals) and efficiency (number of doses needed to avert a death) change as the population experiences waves of wild-type, Beta, Delta, and Omicron infections. Next, we introduce six hypothetical variants starting from February 2022 and evaluate the impact of (a) the existing set of vaccines, and (b) vaccines specifically targeted to the new variants. Result(s): We estimate that within our simulated population, vaccine efficacy against severe disease decreased from 80% to 20% in the wake of the first wave of wild-type COVID-19, then increased back to ~70% over the latter half of 2020 as population immunity waned. This pattern repeated following each subsequent wave of infections, with vaccine efficacy falling to its lowest (10%) in the immediate wake of the Omicron wave in December 2021. The efficiency of vaccination decreases over time at an increasing rate: at peak efficiency, fewer than 100 doses would have been required to avert a single death, but by the end of January 2022, we estimate that nearly 4,000 doses would be required to avert a single death. We find that variant-chasing vaccines will only add value above pre-existing vaccines if we can shorten the window between variant introduction and vaccine deployment to under three weeks, an impossible time-frame without significant NPI use. Conclusion(s): Although the vaccines have proven to be remarkably effective, our work demonstrates that the population immunity acquired over the first two years of the pandemic significantly reduced the impact per dose of doses delivered after this time. Next-generation vaccines to fight future COVID variants and/or other respiratory diseases must be delivered rapidly at scale for vaccine strategies to be maximally effective.
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Introduction/Aim: As health systems emerge through successive waves of COVID-19, focus shifts to the management of Post-COVID-19 conditions. The aim of this prospective observational study was to characterise and evaluate the respiratory sequelae affecting patients 6-months post-diagnosis of COVID-19. SIGNFICANT MODELLING PREDICTORS Outcome Predictors MMRC>= 1 Disease severity Moderate: OR 16.5 +/- 1.02 (SE) p = 0.006 Impaired DLCO (%predicted) Disease severity B=-1.51+/-0.67 (SE) p = 0.010 Impaired TLC (%predicted) D-Dimer B= -0.305 +/- 0.001 (SE), p = 0.05 TLC below LLN Diabetes B=-1.28 +/- 0.32 (SE), p = 0.044 Methods: Patients were evaluated for symptom burden and lung function at 6-months post-diagnosis of COVID-19 in an outpatient setting. Result(s): Fifty-eight (45 inpatients and 13 outpatients;median age 59 years, 28 females) patients attended 6-month clinic appointment. Whilst nearly half (28,48.3%) were asymptomatic at 6-months, 24 (41.3%) patients reported a modified medical research council dyspnoea scale (MMRC) >= 1 and 21 (36.2%) patient-reported fatigue (n= 21, 36.2%). Reduced TLC (n= 11/50, 22.0%) and DLCO (n = 12/51, 23.5%) were common at 6-months. Results of predictive modelling analyses are described in adjacent table. Conclusion(s): Patients presenting with increased disease severity are at risk of persistent dyspnoea and impaired diffusion capacity, 6-months following acute COVID-19 illness. Research guided management of this growing at risk cohort, while paramount, poses a formidable challenge to stretched healthcare systems.
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Background: Since early 2020, the novel SARS-CoV-2 virus has spread rapidly throughout the globe. Subsequently many individuals have developed some form of immunity due to either a prior infection, one or more vaccinations, or a combination of the two. Using local epidemic data and mathematical modeling, we enumerate the various immune populations in Washington State and Oregon and quantify the level of protection against infection and hospitalization. Method(s): We developed a compartmental model of ordinary differential equations, which stratifies the population by age (0-17 years, 18-49 years, 50-64 years, and 65+ years), region, type of immunity (naive, infectionderived, vaccine-derived, booster-derived, hybrid immunity, etc), and recency of immune conferring event (recent and waned). To track the number of individuals in each category we combine 1) literature-based estimates of susceptibility to infection and severe disease by age, immune status, and variant, 2) calibration to the number of severe infections (hospitalizations and deaths) and number of vaccinations and 3) validation with serological surveys of the population. Result(s): We estimate that by mid-April 2022 more than 95% of the populations of both Washington and Oregon had some immunity against COVID-19 infection and hospitalization. Younger age groups tended to have much higher rates of natural or hybrid immunity with 96% of 0-17-year-olds and 83% of 18-49-year-olds protected due to past infections. Overall, the population-level immunity against the Omicron variant reduced risk of infection by 59% (95% Credible Interval 54% - 62%) and risk of hospitalization by 79% (95% CI 77% - 81%) in Washington and 62% (95% CI 57% -66%) and 83% (95% CI 82% - 85%), respectively, in Oregon. There was similar population-level protection against Delta at the start of the Omicron wave in early December 2021, which reduced risk of infection by 60% (95% CI 56% - 63%) and risk of hospitalization 79% (95% CI 78% - 80%) in Washington and 66% (95%CI 63% - 70%) and 82% (81% - 83%), respectively, in Oregon. Conclusion(s): Very large waves of new infections throughout 2021 and early 2022, in addition to high levels of vaccination and boosting among the older age groups in Washington and Oregon have greatly reduced population susceptibility to currently circulating strains. However even very high population immunity has allowed for emergence of novel variants that escape existing immunity, highlighting the need for continued develop of new variantspecific boosters.
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Background: The impact of COVID-19 pandemic was apparently less severe in African continents, probably underestimated due to the limited testing capacities and access to health facilities, particularly in rural areas. Hospital and community surveillance of COVID-19 was established in Manhica District, rural Mozambique to understand the epidemic curve and natural history of SARSCoV- 2 including age-specific incidence of severe COVID-19 and reproduction number and effects of interventions through mathematical modelling Methods: Suspected cases visiting the Manhica District Hospital were screened for SARS-CoV-2 by qRT-PCR. Four age-stratified (0-19, 20-39, 40-59 and >=60 years, n=300 each) community-based serosurveys were conducted (Apr 2021-Feb 2022) to estimate the prevalence of antibodies (Abs) against SARS-CoV-2. We fitted a statistical model within a Bayesian framework, to estimate the extent to which older people were over-represented in mortality data throughout the pandemic. This involved training the model on data from the pre-pandemic period and then using this model to generate estimates of the expected levels of mortality in the absence of COVID-19 in adults aged 40+ using data from our reference category (15-39 year olds). Result(s): Between Dec 2020 and Aug 2022, 31.2% of 1332 swabs tested positive for SARS-CoV-2, with high proportion among people aged 50-59 years (62.1%, 36/58). Abs against SARS-CoV-2 were detected in 28% (180/666) of subjects enrolled in survey one, which increased two and tri-fold, in surveys 2 (64%, 595/936) and 3 (91%, 700/768);remaining stable (91.3%, 1023/1121) in 4. Age-specific analysis showed consistency on Abs detection over the surveys, including people non-eligible for vaccination (0-17 years) where >80% (165/188) had Abs detected. 93% (359/384) of subjected with Abs in survey 3, remained positive 3 months later. Shifting age-patterns throughout the pandemic are consistent with a high impact of the disease particularly in older ages. Depending on assumptions made in our modelling, we estimate a cumulative excess mortality rates in adults aged 80+ of between 8 and 17% with the largest peak coinciding with the peak in the delta variant wave. Conclusion(s): Our data reveal that people in rural areas were widely exposed across including unvaccinated ones;and there was a signature COVID-19-like shift in mortality patterns towards older ages, suggesting substantial impact, of the pandemic that is largely not reflected in patterns of confirmed COVID-19 deaths. Quantitative estimates of shift in age-patterns throughout the pandemic. (A) Shows the fit of the model to age-patterns of mortality in the pre-pandemic period 2018-2020. This model is then used to generate the expected numbers of deaths in individuals aged 40+ throughout the pandemic (2020-2022). (B) excess deaths in the pandemic relative to the model, shown in (A), black lines and grey shaded regions show estimates assuming that declines in reported mortality in under 40s are due to declines in mortality (assumption 1), coloured show equivalent estimates assuming that declines in mortality in under 40s are due to declines in ascertainment (assumption 2). (C) Shows estimates from (A) as mortality per 1000 individuals within the age strata, (D) shows each excess mortality estimate as a proportion of the population within the age strata, with seroprevalence estimated from the first two cross-sectional surveys highlighted for reference.
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Background: As COVID-19 cases persist, one potential intervention to reduce absenteeism in the workplace due to COVID-19 is to use rapid antigen diagnostics to mitigate the spread of SARS-CoV-2. Furthermore, routine testing in the workplace offers an avenue to reaching a large proportion of the population which could lead to a greater community impact beyond solely mitigating transmission events that occur in the workplace. We sought to identify the most cost-effective workplace testing strategies at the community level and within individual workplaces. Method(s): We used two models to understand how SARS-CoV-2 AgRDTs could best be implemented within the workplace to mitigate the spread of COVID-19. In our community-level dynamic transmission model, PATAT, we evaluated the impact of symptomatic testing and asymptomatic testing of a fixed proportion of the formally employed workforce on broader community transmission. We stratified runs by asymptomatic testing frequency, vaccine coverage, vaccine effectiveness, and Rt. Simulations were informed using demographic data from Georgia, Brazil, and the Netherlands. We conducted a cost-effectiveness analysis using the results from each country and assumed a $2.50 total cost per test. Result(s): We observed a substantial decrease in the number of infections occurring in both the workplace and community when a SARS-CoV-2 AgRDTs strategy was implemented. Under all conditions, mandatory symptomatic testing and related quarantine from the workplace averted up to 72%, 79%, and 74% of community infections in Brazil, Georgia, and the Netherlands respectively. Limiting tests to symptomatic workers was always on the cost-effectiveness frontier, regardless of the vaccine coverage, efficacy, or Rt of the virus (Figure 1), at $2-$4 per workplace infection prevented. While asymptomatic testing was on the cost-effectiveness frontier, it would cost an additional $500-$6700 to prevent one additional workplace infection. The added benefit of routine asymptomatic testing was minimal until 100% of the workforce was reached. Conclusion(s): We found self-testing with AgRDTs for the formally employed workforce is both efficient at reducing workplace and community infections as well as cost-effective when targeting symptomatic individuals. Willingness to pay to avoid workplace absenteeism may differ by country, individual workplaces, and the perceived economic value of several workdays missed. If there is a higher willingness to pay, routine asymptomatic screening may be considered.
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Background: People with cystic fibrosis (CF) are more likely to have anxiety and depression symptoms than the general population, with psychological distress being associated with negative health outcomes. The Cincinnati Children's Hospital Medical Center CF Center has been screening people with CF aged 12 and older since 2016 for anxiety and depressive symptoms. Little is known about longitudinal mental health trends for youth with CF, especially during the COVID-19 pandemic. Method(s): Chart review was conducted for individuals aged 12 and older seen for routine care at our center with at least one General Anxiety Disorder (GAD-7) or Patient Health Questionnaire (PHQ-9) screening result between January 2016 and December 2021. Data included demographic characteristics;dates and scores of GAD-7 and PHQ-9;mental health encounters 12 months before each screening date;and clinical variables of disease severity, including percentage predicted forced expiratory volume in 1 second (FEV1pp), body mass index, CF-related diabetes (CFRD), antibiotics in the 28 days prior, and exacerbations in the 12 months prior. Descriptive statistics were used to summarize demographic variables, logistic regression and linear mixed modeling were used to identify predictive relationships, and t-testswere used to compare impact of COVID with that of prior years. Result(s): The sample included 150 individuals with at least one screen across the 6 years. An average of 83 people completed at least one GAD-7 or PHQ-9 in each year. Across the 6-year time period, the percentage of individuals with low scores increased, and the percentage of people with moderate to severe scores was stable (Figure 1). Approximately 35% of individuals were rescreened at least once in a given year because of a previously high symptom score. For thosewho screened in the moderate to severe range (>=10) on initial screens per year, an average of 32% (GAD-7) and 37% (PHQ-9) had a lower score (<10) on their second screen per year. Individuals who scored 10 or higher on initial GAD-7 or PHQ-9 screens in any year were statistically more likely to have a CFRD diagnosis ( p = 0.02, GAD-7;p = 0.02, PHQ-9) and more psychology or psychiatry visits 12 months before the screening date ( p < 0.01, GAD-7;p < 0.01, PHQ-9) than those with minimal scores. In addition, PHQ-9 scores of 10 or greater were significantly associated with lower FEV1pp than low scores. Adherence to screening protocols consistently increased over time. Of all eligible individuals, 56% completed a GAD-7 and 55% a PHQ-9 in 2016, increasing to 92% and 94%, respectively, by 2021, despite the impact of the COVID-19 pandemic on CF care visit frequency. GAD-7 scores were not significantly different before COVID and during COVID ( p = 0.06);PHQ-9 scores were higher before than during COVID ( p = 0.02) despite similar numbers of screens conducted per year. (Figure Presented)Figure 1. Percentage of initial Patient Health Questionnaire (PHQ-9) and General Anxiety Disorder (GAD-7) scores per year from 2016 to 2021 of people with cystic fibrosis seen at Cincinnati Children's Hospital Medical Center Conclusion(s): These longitudinal trends in mental health symptom scores over time are reassuring,with increasing frequency of lowscores and stable moderate to severe scores. This may be because of greater awareness of mental health symptoms, more interventions through care teams, or improved access to resources. Similarly, although general population data suggest worsening of anxiety and depressive symptoms during the COVID- 19 pandemic, we hypothesize thatwewere able to buffer the impact of the pandemic on mental health in our center by screening and responding to screens. These results highlight the importance of consistent monitoring and support for mental health symptoms in people with CFCopyright © 2022, European Cystic Fibrosis Society. All rights reserved
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Background: Throughout the COVID-19 pandemic, it was evident that many SARS-CoV-2 infections occurred at mass gathering events. In many LMICs and LICs, places of worship serve as a venue for mass gatherings, and therefore a potential source of large-scale transmission events. Mass gatherings at places of worship also serve as an opportunity to distribute Ag-RDTs to a significant proportion of the community at regular intervals, disrupting transmission within the event and potentially impacting community spread of SARS-CoV-2. Method(s): We used an agent-based community assessment model, Propelling Action for Testing and Treatment, to estimate how various strategies of asymptomatic Ag-RDT self-testing of a fixed percentage of persons attending large religious gatherings (10%, 20%, 40%, 100%), in addition to the general underlying level of ongoing symptomatic testing in the population, would impact community transmission of SARS-CoV-2 in 3 contexts (Brazil, Georgia, Zambia). These testing strategies were analyzed with bi-weekly and weekly asymptomatic self-testing in a population with varying levels of vaccine efficacy (low/high), vaccine coverage (10%, 50%, 80%), and reproductive numbers (0.9, 1.2, 1.5, and 2.0) to simulate varying stages of the COVID-19 pandemic. We then performed an economical evaluation of the results from the model to understand the impact and cost-effectiveness of each self-testing strategy at places of worship. Result(s): In each of the epidemic conditions modeled, testing of symptomatic persons at weekly and biweekly frequencies can avert 2%-16% of Brazilian community infections and 31%-45% of infections occurring in places of worship in Brazil. The same is true in Georgia (1%-6% of total infections and 28%-45% place of worship-related infections) and Zambia (2%-21% of total infections and 29%-45% of place of worship related infections) despite differences in the proportion of populations regularly attending places of worship in the 3 countries. Asymptomatic self-testing in 100% of places of worship in a country result in the greatest percent of infections averted and consistently lands on the cost-effectiveness frontier yet requires a budget 520- 1550x greater than that of symptomatic testing alone. Conclusion(s): Testing of symptomatic persons attending regular religious gatherings have a significant impact on the spread of SARS-CoV-2 in places of worship and can significantly reduce community spread in contexts where population level attendance at religious gatherings is high. Cost-effectiveness analysis from Brazil, Georgia and Zambia modelling results with infections averted within places of worship and total community infections averted assuming a total cost per self-test of $2.50 USD.
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The novel coronavirus pandemic has continued to spread worldwide for more than two years. The development of automated solutions to support decision-making in pandemic control is still an ongoing challenge. This study aims to develop an agent-based model of the COVID-19 epidemic process to predict its dynamics in a specific area. The model shows sufficient accuracy for decision-making by public health authorities. At the same time, the advantage of the model is that it allows taking into account the stochastic nature of the epidemic process and the heterogeneity of the studied population. At the same time, the adequacy of the model can be improved with a more detailed description of the population and external factors that can affect the dynamics of the epidemic process. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The proceedings contain 71 papers. The topics discussed include: experience of learning human anatomy and histology during COVID-19 pandemic in Kharkiv National Medical University;using musculoskeletal modelling to investigate the functional significance of craniofacial form variation within the genus homo;a morphometric analysis of the cranial fossae in patients with scaphocephaly;exploring the thalamus in young adolescents with psychotic experiences;to replace or not replace that is the question: addressing fate decisions during minipig tooth replacement;anatomy of termination of popliteal artery: a multidetector CT angiographic study;anatomical variation between populations of British red squirrels: the potential impact of supplementary feeding;revealing the biomechanics of the masticatory muscles in the eastern grey squirrel (Sciurus carolinensis) using multibody dynamics analysis;and myoepithelial and immune cell dynamics in the ovine mammary gland during postnatal development.
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Individuals with comorbidities (i.e., Diabetes Mellitus, hypertension, heart diseases) are more likely to develop a more severe form of coronavirus disease 2019 (COVID-19), thus, they should take necessary precautions to avoid infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its emerging variants and subvariants by getting COVID-19 vaccination and booster doses. In this regard, we used text analytics techniques, specifically Natural Language Processing (NLP), to understand the perception of Twitter users having comorbidities (diabetes, hypertension, and heart diseases) towards the COVID-19 vaccine booster doses. Understanding and identifying Twitter users' perceptions and perspectives will help the members of medical fraternities, governments, and policymakers to frame and implement a suitable public health policy for promoting the uptake of booster shots by such vulnerable people. A total of 176,540 tweets were identified through the scrapping process to understand the perception of individuals with the mentioned comorbidities regarding the COVID-19 booster dose. From sentiment analysis, it was revealed that 57.6% out of 176,540 tweets expressed negative sentiments about the COVID-19 vaccine booster doses. The reasons for negative expressions have been found using the topic modeling approach (i.e., risk factors, fear of myocardial fibrosis, stroke, or death, and using vaccines as bio-weapons). Of note, enhancing the COVID-19 vaccination drive by administering its booster doses to more and more people is of paramount importance for rendering higher protective immunity under the current threats of recently emerging newer Omicron subvariants which are presently causing a rise in cases in a few countries, such as China and others, and might lead to a feasible new wave of the pandemic with the surge in cases at the global level. Copyright © The Author(s) 2023.
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Concerns about an increase in cases during the COVID-19 pandemic have been heightened by the emergence of a new Omicron subvariant XBB.1.5 that joined the previously reported BF.7 as a source of public health concern. COVID-19 cases have been on the rise intermittently throughout the ongoing pandemic, likely because of the continuous introduction of SARS-CoV-2 subtypes. The present study analyzed the Indian citizen's perceptions of the latest covid variants XBB.1.5 and BF.7 using the natural language processing technique, especially topic modeling and sentiment analysis. The tweets posted by Indian citizens regarding this issue were analyzed and used for this study. Government authorities, policymakers, and healthcare officials will be better able to implement the necessary policy effectively to tackle the XBB 1.5 and BF.7 crises if they are aware of the people's sentiments and concerns about the crisis. A total of 8,54,312 tweets have been used for this study. Our sentiment analysis study has revealed that out of those 8,54,312 tweets, the highest number of tweets (n = 3,19,512 tweets (37.3%)) about COVID variants XBB.1.5 and BF.7 had neutral sentiments, 3,16,951 tweets (37.1%) showed positive sentiments and 2,17,849 tweets (25.4%) had negative sentiments. Fear of the future and concerns about the immunity of the vaccines are of prime concerns to tackle the ongoing pandemic. Copyright © The Author(s) 2023.
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Background Biochemical markers of cardiac injury and strain are proven indicators of severe COVID-19. Whether enzyme elevation is a product of cardiopulmonary strain versus myocardial viral injury is not well defined. CARDIO-COVID is a registry designed to study COVID-19 patients admitted to ICUs with evidence of cardiac injury. Methods Inclusion criteria for the CARDIO-COVID registry are PCR positive test for SARS-CoV2, ICU admission and either elevated troponin, elevated NT-proBNP/BNP, or new onset heart failure. Registry contains 1328 cases from 16 centers in the US, Canada, and Europe. 838 cases were included for analysis. Cases were collected between March 2020 - May 2021. Multivariate regression analyses were performed. Results Patients were 51.3% male, average age of 67.4 years and 32% Caucasian. 63% had pre-existing cardiovascular disease. Morbidity and mortality were common: 40% died, 50% underwent intubation, 20% required renal replacement therapy, and 5% had cardiac arrest requiring CPR. New onset arrhythmias were common (26%), but VT/VF was rare (4.8%). Cardiovascular complications were minor drivers of morbidity: 4.8% had ACS requiring catheterization, 8.0% had new onset heart failure (median EF 43% (IQR 31 - 47.75%), 4.4% had a CVA, and 6.7% had PE. Of patients who died, 65% died from hypoxemic respiratory failure, 10.5% from septic shock, 9.3% from PEA, and 3.1% from cardiogenic shock. Modeling showed insignificant increased odds of death in patients with MACE (p-value 0.22, OR 1.94 CI 0.67 - 5.82). Age (p-value 0.005) and intubation (p-value 0.001, OR 5.8 CI 2.1 - 18) were strongest predictors of death. Every increase in age by one year was associated with 5% increase in odds of death. Degree of cardiac enzyme elevation was not associated with MACE, death, or intubation. Conclusion While elevated cardiac enzymes are common in severe COVID-19, cardiac complications are not common drivers of mortality. Respiratory failure and septic shock are leading causes of death. These findings suggest that in severe COVID-19 cardiac enzyme elevation usually reflects cardiopulmonary strain from respiratory distress rather than myocardial injury portending cardiac failure or death.Copyright © 2023 American College of Cardiology Foundation
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How an infection propagates inside the lung is not well understood. Capturing its dynamics might help to understand how pathologies such as COVID19 can lead to rapid airways inflammation and respiratory failure. We hypothesized that respiratory failure might result from the interaction between the propagation of the infection from airway to airway (inner contagiousness) and the pathogen virulence. We develop a mathematical model of the infection and inflammation of the proximal lung (511 susceptible airways) by a generic pathogen that propagates from neighbor to neighbor between the airways. The degree of respiratory failure is evaluated by computing the mean number of infected airways (NI) and the mean drop in oxygen transfer to blood (DOx), assuming no compensation from patient ventilation. We simulated 840 idealized patients, covering 3 different degrees of virulence (Cured (C), Aseptic (A) and Septic (S) outcomes) and 14 degrees of contagiousness (1<=c<=14, arbitrary units). When virulence increases, the pathogens remain longer in the airways, increasing the propagation probability: NI(C)=51, DOx(C)=8.9%;NI(A)=410, DOx(A)=47.2%;NI(S)=511, DOx(S)=55.5%. For low contagiousness, c=1, NI(C)=1.6, DOx(C)=2.2%;NI(A)=132, DOx(A)=25.8%. However, NI(S)=511 and DOx(S)=52.2%. High contagiousness, c=14, leads to a large propagation whatever the virulence (NI(S/A)=511 and DOx(S/A)=57.5%;NI(C)=428 and DOx(C)=38.6%). Medium virulence and contagiousness also lead to a large propagation: for c=7, NI(A)=508, DOx=52.5%. Residence time of pathogens and inner contagiousness are interacting factors that might bring high NI and DOx. This interaction might be a core determinant of potential respiratory failure.
ABSTRACT
The proceedings contain 123 papers. The topics discussed include: national study on the risks of COVID-19 for pediatric renal transplant recipients;evaluation of a creative photography workshop for children and young people following a diagnosis of PIMS-TS;reducing blood product usage through technology in transplantation;pharmacokinetic modelling of different tacrolimus formulations in children and adolescents;pediatric laparoscopic splenectomy: a single center 11 years' experience;our people: pursuing positivity in the pandemic - 'pause, power up, push on';delivering digital learning packages to address allied health professionals' skill gaps in research;building Bertie bowel: designing an immersive simulation experience for pediatric radiology teams managing intussusception;development of OctiPAT: a patient-facing mobile and web-based application to provide higher quality, patient-focused, multidisciplinary care to a complex patient cohort;and implementing Speech@Home into clinical practice using a quality improvement (QI) methodology.
ABSTRACT
Background: Natural disasters and pandemics can be highly challenging to blood supply chains. This review aimed to assess the impacts of pandemics and natural disasters on blood donation globally, appraise any similarities and differences, and provide an overview of the mitigation strategies and optimizations applied as well as risks modelling undertaken. Method(s): Full text, peer-reviewed articles that studied the impact of any pandemic and natural disaster on blood donation, blood supply management, and modelling searchable in PubMed, Scopus, Web of Science, and Cochrane Library between Jan 1980 and Jan 2023, inclusive were included. We performed quality assessments and summarised potential lessons learned. Result(s): Overall, 98 studies were identified and assessed in this review, of which 58 were related to pandemics and 17 related to natural disasters. 97% of the studies on pandemics and blood donation were on COVID-19, while 88% of studies on natural disasters were on earthquakes. We confirmed that during the COVID-19 pandemic, blood donation numbers decreased compared to the pre-pandemic period, while just after an earthquake, blood donation numbers tended to increase, which in both cases put the blood supply chain under pressure (creating shortage or wastage). The increase of first-time donors was higher after a sudden destructive earthquake than after the COVID-19 pandemic. Public awareness campaigns, donors transportation, home visits, measures to minimize wastage of blood components, activation of contingency plans, and altering donor eligibility criteria were implemented to help the blood supply chain to respond to the demand and reduce wastage. However, no pandemic plans, per se were identified highlighting the lack of an emergency plan in collaboration with health authorities. Several optimization models were developed to help the blood supply chain reduce costs and identify faster transportation in times of earthquake, however, optimization models targeting a pandemic were lacking, as were risk modelling analyses for both events. Conclusion(s): Optimization models, risk modelling, serosurveillance and haemovigilance should be combined with infectious diseases case surveillance to better prepare the whole supply chain logistics to safely attend the demand. Findings on blood donor demographics were inconclusive during or after major events, which highlight the need for further investigations.Copyright © 2023 The Authors