AVASCULAR NECROSIS OF HIP AFTER ACTIVE COVID-19 INFECTION

Background and objectives: The course of SARS-CoV-2 (COVID-19) is still under analysis. The majority of complications arising from the infection are related to the respiratory system. The adverse effect of the viral infection on bone and joint tissue has also been observed. Materials and Methods: We present a group of 10 patients with degeneration of hip, with a background of avascular necrosis (AVN) immediately after infection with the COVID-19 virus. In MR imaging, changes in the characteristics of AVN were documented. Results: Observation of this group showed a clear correlation among the history of COVID-19 disease in the patients, moderately severe symptoms, high levels of IgG antibodies, and the time of occurrence of joint changes. No other clinically significant complications were observed following COVID-19 infection in the study group. No other risk factors for AVN or autoimmune or degenerative diseases were found in the study group. The group of patients responded well to empirical treatment with steroids, which normalized acute inflammatory symptoms and pain in the joints. Conclusions: During coronavirus (COVID-19) infection, there are complications in the locomotor system, such as microembolism and the formation of AVN;hence, more research is needed. [ FROM AUTHOR] Copyright of Journal of Cardiovascular Disease Research (Journal of Cardiovascular Disease Research) is the property of Journal of Cardiovascular Disease Research and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

SARS-CoV-2 Infections, Clinical Characteristics, and Related Risk Factors: The First 8 Months Surveillance Study Conducted in Southwest Ethiopia.

Coronavirus disease 2019 (COVID-19) is caused by a severe acute respiratory syndrome coronavirus (SARS-CoV-2) and became pandemic after emerging in Wuhan, China, in December 2019. We aimed to investigate the prevalence, clinical characteristics, and risk factors for SARS-CoV-2 infections in districts of southwest Ethiopia. A study was conducted on COVID-19 surveillance data in the diagnostic center of the southwest district of Ethiopia from July 1, 2020, to February 30, 2021. A total of 10 618 nasopharyngeal specimens were tested for SARS-COV-2 using the detection of unique sequences of virus RNA by reverse transcriptase PCR. Data were entered into Epidata version 3.1 and analyzed using SPSS version 25. Logistic regression was used to determine the relationship between COVID-19 and risk factors, with a significance level of P = 0.05. A total of 10 618 individuals were tested for SARS-CoV-2. Of these, 419 (3.9%) patients tested positive for SARS-CoV-2. Among a total of 419 patients who tested positive for SARS-CoV-2, 80.2% were asymptomatic, 264 (63.0%) were males, and 233 (55.6%) were aged 19 to 35 years. Comorbidity was present in 37 (8.8%). The risk of getting SARS-CoV-2 infections was increased with male sex (AOR = 1.248; 95% CI: 1.007, 1.547), health workers (AOR = 3.187; 95% CI: 1.960, 5.182), prisoners (AOR = 2.118; 95% CI: 1.104, 4.062), and comorbid conditions (AOR = 2.972; 95% CI: 1.649, 5.358), such as diabetes (AOR = 4.765; 95% CI: 1.977-11.485) and other respiratory problems (AOR = 3.267; 95% CI: 1.146-9.317). Despite the fact that overall laboratories confirmed prevalence of SARS-CoV-2 infections in the study area was low and dynamic, it was spread to all zones of the study area. This highlights the importance of implementing the most effective public health strategies to prevent the further spread and reduce the burden of SARS-CoV-2 infections.

The effect of current infection control procedures and application times on the dimensional stability of dental impression materials

Aims: In this study, the effects of different disinfection and sterilization methods and their application duration on the dimensional stability of impression materials were evaluated. Methods: Two impression materials, condensation (CS) and addition silicone (VPS), disinfectants with 5.25% sodium hypochlorite (NaOCl) immersion, 3% hydrogen peroxide immersion and steam autoclave were selected. Disc-shaped samples (n=112) were obtained in 7 subgroups of each material (n=8). Sixteen untreated samples served as controls. Dimensional change was measured with a digital micrometer in the reference lines on the sample. Results: The highest mean percentage of dimensional change for the 50 min autoclave was 0.10±0.03% for CS and 0.10±0.02% for VPS. The dimensional change in CS did not differ for hydrogen peroxide. Compared with the controls, dimensional change was significant in 20 min NaOCl and 50 min autoclave (p<.05). Both impression materials in the autoclave showed statistically significant dimensional changes regardless of the time. The difference in application duration significantly affected the dimensional stability of the impression materials regardless of the procedure (p<.001). Extended application duration did not affect the dimensional stability in the hydrogen peroxide for CS, NaOCl and autoclave for VPS. Conclusions: Chemical disinfection and autoclave sterilization caused statistically significant but clinically acceptable dimensional changes in CS and VPS impression materials used in this study.

Dynamic chest computed tomography change analysis and prediction of length of stay for delta variant COVID-19 patients

OBJECTIVE: As hospital admission rate is high during the COVID-19 pandemic, hospital length of stay (LOS) is a key indicator of medical resource allocation. This study aimed to elucidate specific dynamic longitudinal computed tomography (CT) imaging changes for patients with COVID-19 over in-hospital and predict individual LOS of COVID-19 patients with Delta variant of SARS-CoV-2 using the machine learning method. MATERIALS AND METHODS: This retrospective study recruited 448 COVID-19 patients with a total of 1761 CT scans from July 14, 2021 to August 20, 2021 with an averaged hospital LOS of 22.5 ± 7.0 days. Imaging features were extracted from each CT scan, including CT morphological characteristics and artificial intelligence (AI) extracted features. Clinical features were obtained from each patient's initial admission. The infection distribution in lung fields and progression pattern tendency was analyzed. Then, to construct a model to predict patient LOS, each CT scan was considered as an independent sample to predict the LOS from the current CT scan time point to hospital discharge combining with the patients' corresponding clinical features. The 1761 follow-up CT data were randomly split into training set and testing set with a ratio of 7:3 at patient-level. A total of 85 most related clinical and imaging features selected by Least Absolute Shrinkage and Selection Operator were used to construct LOS prediction model. RESULTS: Infection-related features were obtained, such as the percentage of the infected region of lung, ground-glass opacity (GGO), consolidation and crazy-paving pattern, and air bronchograms. Their longitudinal changes show that the progression changes significantly in the earlier stages (0–3 days to 4–6 days), and then, changes tend to be statistically subtle, except for the intensity range between (−470 and −70) HU which exhibits a significant increase followed by a continuous significant decrease. Furthermore, the bilateral lower lobes, especially the right lower lobe, present more severe. Compared with other models, combining the clinical, imaging reading, and AI features to build the LOS prediction model achieved the highest R2 of 0.854 and 0.463, Pearson correlation coefficient of 0.939 and 0.696, and lowest mean absolute error of 2.405 and 4.426, and mean squared error of 9.176 and 34.728 on the training and testing set. CONCLUSION: The most obvious progression changes were significantly in the earlier stages (0–3 days to 4–6 days) and the bilateral lower lobes, especially the right lower lobe. GGO, consolidation, and crazy-paving pattern and air bronchograms are the most main CT findings according to the longitudinal changes of infection-related features with LOS (day). The LOS prediction model of combining clinical, imaging reading, and AI features achieved optimum performance.

Prognostic impact of CT severity score in childhood cancer with SARS-CoV-2

BackgroundCT chest severity score (CTSS) is a semi-quantitative measure done to correlate the severity of the pulmonary involvement on the CT with the severity of the disease.The objectives of this study are to describe chest CT criteria and CTSS of the COVID-19 infection in pediatric oncology patients, to find a cut-off value of CTSS that can differentiate mild COVID-19 cases that can be managed at home and moderate to severe cases that need hospital care.A retrospective cohort study was conducted on 64 pediatric oncology patients with confirmed COVID-19 infection between 1 April and 30 November 2020. They were classified clinically into mild, moderate, and severe groups. CT findings were evaluated for lung involvement and CTSS was calculated and range from 0 (clear lung) to 20 (all lung lobes were affected).ResultsOverall, 89% of patients had hematological malignancies and 92% were under active oncology treatment. The main CT findings were ground-glass opacity (70%) and consolidation patches (62.5%). In total, 85% of patients had bilateral lung involvement, ROC curve showed that the area under the curve of CTSS for diagnosing severe type was 0.842 (95% CI 0.737–0.948). The CTSS cut-off of 6.5 had 90.9% sensitivity and 69% specificity, with 41.7% positive predictive value (PPV) and 96.9% negative predictive value (NPV). According to the Kaplan–Meier analysis, mortality risk was higher in patients with CT score > 7 than in those with CTSS < 7.ConclusionPediatric oncology patients, especially those with hematological malignancies, are more vulnerable to COVID-19 infection. Chest CT severity score > 6.5 (about 35% lung involvement) can be used as a predictor of the need for hospitalization.

The effects of obesity and metabolic abnormalities on severe COVID-19-related outcomes after vaccination: A population-based study.

Breakthrough SARS-CoV-2 infections of vaccinated individuals are being reported globally, resulting in an increased risk of hospitalization and death among such patients. Therefore, it is crucial to identify the modifiable risk factors that may affect the protective efficacy of vaccine use against the development of severe COVID-19 and thus to initiate early medical interventions. Here, in population-based studies using the UK Biobank database and the 2021 National Health Interview Survey (NHIS), we analyzed 20,362 participants aged 50 years or older and 2,588 aged 18 years or older from both databases who tested positive for SARS-COV-2, of whom 33.1% and 67.7% received one or more doses of vaccine, respectively. In the UK Biobank, participants are followed from the vaccination date until October 18, 2021. We found that obesity and metabolic abnormalities (namely, hyperglycemia, hyperlipidemia, and hypertension) were modifiable factors for severe COVID-19 in vaccinated patients (all p < 0.05). When metabolic abnormalities were present, regardless of obesity, the risk of severe COVID-19 was higher than that of metabolically normal individuals (all p < 0.05). Moreover, pharmacological interventions targeting such abnormalities (namely, antihypertensive [adjusted hazard ratio (aHR) 0.64, 95% CI 0.48-0.86; p = 0.003], glucose-lowering [aHR 0.55, 95% CI 0.36-0.83; p = 0.004], and lipid-lowering treatments [aHR 0.50, 95% CI 0.37-0.68; p < 0.001]) were significantly associated with a reduced risk for this outcome. These results show that more proactive health management of patients with obesity and metabolic abnormalities is critical to reduce the incidence of severe COVID-19 after vaccination.

Integrated genomic surveillance enables tracing of person-to-person SARS-CoV-2 transmission chains during community transmission and reveals extensive onward transmission of travel-imported infections, Germany, June to July 2021.

BackgroundTracking person-to-person SARS-CoV-2 transmission in the population is important to understand the epidemiology of community transmission and may contribute to the containment of SARS-CoV-2. Neither contact tracing nor genomic surveillance alone, however, are typically sufficient to achieve this objective.AimWe demonstrate the successful application of the integrated genomic surveillance (IGS) system of the German city of Düsseldorf for tracing SARS-CoV-2 transmission chains in the population as well as detecting and investigating travel-associated SARS-CoV-2 infection clusters.MethodsGenomic surveillance, phylogenetic analysis, and structured case interviews were integrated to elucidate two genetically defined clusters of SARS-CoV-2 isolates detected by IGS in Düsseldorf in July 2021.ResultsCluster 1 (n = 67 Düsseldorf cases) and Cluster 2 (n = 36) were detected in a surveillance dataset of 518 high-quality SARS-CoV-2 genomes from Düsseldorf (53% of total cases, sampled mid-June to July 2021). Cluster 1 could be traced back to a complex pattern of transmission in nightlife venues following a putative importation by a SARS-CoV-2-infected return traveller (IP) in late June; 28 SARS-CoV-2 cases could be epidemiologically directly linked to IP. Supported by viral genome data from Spain, Cluster 2 was shown to represent multiple independent introduction events of a viral strain circulating in Catalonia and other European countries, followed by diffuse community transmission in Düsseldorf.ConclusionIGS enabled high-resolution tracing of SARS-CoV-2 transmission in an internationally connected city during community transmission and provided infection chain-level evidence of the downstream propagation of travel-imported SARS-CoV-2 cases.

Fruit-CoV: An efficient vision-based framework for speedy detection and diagnosis of SARS-CoV-2 infections through recorded cough sounds.

COVID-19 is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This deadly virus has spread worldwide, leading to a global pandemic since March 2020. A recent variant of SARS-CoV-2 named Delta is intractably contagious and responsible for more than four million deaths globally. Therefore, developing an efficient self-testing service for SARS-CoV-2 at home is vital. In this study, a two-stage vision-based framework, namely Fruit-CoV, is introduced for detecting SARS-CoV-2 infections through recorded cough sounds. Specifically, audio signals are converted into Log-Mel spectrograms, and the EfficientNet-V2 network is used to extract their visual features in the first stage. In the second stage, 14 convolutional layers extracted from the large-scale Pretrained Audio Neural Networks for audio pattern recognition (PANNs) and the Wavegram-Log-Mel-CNN are employed to aggregate feature representations of the Log-Mel spectrograms and the waveform. Finally, the combined features are used to train a binary classifier. In this study, a dataset provided by the AICovidVN 115M Challenge is employed for evaluation. It includes 7,371 recorded cough sounds collected throughout Vietnam, India, and Switzerland. Experimental results indicate that the proposed model achieves an Area Under the Receiver Operating Characteristic Curve (AUC) score of 92.8% and ranks first on the final leaderboard of the AICovidVN 115M Challenge. Our code is publicly available.

Meta-Data Analysis to Explore the Hub of the Hub-Genes That Influence SARS-CoV-2 Infections Highlighting Their Pathogenetic Processes and Drugs Repurposing.

The pandemic of SARS-CoV-2 infections is a severe threat to human life and the world economic condition. Although vaccination has reduced the outspread, but still the situation is not under control because of the instability of RNA sequence patterns of SARS-CoV-2, which requires effective drugs. Several studies have suggested that the SARS-CoV-2 infection causing hub differentially expressed genes (Hub-DEGs). However, we observed that there was not any common hub gene (Hub-DEGs) in our analyses. Therefore, it may be difficult to take a common treatment plan against SARS-CoV-2 infections globally. The goal of this study was to examine if more representative Hub-DEGs from published studies by means of hub of Hub-DEGs (hHub-DEGs) and associated potential candidate drugs. In this study, we reviewed 41 articles on transcriptomic data analysis of SARS-CoV-2 and found 370 unique hub genes or studied genes in total. Then, we selected 14 more representative Hub-DEGs (AKT1, APP, CXCL8, EGFR, IL6, INS, JUN, MAPK1, STAT3, TNF, TP53, UBA52, UBC, VEGFA) as hHub-DEGs by their protein-protein interaction analysis. Their associated biological functional processes, transcriptional, and post-transcriptional regulatory factors. Then we detected hHub-DEGs guided top-ranked nine candidate drug agents (Digoxin, Avermectin, Simeprevir, Nelfinavir Mesylate, Proscillaridin, Linifanib, Withaferin, Amuvatinib, Atazanavir) by molecular docking and cross-validation for treatment of SARS-CoV-2 infections. Therefore, the findings of this study could be useful in formulating a common treatment plan against SARS-CoV-2 infections globally.

Attitude and Level of COVID-19 Vaccination among Women in Reproductive Age during the Fourth Pandemic Wave: A Cross-Sectional Study in Poland.

COVID-19 vaccination, apart from the sanitary regime, is the most efficient strategy to limit the spread of the SARS-CoV-2 virus and significantly reduce the severity of the disease following infection. A cross-sectional survey was conducted during the fourth wave of the COVID-19 pandemic among pregnant Polish women and women who have already given birth to evaluate the level and attitude to vaccination. Briefly, 1196 women (256 pregnant and 940 mothers) participated in the study; 68.0% of pregnant women and 66.2% of mothers declared that they had received COVID-19 vaccination. The most frequently stated reasons not to get vaccinated were possible adverse effects on the mother, fetus or breastfed child, post-vaccination complications and limited scientific evidence on the safety of the COVID-19 vaccine. The identified predictors of avoiding COVID-19 vaccination are young age, residing in small cities or rural areas, cohabitation, low anxiety level regarding SARS-CoV-2 infection, and little knowledge concerning maternal vaccine-induced immune protection delivered to offspring. Despite the unlimited access to COVID-19 vaccination, the declared level of vaccination is worryingly low. The knowledge concerning the benefits of vaccination to mothers and their offspring is not satisfactory and requires urgent educational action, particularly among young women living outside big cities and single motherhood.

Importance of Vaccination against SARS-CoV-2 in Patients with Interstitial Lung Disease Associated with Systemic Autoimmune Disease.

OBJECTIVES: To describe the frequency of COVID-19 and the effect of vaccination in patients with interstitial lung disease and systemic autoimmune disease (ILD-SAD) and to identify factors associated with infection and severity of COVID-19. METHODS: We performed a cross-sectional multicenter study of patients with ILD-SAD followed between June and October 2021. The main variable was COVID-19 infection confirmed by a positive polymerase chain reaction (PCR) result for SARS-CoV-2. The secondary variables included severity of COVID-19, if the patient had to be admitted to hospital or died of the disease, and vaccination status. Other variables included clinical and treatment characteristics, pulmonary function and high-resolution computed tomography. Two logistic regression was performed to explore factors associated with "COVID-19" and "severe COVID-19". RESULTS: We included 176 patients with ILD-SAD: 105 (59.7%) had rheumatoid arthritis, 49 (27.8%) systemic sclerosis, and 22 (12.54%) inflammatory myopathies. We recorded 22/179 (12.5%) SARS-CoV-2 infections, 7/22 (31.8%) of them were severe and 3/22 (13.22%) died. As to the vaccination, 163/176 (92.6%) patients received the complete doses. The factors associated with SARS-CoV-2 infection were FVC (OR (95% CI), 0.971 (0.946-0.989); p = 0.040), vaccination (OR (95% CI), 0.169 (0.030-0.570); p = 0.004), and rituximab (OR (95% CI), 3.490 (1.129-6.100); p = 0.029). The factors associated with severe COVID-19 were the protective effect of the vaccine (OR (95% CI), 0.024 (0.004-0.170); p < 0.001) and diabetes mellitus (OR (95% CI), 4.923 (1.508-19.097); p = 0.018). CONCLUSIONS: Around 13% of patients with ILD-SAD had SARS-CoV-2 infection, which was severe in approximately one-third. Most patients with severe infection were not fully vaccinated.

Acute appendicitis during the COVID-19 pandemic-changes in incidence and clinical presentation but not in patients' outcome.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic is an ongoing severe issue. OBJECTIVE: The aim of this study was to compare the incidence, severity and treatment of acute appendicitis (AA) before and during the COVID-19 pandemic. METHODS: A retrospective cohort analysis was conducted between January 2019 and April 2020 in one high-volume center. A comparison was performed between two groups (Group A: patients admitted with AA before the COVID-19 pandemic; Group B: patients admitted with AA at the beginning of the pandemic) in terms of the incidence of AA and clinical and pathological outcomes. The incidence of AA was also analyzed in six surrounding peripheral hospitals. RESULTS: A total of 94 patients were identified, 54 in Group A and 40 in Group B (57% vs. 43%). Demographic data were comparable between groups. AA in Group B showed a significant higher rate of histological advanced cases (10 (18.5%) Group A vs. 20 (50%) Group B, P = 0.001) and the need for postoperative antibiotic treatment (6 (11.1%) Group A vs. 11 (27.5%) Group B, P = 0.045). During the pandemic, a higher percentage of patients were treated at peripheral hospitals (Group A: 54/111 vs. 40/126). CONCLUSION: During the onset of the COVID-19 pandemic there was a significant decrease of patients with AA in a high-volume center, which showed more advanced disease of AA. This significant decrease in the high-volume center correlates with an increase in patients with AA in peripheral hospitals and represents a change in patient flow during the onset of the pandemic.

Impact of Changes in Infection Control Measures on the Dynamics of COVID-19 Infections in Schools and Pre-schools.

Introduction: With the increased emergence of SARS-CoV-2 variants, the impact on schools and preschools remains a matter of debate. To ensure that schools and preschools are kept open safely, the identification of factors influencing the extent of outbreaks is of importance. Aim: To monitor dynamics of COVID-19 infections in schools and preschools and identify factors influencing the extent of outbreaks. Methods: In this prospective observational study we analyzed routine surveillance data of Mecklenburg-Western Pomerania, Germany, from calendar week (CW) 32, 2020 to CW19, 2021 regarding SARS-CoV-2 infection events in schools and preschools considering changes in infection control measures over time. A multivariate linear regression model was fitted to evaluate factors influencing the number of students, teachers and staff tested positive following index cases in schools and preschools. Due to an existing multicollinearity in the common multivariate regression model between the variables "face mask obligation for children" and "face mask obligation for adults", two further separate regression models were set up (Multivariate Model Adults and Multivariate Model Children). Results: We observed a significant increase in secondary cases in preschools in the first quarter of 2021 (CW8 to CW15, 2021), and simultaneously a decrease in secondary cases in schools. In multivariate regression analysis, the strongest predictor of the extent of the outbreaks was the teacher/ caregiver mask obligation (B = -1.9; 95% CI: -2.9 to -1.0; p < 0.001). Furthermore, adult index cases (adult only or child+adult combinations) increased the likelihood of secondary cases (B = 1.3; 95% CI: 0.9 to 1.8; p < 0.001). The face mask obligation for children also showed a significant reduction in the number of secondary cases (B = -0.6; 95% CI: -0.9 to -0.2; p = 0.004. Conclusion: The present study indicates that outbreak events at schools and preschools are effectively contained by an obligation for adults and children to wear face masks.

Avascular Necrosis Bone Complication after Active COVID-19 Infection: Preliminary Results.

Background and objectives: The course of SARS-CoV-2 (COVID-19) is still under analysis. The majority of complications arising from the infection are related to the respiratory system. The adverse effect of the viral infection on bone and joint tissue has also been observed. Materials and Methods: We present a group of 10 patients with degeneration of large joints and adjacent epiphyses of long bones and the spine, with a background of bone infarctions and avascular necrosis (AVN) immediately after infection with the COVID-19 virus. In MR imaging, changes in the characteristics of AVN were documented. Results: Observation of this group showed a clear correlation among the history of COVID-19 disease in the patients, moderately severe symptoms, high levels of IgG antibodies, and the time of occurrence of joint changes. No other clinically significant complications were observed following COVID-19 infection in the study group. No other risk factors for AVN or autoimmune or degenerative diseases were found in the study group. The group of patients responded well to empirical treatment with steroids, which normalized acute inflammatory symptoms and pain in the joints. Conclusions: During coronavirus (COVID-19) infection, there are complications in the locomotor system, such as microembolism and the formation of AVN; hence, more research is needed.

Coronavirus Disease 2019 Vaccine Impact on Rates of Severe Acute Respiratory Syndrome Coronavirus 2 Cases and Postvaccination Strain Sequences Among Health Care Workers at an Urban Academic Medical Center: A Prospective Cohort Study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) vaccine trials and post-implementation data suggest that vaccination decreases infections. We examine vaccination's impact on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) case rates and viral diversity among health care workers (HCWs) during a high community prevalence period. METHODS: In this prospective cohort study, HCW received 2 doses of BNT162b2 or mRNA-1273. We included confirmed cases among HCWs from 9 December 2020 to 23 February 2021. Weekly SARS-CoV-2 rates per 100,000 person-days and by time from first injection (1-14 and ≥15 days) were compared with surrounding community rates. Viral genomes were sequenced. RESULTS: SARS-CoV-2 cases occurred in 1.4% (96/7109) of HCWs given at least a first dose and 0.3% (17/5913) of HCWs given both vaccine doses. Adjusted rate ratios (95% confidence intervals) were 0.73 (.53-1.00) 1-14 days and 0.18 (.10-.32) ≥15 days from first dose. HCW ≥15 days from initial dose compared to 1-14 days were more often older (46 vs 38 years, P = .007), Latinx (10% vs 8%, P = .03), and asymptomatic (48% vs 11%, P = .0002). SARS-CoV-2 rates among HCWs fell below the surrounding community, an 18% vs 11% weekly decrease, respectively (P = .14). Comparison of 50 genomes from post-first dose cases did not indicate selection pressure toward known spike antibody escape mutations. CONCLUSIONS: Our results indicate an early positive impact of vaccines on SARS-CoV-2 case rates. Post-vaccination isolates did not show unusual genetic diversity or selection for mutations of concern.

[SARS-CoV-2-associated deaths in adult persons up to 50 years of age]. / SARS-CoV-2-assoziierte Todesfälle von erwachsenen Personen bis 50 Jahre: Eine retrospektive Auswertung der COVID-19-assoziierten Todesfälle im Jahr 2020 im Institut für Rechtsmedizin Hamburg, Deutschland.

INTRODUCTION: Several evaluations of deaths in persons of advanced age associated with SARS-CoV­2 can be found in the international literature. The aim of this work was the evaluation of deaths associated with SARS-CoV­2 of persons of younger or middle age (up to 50 years) at the Institute of Legal Medicine in Hamburg, Germany, with presentation of frequency, comorbidities and disease courses. MATERIAL AND METHODS: A total of 735 SARS-CoV-2-associated cases of decedents with registered addresses in Hamburg were evaluated in 2020 at the Institute of Legal Medicine in Hamburg, Germany, using various examination methods. The selection and performance of the respective methods was based on the consent given by the relatives. In addition, more autopsies of decedents with a registered address outside Hamburg and positive SARS-CoV­2 detection were performed. RESULTS AND CONCLUSION: Of the 735 decedents 9 with a registered Hamburg address and 3 of the deaths studied with an external registered address (n = 12; 7 men and 5 women) were aged 50 years or younger, with an average age of 39.8 years. Essentially, there were cardiovascular, neurological, and malignant pre-existing diseases, as well as obesity. The SARS-CoV­2 was detected post-mortem for the first time in two cases; these were found to have a virus-independent cause of death. Of the individuals 7 died from COVID-19 pneumonia, 3 individuals from the consequences of the necessary intensive medical treatment.Several studies have demonstrated an association between obesity and severe SARS-CoV-2-related disease progression, particularly in younger patients and this was confirmed in the legal medicine study population.

Rationale and Criteria for a COVID-19 Model Framework.

Complex systems are inherently multilevel and multiscale systems. The infectious disease system is considered a complex system resulting from the interaction between three sub-systems (host, pathogen, and environment) organized into a hierarchical structure, ranging from the cellular to the macro-ecosystem level, with multiscales. Therefore, to describe infectious disease phenomena that change through time and space and at different scales, we built a model framework where infectious disease must be considered the set of biological responses of human hosts to pathogens, with biological pathways shared with other pathologies in an ecological interaction context. In this paper, we aimed to design a framework for building a disease model for COVID-19 based on current literature evidence. The model was set up by identifying the molecular pathophysiology related to the COVID-19 phenotypes, collecting the mechanistic knowledge scattered across scientific literature and bioinformatic databases, and integrating it using a logical/conceptual model systems biology. The model framework building process began from the results of a domain-based literature review regarding a multiomics approach to COVID-19. This evidence allowed us to define a framework of COVID-19 conceptual model and to report all concepts in a multilevel and multiscale structure. The same interdisciplinary working groups that carried out the scoping review were involved. The conclusive result is a conceptual method to design multiscale models of infectious diseases. The methodology, applied in this paper, is a set of partially ordered research and development activities that result in a COVID-19 multiscale model.

[COVID-19 in Schleswig-Holstein: infection epidemiological evaluations from March to September 2020]. / COVID-19 in Schleswig-Holstein: Infektionsepidemiologische Auswertungen von März bis September 2020.

The COVID-19 pandemic poses major challenges for the German notification system in public infection control. For the federal state of Schleswig-Holstein evaluations, the state reporting office supports the public health departments by providing daily and weekly evaluations and supports the transmission of notification data to the Robert Koch Institute according to the Infection Protection Act.In the present report of the state notification office of Schleswig-Holstein, the SARS-CoV­2 reporting data for the period from March to September 2020 are evaluated. Based on the development of the infection numbers, this period was divided into two phases of similar size: March to May and June to September. A total of 4898 infection cases were reported. Upon comparison of the phases, there were particularly marked differences in hospitalization and mortality, age, and countries of infection site. In the first phase, elderly persons were particularly affected by high rates of hospitalization and mortality. In the second phase, the average age and hospitalization and mortality rates were significantly lower, and a particularly large proportion were associated with international travel activity. The evaluation of the outbreak documentation revealed a particular focus in private household settings. This article describes the epidemic situation in a low-incidence state within the Federal Republic of Germany.

Immunotherapy may protect cancer patients from SARS-CoV-2 infection: a single-center retrospective analysis.

Coronavirus disease 2019 (COVID-19) global pandemic has created unique challenges to healthcare systems throughout the world. Ensuring subjects' safety is mandatory especially in oncology, in consideration of cancer patients' particular frailty. We examined the proportion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) IgM and/or IgG positive subjects in three different groups from Istituto Nazionale Tumori - IRCCS "Fondazione G. Pascale" in Naples (Campania region, Italy): cancer patients treated with Innovative Immunotherapy (Immune Checkpoint Inhibitors, ICIs), cancer patients undergoing standard Chemotherapies (CHTs) and healthcare providers. 9 out of 287 (3.1%) ICIs patients resulted positive, with a significant lower percentage in respect to CHTs patients (39 positive subjects out of 598, 6.5%) (p = 0.04). There was no statistically significant difference between ICIs cohort and healthcare providers, 48 out of 1050 resulting positive (4.6%). Performing a Propensity Score Matching based on gender and tumor stage, the effect of treatment on seropositivity was analyzed through a regression logistic model and the ICIs treatment resulted to be the only protective factor significantly (p = 0.03) associated with positivity (odds ratio-OR: 0.41; 95% confidence interval-CI 0.18-0.91). According to these preliminary data, ICIs would appear to be a protective factor against the onset of COVID-19 infection.