Effectiveness of Vaccination and Previous Infection Against Omicron Infection and Severe Outcomes in Children Under 12 Years of Age (preprint)

Background: Data on the protection conferred by vaccination and previous infection against omicron infection and severe outcomes in children can inform prevention strategies. Methods: We obtained vaccination records and clinical outcomes for 1,368,721 North Carolina residents 11 years of age or younger from October 29, 2021 to January 6, 2023. We used Cox regression to estimate the time varying effects of primary and booster vaccination and previous infection on the risks of omicron infection, hospitalization, and death. Results: For children 5 to 11 years of age, the effectiveness of primary vaccination against infection was 59.9% (95% confidence interval [CI], 58.5 to 61.2), 33.7% (95% CI, 32.6 to 34.8), and 14.9% (95% CI, 12.3 to 17.5) at 1, 4 and 10 months after the first dose; the effectiveness of a monovalent or bivalent booster dose after 1 month was 24.4% (95% CI, 14.4 to 33.2) or 76.7% (95% CI, 45.7 to 90.0); and the effectiveness of omicron infection against reinfection was 79.9% (95% CI, 78.8 to 80.9) and 53.9% (95% CI, 52.3 to 55.5) after 3 and 6 months, respectively. For children 0 4 years of age, the effectiveness of primary vaccination against infection was 63.8% (95% CI, 57.0 to 69.5) and 58.1% (95% CI, 48.3 to 66.1) at 2 and 5 months after the first dose, and the effectiveness of omicron infection against reinfection was 77.3% (95% CI, 75.9 to 78.6) and 64.7% (95% CI, 63.3 to 66.1) after 3 and 6 months, respectively. For both age groups, vaccination and previous infection had better effectiveness against hospitalization and death than against infection. Conclusions: Vaccination was effective against omicron infection and severe outcomes in children under the age of 12 years, although the effectiveness decreased over time. Bivalent boosters were more effective than monovalent boosters. Immunity acquired via omicron infection was very high and waned gradually over time.

Reliably Assessing Duration of Protection for COVID-19 Vaccines (preprint)

Decision-making about booster dosing for COVID-19 vaccine recipients hinges on reliable methods for evaluating the longevity of vaccine protection. We show that modeling of protection as a piecewise linear function of time since vaccination for the log hazard ratio of the vaccine effect provides more reliable estimates of vaccine effectiveness at the end of an observation period and also more reliably detects plateaus in protective effectiveness as compared with the traditional method of estimating a constant vaccine effect over each time period. This approach will be useful for analyzing data pertaining to COVID-19 vaccines and other vaccines where rapid and reliable understanding of vaccine effectiveness over time is desired.

Effectiveness of Covid-19 Vaccines in the United States Over 9 Months: Surveillance Data from the State of North Carolina (preprint)

Background: The duration of protection afforded by Covid19 vaccines in the United States is unclear. Whether the recent increase of breakthrough infections was caused by waning immunity to the primary vaccination or by emergence of new variants that are more highly transmissible is also unknown. Methods: We extracted data on vaccination histories and clinical outcomes (Covid19, hospitalization, death) for the period from December 13, 2020 through September 8, 2021 by linking data from the North Carolina COVID19 Surveillance System and COVID19 Vaccine Management System covering ~10.6 million residents statewide. We used the Kaplan-Meier method to estimate the effectiveness of the BNT162b2 (Pfizer), mRNA-1273 (Moderna), and Ad26.COV2.S (Janssen) vaccines in reducing the incidence of Covid19 over successive post-vaccination time periods, producing separate estimates for individuals vaccinated during different calendar periods. In addition, we used Cox regression with time-dependent vaccination status and time-varying hazard ratios to estimate the effectiveness of the three vaccines in reducing the hazard rates or current risks of Covid19, hospitalization, and death, as a function of time elapsed since the first dose. Results: For the Pfizer two-dose regimen, vaccine effectiveness in reducing the current risk of Covid-19 ramps to a peak level of 94.9% (95% confidence interval [CI], 94.5 to 95.2) at 2 months (post the first dose) and drops to 70.1% (95% CI, 68.9 to 71.2) after 7 months; effectiveness in reducing the current risk of hospitalization ramps to a peak level of 96.4% (95% CI, 94.7 to 97.5) at 2 months and remains at 87.7% (95% CI, 84.3 to 90.4) at 7 months; effectiveness in reducing the current risk of death ramps to 95.9% (95% CI, 92.9 to 97.6) at 2 months and is maintained at 88.4% (95% CI, 83.0 to 92.1) at 7 months. For the Moderna two-dose regimen, vaccine effectiveness in reducing the current risk of Covid-19 ramps to a peak level of 96.0% (95% CI, 95.6 to 96.4) at 2 months and drops to 81.9% (95% CI, 81.0 to 82.7) after 7 months; effectiveness in reducing the current risk of hospitalization ramps to a peak level of 97.5% (95% CI, 96.3 to 98.3) at 2 months and remains at 92.3% (95% CI, 89.7 to 94.3) at 7 months; effectiveness in reducing the current risk of death ramps to 96.0% (95% CI, 91.9 to 98.0) at 3 months and remains at 93.7% (95% CI, 90.2 to 95.9) at 7 months. For the Janssen one-dose regimen, effectiveness in reducing the current risk of Covid-19 ramps to a peak level of 79.0% (95% CI, 77.1 to 80.7) at 1 month and drops to 64.3% (95% CI, 62.3 to 66.1) after 5 months; effectiveness in reducing the current risk of hospitalization ramps to a peak level of 89.8% (95% CI, 78.8 to 95.1) at 2 months and stays above 80% through 5 months; effectiveness in reducing the current risk of death ramps to 89.4% (95% CI, 52.3 to 97.6) at 3 months and stays above 80% through 5 months. For all three vaccines, the ramping and waning patterns are similar for individuals who were vaccinated at different dates, and across various demographic subgroups (age, sex, race/ethnicity, geographic region, county-level vaccination rate). Conclusions: The two mRNA vaccines are remarkably effective and durable in reducing the risks of hospitalization and death. The Janssen vaccine also offers a high level of protection against hospitalization and death. The Moderna vaccine is significantly more durable than the Pfizer vaccine in reducing the risk of Covid19. Waning vaccine effectiveness is caused primarily by declining immunity rather than emergence of new variants. It would be worthwhile to investigate the effectiveness of the Janssen vaccine as a two-dose regimen, with the second dose given approximately 1 month after the first dose.

Photosensitizers: A Membrane-Targeting Photosensitizer with Aggregation-Induced Emission Characteristics for Highly Efficient Photodynamic Combat of Human Coronaviruses (Small 30/2021)

Lianrong Wang, Engui Zhao, Sijie Chen and co-workers (article number 2101770) develop a novel membrane-targeting photosensitizer (DTTPB) with aggregation-induced emission characteristics for efficient photodynamic inactivation of human coronaviruses. DTTPB can bind to the envelope of human coronaviruses and sensitize the production of reactive oxygen species, which can effectively inactivate human coronaviruses upon white-light irradiation.

A Systematic Investigation of KB-Text Embedding Alignment at Scale (preprint)

Knowledge bases (KBs) and text often contain complementary knowledge: KBs store structured knowledge that can support long range reasoning, while text stores more comprehensive and timely knowledge in an unstructured way. Separately embedding the individual knowledge sources into vector spaces has demonstrated tremendous successes in encoding the respective knowledge, but how to jointly embed and reason with both knowledge sources to fully leverage the complementary information is still largely an open problem. We conduct a large-scale, systematic investigation of aligning KB and text embeddings for joint reasoning. We set up a novel evaluation framework with two evaluation tasks, few-shot link prediction and analogical reasoning, and evaluate an array of KB-text embedding alignment methods. We also demonstrate how such alignment can infuse textual information into KB embeddings for more accurate link prediction on emerging entities and events, using COVID-19 as a case study.

Evaluating Vaccine Efficacy Against SARS-CoV-2 Infection (preprint)

Although interim results from several large placebo-controlled phase 3 trials demonstrated high vaccine efficacy (VE) against symptomatic COVID-19, it is unknown how effective the vaccines are in preventing people from becoming asymptomatically infected and potentially spreading the virus unwittingly. It is more difficult to evaluate VE against SARS-CoV-2 infection than against symptomatic COVID-19 because infection is not observed directly but rather is known to occur between two antibody or RT-PCR tests. Additional challenges arise as community transmission changes over time and as participants are vaccinated on different dates because of staggered enrollment or crossover before the end of the study. Here, we provide valid and efficient statistical methods for estimating potentially waning VE against SARS-CoV-2 infection with blood or nasal samples under time-varying community transmission, staggered enrollment, and blinded or unblinded crossover. We demonstrate the usefulness of the proposed methods through numerical studies mimicking the BNT162b2 phase 3 trial and the Prevent COVID U study. In addition, we assess how crossover and the frequency of diagnostic tests affect the precision of VE estimates. SummaryWe show how to estimate potentially waning efficacy of COVID-19 vaccines against SARS-CoV-2 infection using blood or nasal samples collected periodically from clinical trials with staggered enrollment of participants and crossover of placebo recipients.

Sexual dimorphism and plasticity in wing shape in three Diptera (preprint)

The ability of powered flight in insects facilitated their great evolutionary success allowing them to occupy various ecological niches. Beyond this primary task, wings are often involved in various premating behaviors, such as the generation of courtship songs and the initiation of mating in flight. These specific functions imply special adaptations of wing morphology, as well as sex-specific wing morphologies. Although wing morphology has been extensively studied in Drosophila melanogaster, a comprehensive understa nding of sexual wing shape dimorphisms and developmental plasticity is missing for other Diptera. Therefore, we raised flies of the three Diptera species Drosophila melanogaster, Ceratitis capitata and Musca domestica at different environmental conditions and applied geometric morphometrics to analyze wing shape. Our data showed extensive interspecific differences in wing shape, as well as a clear sexual wing shape dimorphism in all three species. We revealed an impact of different rearing temperatures wing shape in all three species, which was mostly explained by plasticity in wing size in D. melanogaster. Rearing densities had significant effects on allometric wing shape in D. melanogaster, while no obvious effects were observed for the other two species. Additionally, we do not find evidence for sex-specific response to different rearing conditions in all three species. We determined species-specific and common trends in shape alterations, and we hypothesize developmental and functional implications of our data. Contribution to the Field StatementThe size and shape of organisms and organs must be tightly controlled during development to ensure proper functionality. However, morphological traits vary considerably in nature contributing to phenotypic diversity. Such variation can be the result of evolutionary adaptations as well as plasticity for example as reaction to changing environmental conditions during development. It is therefore a major aim in Biology to unravel the processes that control differences in adult morphology. Insect wings are excellent models to study how organ size and shape evolves because they facilitate basic tasks such as mating and feeding. Accordingly, a tremendous variety of wings sizes and shapes evolved in nature. Additionally, plasticity in wing morphology in response to different rearing conditions has been observed in many insects contributing to phenotypic diversity. In this work we applied Geometric Morphometrics to study wing shape in the three Diptera species: the Mediterranean fruit fly Ceratitis capitata, the Vinegar fly Drosophila melanogaster and the housefly Musca domestica. Flies were raised in different temperature and density regimes that allowed us to study the effects of these environmental factors on wing shape. Additionally, in accordance with different mating behaviors of these flies, we observed a clear sexual shape dimorphism in all three species. Since the three studied species represent serious pests and disease vectors, our findings may contribute to existing and future monitoring efforts.

Clinical feature analysis on death cases of the COVID-19

Objective: To analyze clinical characteristics in patients died of coronavirus disease 2019 (COVID-19), and provide experience for guiding clinical treatment and evaluating prognosis.

Whole genome identification of potential G-quadruplexes and analysis of the G-quadruplex binding domain for SARS-CoV-2 (preprint)

The Coronavirus Disease 2019 (COVID-19) pandemic caused by SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) quickly become a global public health emergency. G-quadruplex, one of the non-canonical secondary structures, has shown potential antiviral values. However, little is known about G-quadruplexes on the emerging SARS-CoV-2. Herein, we characterized the potential G-quadruplexes both in the positive and negative-sense viral stands. The identified potential G-quadruplexes exhibits similar features to the G-quadruplexes detected in the human transcriptome. Within some bat and pangolin related beta coronaviruses, the G-quartets rather than the loops are under heightened selective constraints. We also found that the SUD-like sequence is retained in the SARS-CoV-2 genome, while some other coronaviruses that can infect humans are depleted. Further analysis revealed that the SARS-CoV-2 SUD-like sequence is almost conserved among 16,466 SARS-CoV-2 samples. And the SARS-CoV-2 SUDcore-like dimer displayed similar electrostatic potential pattern to the SUD dimer. Considering the potential value of G-quadruplexes to serve as targets in antiviral strategy, we hope our fundamental research could provide new insights for the SARS-CoV-2 drug discovery.

Fast automated detection of COVID-19 from medical images using convolutional neural networks (preprint)

Coronavirus Disease 2019 (COVID-19) is a global pandemic that poses significant health risks. The sensitivity of diagnostic tests for COVID-19 is low due to irregularities in the handling of the specimens. We propose a deep learning framework that identifies COVID-19 from medical images as an effective auxiliary testing method to improve diagnostic sensitivity. We use pseudo-coloring methods and a platform for annotating X-ray and computed tomography (CT) images to train and evaluate the convolutional neural network (CNN). The CNN achieves a performance similar to that of experts and provides high scores for multiple statistical indices, with F1 scores above 96% and specificity over 99%. Heatmaps are used to visualize the salient features extracted by the CNN. The CNN-based regression provides strong correlations between the lesion areas in the images and five clinical indicators, improving the interpretation accuracy of the classification framework. The proposed method represents a potential computer-aided diagnosis method for COVID-19 in clinical practice.