Exploiting Modeling Studies for Evaluating the Potential Antiviral Activities of some Clinically Approved Drugs and Herbal Materials against SARS-CoV-2: Theoretical Studies toward Hindering the Virus and Blocking the Human Cellular Receptor

This research theoretically modeled the binding interaction of the Sars-Cov-2 (Spike protein) utilizing molecular docking with some potential repurposed antiviral medications and two botanical products (Curcumin and Quercetin). Molecular docking between the drugs and the Sars-Cov-2 proteins reflecting the pure electrostatic forces and H-bond formation is complemented with the DFT results that shed light on the electronic nature of the interactions. Moreover, DFT computations provide invaluable information about the drug reactivity indices calculated from the energies of the frontier orbitals. The DFT results indicate intermolecular electron donor-acceptor interaction besides the H-bond formation. Most of the considered medication molecules act as electron-sink candidates except EIDD-2801 (molnupiravir), the electron donor. The theoretical results show the high possibility of blocking the human cellular entry against Sare-Cov-2 via strong interaction of the drugs with its peptide sequence (β6) measured by the high binding energy of docking or weakening its activity due to the electronic donor-acceptor interactions indicated by reactivity indices computed from the frontier molecular orbitals. © 2023 Taylor & Francis Group, LLC.

Immunology of Aging: the Birth of Inflammaging.

The inflammaging concept was introduced in 2000 by Prof. Franceschi. This was an evolutionary or rather a revolutionary conceptualization of the immune changes in response to a lifelong stress. This conceptualization permitted to consider the lifelong proinflammatory process as an adaptation which could eventually lead to either beneficial or detrimental consequences. This dichotomy is influenced by both the genetics and the environment. Depending on which way prevails in an individual, the outcome may be healthy longevity or pathological aging burdened with aging-related diseases. The concept of inflammaging has also revealed the complex, systemic nature of aging. Thus, this conceptualization opens the way to consider age-related processes in their complexity, meaning that not only the process but also all counter-processes should be considered. It has also opened the way to add new concepts to the original one, leading to better understanding of the nature of inflammaging and of aging itself. Finally, it showed the way towards potential multimodal interventions involving a holistic approach to optimize the aging process towards a healthy longevity.

Developing an analytical framework for estimating food security indicators in the United Arab Emirates: A review.

Rapid population growth, climate change, limited natural resources, and the COVID-19 pandemic contribute to increased global hunger, necessitating intensive efforts to ensure food security and nutrition (FSN). Previous FSN approaches covered some dimensions, but not all, resulting in significant gaps in food security indicators. The Gulf Cooperation Council (GCC) and the Middle East and North Africa (MENA) regions have received less attention in food security studies, thus far necessitating considerable effort to develop an appropriate analytical framework. This study reviewed articles and international reports of FSN indicators, drivers and policies, methods, and models and extracted the challenges and gaps from the global and UAE contexts. The UAE and the world have gaps in FSN drivers, indicators, and methods, necessitating potential solutions to meet future challenges such as rapid population growth, pandemics, and limited natural resources. As a result, we created a newly developed analytical framework that addresses the shortcomings of previous approaches such as sustainable food systems developed by FAO and the Global Food Security Index (GFSI) and covers all aspects of food security. Gaps in knowledge in FSN drivers and policies, indicators, big data, methods, and models were considered in the developed framework, which has specific advantages. The novel developed framework addresses all food security dimensions (access, availability, stability, and utilization), ensuring poverty reduction, food security, and nutrition security while outperforming previous approaches (i.e., FAO and GFSI). The developed framework could be used successfully not only in the UAE and MENA, but also, globally, helping to solve food insecurity and malnutrition for future generations. The scientific community and policymakers should disseminate such solutions to address global food insecurity and ensure nutrition for future generations in the face of rapid population growth, limited natural resources, climate change, and spreading pandemics. Supplementary Information: The online version contains supplementary material available at 10.1007/s10668-023-03032-3.

Forecasting energy consumption demand of customers in smart grid using Temporal Fusion Transformer (TFT)

Energy consumption prediction has always remained a concern for researchers because of the rapid growth of the human population and customers joining smart grids network for smart home facilities. Recently, the spread of COVID-19 has dramatically increased energy consumption in the residential sector. Hence, it is essential to produce energy per the residential customers' requirements, improve economic efficiency, and reduce production costs. The previously published papers in the literature have considered the overall energy consumption prediction, making it difficult for production companies to produce energy per customers' future demand. Using the proposed study, production companies can accurately have energy per their customers' needs by forecasting future energy consumption demands. Scientists and researchers are trying to minimize energy consumption by applying different optimization and prediction techniques;hence this study proposed a daily, weekly, and monthly energy consumption prediction model using Temporal Fusion Transformer (TFT). This study relies on a TFT model for energy forecasting, which considers both primary and valuable data sources and batch training techniques. The model's performance has been related to the Long Short-Term Memory (LSTM), LSTM interpretable, and Temporal Convolutional Network (TCN) models. The model's performance has remained better than the other algorithms, with mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE) of 4.09, 2.02, and 1.50. Further, the overall symmetric mean absolute percentage error (sMAPE) of LSTM, LSTM interpretable, TCN, and proposed TFT remained at 29.78%, 31.10%, 36.42%, and 26.46%, respectively. The sMAPE of the TFT has proved that the model has performed better than the other deep learning models. © 2023 The Author(s)

Importance of medical training for public during outbreaks

The aim of this work is to clarify the necessity of medical training for public during COVID19 time. Reviewing the related published articles, online newspapers, and related associations websites. Scientific literature showed that trained public deal with outbreaks to save themselves and cooperate with the governmental agencies to tackle challenges during outbreaks. Medical training about public health issues is essential. It helps in overcoming challenges during outbreaks and protects public health to secure stability.

Prediction System for Diagnosis and Detection of Coronavirus Disease-2019 (COVID-19): A Fuzzy-Soft Expert System

In early December 2019, a new virus named "2019 novel coronavirus (2019-nCoV)" appeared in Wuhan, China. The disease quickly spread worldwide, resulting in the COVID-19 pandemic. In the currentwork, we will propose a novel fuzzy softmodal (i.e., fuzzy-soft expert system) for early detection of COVID-19. Themain construction of the fuzzy-soft expert systemconsists of five portions. The exploratory study includes sixty patients (i.e., fortymales and twenty females) with symptoms similar to COVID-19 in (Nanjing Chest Hospital, Department of Respiratory, China). The proposed fuzzy-soft expert systemdepended on five symptoms of COVID-19 (i.e., shortness of breath, sore throat, cough, fever, and age).We will use the algorithm proposed by Kong et al. to detect these patients who may suffer from COVID-19. In this way, the present system is beneficial to help the physician decide if there is any patient who has COVID-19 or not. Finally, we present the comparison between the present system and the fuzzy expert system. © 2023 Tech Science Press. All rights reserved.

Evaluation of immunogenicity and reactogenicity of COVID-19 vaccines in pregnant women.

OBJECTIVE: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in pregnancy is associated with increased risk of adverse maternal and perinatal outcomes. Vaccines are highly effective at preventing severe coronavirus disease 2019 (COVID-19), but there are limited data on COVID-19 vaccines in pregnancy. This study aimed to investigate the reactogenicity and immunogenicity of COVID-19 vaccines in pregnant women when administered according to the 12-week-interval dosing schedule recommended in the UK. METHODS: This was a cohort study of pregnant women receiving COVID-19 vaccination between April and September 2021. The outcomes were immunogenicity and reactogenicity after COVID-19 vaccination. Pregnant women were recruited by phone, e-mail and/or text and were vaccinated according to vaccine availability at their local vaccination center. For immunogenicity assessment, blood samples were taken at specific timepoints after each dose to evaluate nucleocapsid protein (N) and spike protein (S) antibody titers. The comparator group comprised non-pregnant female healthcare workers in the same age group who were vaccinated as part of the national immunization program in a contemporaneous longitudinal cohort study. Longitudinal changes in serum antibody titers and association with pregnancy status were assessed using a two-step regression approach. Reactogenicity assessment in pregnant women was undertaken using an online questionnaire. The comparator group comprised non-pregnant women aged 18-49 years who had received two vaccine doses in primary care. The association of pregnancy status with reactogenicity was assessed using logistic regression analysis. RESULTS: Overall, 67 pregnant women, of whom 66 had received a mRNA vaccine, and 79 non-pregnant women, of whom 50 had received a mRNA vaccine, were included in the immunogenicity study. Most (61.2%) pregnant women received their first vaccine dose in the third trimester, while 3.0% received it in the first trimester and 35.8% in the second trimester. SARS-CoV-2 S-antibody geometric mean concentrations after mRNA vaccination were not significantly different at 2-6 weeks after the first dose but were significantly lower at 2-6 weeks after the second dose in infection-naïve pregnant compared with non-pregnant women. In pregnant women, prior infection was associated with higher antibody levels at 2-6 weeks after the second vaccine dose. Reactogenicity analysis included 108 pregnant women and 116 non-pregnant women. After the first dose, tiredness and chills were reported less commonly in pregnant compared with non-pregnant women (P = 0.043 and P = 0.029, respectively). After the second dose, feeling generally unwell was reported less commonly (P = 0.046) in pregnant compared with non-pregnant women. CONCLUSIONS: Using an extended 12-week interval between vaccine doses, antibody responses after two doses of mRNA COVID-19 vaccine were found to be lower in pregnant compared with non-pregnant women. Strong antibody responses were achieved after one dose in previously infected women, regardless of pregnancy status. Pregnant women reported fewer adverse events after both the first and second dose of vaccine. These findings should now be addressed in larger controlled studies. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

How the Cryptocurrencies React to Covid-19 Pandemic? An Empirical Study Using DCC GARCH Model (2019–2021)

The paper aims to examine the dynamic conditional correlation between three major cryptocurrencies: Bitcoin, Litecoin, and Ethereum, during the Covid-19 pandemic. Our sample includes two panels: before/during Covid-19 covering the periods of 01/01/2019 to 12/31/2019 and from 01/01/2020 to 01/03/2021 using hourly data and the DCC GARCH model. The empirical results found that the Covid-19 pandemic positively impacts the cryptocurrencies prices starting from the second semester of 2020. Furthermore, these digital currencies became more vulnerable and showed a high level of volatility, especially Ethereum and Litecoin. Besides, we concluded that there was no significance on the short-run volatility effect during the Covid-19 period, which means the continuity of persistence in the long term. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Colchicine anti-inflammatory therapy for non-intensive care unit hospitalized COVID-19 patients: results from a pilot open-label, randomized controlled clinical trial.

Systemic inflammation is a hallmark of severe coronavirus disease-19 (COVID-19). Anti-inflammatory therapy is considered crucial to modulate the hyperinflammatory response (cytokine storm) in hospitalized COVID-19 patients. There is currently no specific, conclusively proven, cost-efficient, and worldwide available anti-inflammatory therapy available to treat COVID-19 patients with cytokine storm. The present study aimed to investigate the treatment benefit of oral colchicine for hospitalized COVID-19 patients with suspected cytokine storm. Colchicine is an approved drug and possesses multiple anti-inflammatory mechanisms. This was a pilot, open-label randomized controlled clinical trial comparing standard of care (SOC) plus oral colchicine (colchicine arm) vs. SOC alone (control arm) in non-ICU hospitalized COVID-19 patients with suspected cytokine storm. Colchicine treatment was initiated within first 48 hours of admission delivered at 1.5 mg loading dose, followed by 0.5 mg b.i.d. for next 6 days and 0.5 mg q.d. for the second week. A total of 96 patients were randomly allocated to the colchicine (n=48) and control groups (n=48). Both colchicine and control group patients experienced similar clinical outcomes by day 14 of hospitalization. Treatment outcome by day 14 in colchicine vs control arm: recovered and discharged alive: 36 (75.0%) vs. 37 (77.1%), remain admitted after 14-days: 4 (8.3%) vs. 5 (10.4%), ICU transferred: 4 (8.3%) vs. 3 (6.3%), and mortality: 4 (8.3%) vs. 3 (6.3%). The speed of improvement of COVID-19 acute symptoms including shortness of breath, fever, cough, the need of supplementary oxygen, and oxygen saturation level, was almost identical in the two groups. Length of hospitalization was on average 1.5 day shorter in the colchicine group. There was no evidence for a difference between the two groups in the follow-up serum levels of inflammatory biomarkers including C-reactive protein (CRP), D-dimer, lactate dehydrogenase (LDH), ferritin, interleukin-6 (IL-6), high-sensitivity troponin T (hs-TnT) and N-terminal pro b-type natriuretic peptide (NT pro-BNP). According to the results of our study, oral colchicine does not appear to show clinical benefits in non-ICU hospitalized COVID-19 patients with suspected cytokine storm. It is possible that the anti-inflammatory pathways of colchicine are not crucially involved in the pathogenesis of COVID-19.

Forecasting the Use of Decontamination Robots in the COVID Era

This paper explores the introduction and possible adoption of robots that are designed to clean or decontaminate public spaces, such as airports, lobbies, or medical facilities. Such robots are capable of performing autonomous or semiautonomous cleaning functions. They offer the advantage of cleaning areas that may contain harmful biological agents, like the Sars-Cov-2 virus (also known as COVID-19), without exposing human cleaning crews to the risk of infection. Such robots offer a number of additional advantages, including the ability to work 24 hours a day, 7 days a week, to decontaminate more precisely than human cleaning crews, and a variety of operational characteristics that may make them more efficient and cost-effective than traditional cleaning methods. The initial part of the paper involves a case study of a company called Build with Robots, which is in the process of commercializing robots to perform these types of functions. An overview is provided of the general technology involved with these types of robots, as well as an analysis of the industry, and discussion of commercialization prospects. The paper then conducts a technology forecast to determine overall trends for the development and adoption of this technology. The authors use a bibliometric approach and literature review to gather data sets and perform S-curve analysis. This forecast is then used to provide overall conclusions and recommendations about the current state of this technology and its commercialization prospects. © 2022 PICMET.

A COVID-19 Clinical Management Committee to Standardize Care in a 2-Hospital System

Objective: The COVID-19 pandemic has been a challenge for hospital medical staffs worldwide due to high volumes of patients acutely ill with novel syndromes and prevailing uncertainty regarding optimum supportive and therapeutic interventions. Additionally, the response to this crisis was driven by a plethora of nontraditional information sources, such as email chains, websites, non-peer-reviewed preprints, and press releases. Care patterns became idiosyncratic and often incorporated unproven interventions driven by these nontraditional information sources. This report evaluates the efforts of a health system to create and empower a multidisciplinary committee to develop, implement, and monitor evidence-based, standardized protocols for patients with COVID-19. Method(s): This report describes the composition of the committee, its scope, and its important interactions with the health system pharmacy and therapeutics committee, research teams, and other work groups planning other aspects of COVID-19 management. It illustrates how the committee was used to demonstrate for trainees the process and value of critically examining evidence, even in a chaotic environment. Result(s): Data show successful interventions in reducing excessive ordering of certain laboratory tests, reduction of nonrecommended therapies, and rapid uptake of evidence-based or guidelines-supported interventions. Conclusion(s): A multidisciplinary committee dedicated solely to planning, implementing, and monitoring standard approaches that eventually became evidence-based decision-making led to an improved focus on treatment options and outcomes for COVID-19 patients. Data presented illustrate the attainable success of a committee that is both adaptable and suitable for similar emergencies in the future. Copyright © 2022 Turner White Communications Inc.. All rights reserved.

Evaluation of immunogenicity and reactogenicity of COVID‐19 vaccines in pregnant women

Objective SARS‐CoV‐2 infection in pregnancy is associated with increased risk of adverse maternal and perinatal outcomes including preterm birth, pre‐eclampsia, stillbirth, admission to intensive care unit and death. Vaccines are highly effective in preventing severe COVID‐19, however there are limited data on COVID‐19 vaccines in pregnancy. This study aimed to investigate the reactogenicity and immunogenicity of the COVID‐19 vaccine in pregnant women when given using the UK's extended 12‐week interval schedule. Methods This was a cohort study of pregnant women receiving COVID‐19 vaccination between January and September 2021. The primary outcome was immunogenicity and reactogenicity after COVID‐19 vaccination in pregnant women. Pregnant women were recruited by phone, email and text. They were vaccinated according to vaccine availability at their local vaccination hub and blood samples were taken at specific time points after each vaccine for nucleoprotein (N) and spike protein (S) antibodies. The comparator group comprised non‐pregnant female healthcare workers in the same age‐group who were vaccinated as part of the national immunization programme in a contemporaneous longitudinal cohort study. Association of variables with antibody levels was assessed using linear regression analysis after log‐transforming antibody levels. Reactogenicity assessment in pregnant women was undertaken using an online questionnaire. The comparator group comprised non‐pregnant women aged 18‐49 years who had received two vaccine doses in primary care. The association of pregnancy status with reactogenicity was assessed using logistic regression analysis. Results Overall 67 pregnant women including 66 who had received an mRNA vaccine and 50 non‐pregnant women were included in the immunogenicity study. Most pregnant women (61.2%) received the vaccine in the third trimester, while 3.0% received it in their first and 35.8% in the second trimesters. SARS‐CoV‐2 S‐antibody GMCs after mRNA vaccination were not significantly different at 2‐6 weeks after the first dose but were significantly lower at 2‐6 weeks after the second dose of vaccine in infection‐naïve pregnant compared to non‐pregnant women. In pregnant women, prior infection was associated with higher antibody levels compared to infection‐naïve women at 2‐6 weeks after both vaccine doses. The reactogenicity analysis included 108 pregnant women and 116 non‐pregnant women. After the first dose, tiredness and chills were reported less commonly in pregnant women when compared to non‐pregnant women (P=0.043 and P=0.029, respectively). After the second dose feeling generally unwell was reported less commonly (P=0.046) in pregnant women when compared to non‐pregnant women. Conclusions Using an extended 12‐week interval between vaccine doses, antibody responses after 2 doses of mRNA vaccine were found to be lower in pregnant women than in non‐pregnant women. However, Antibody responses to mRNA vaccination were lower in pregnant women when compared to non‐pregnant women. High antibody responses were achieved after one dose in previously infected women, regardless of pregnancy status. Pregnant women had fewer adverse effects after both the first and the second dose of the vaccine. These findings should now be addressed in larger controlled studies. This article is protected by copyright. All rights reserved.

Triggers and Tweets: Implicit Aspect-Based Sentiment and Emotion Analysis of Community Chatter Relevant to Education Post-COVID-19

This research proposes a well-being analytical framework using social media chatter data. The proposed framework infers analytics and provides insights into the public’s well-being relevant to education throughout and post the COVID-19 pandemic through a comprehensive Emotion and Aspect-based Sentiment Analysis (ABSA). Moreover, this research aims to examine the variability in emotions of students, parents, and faculty toward the e-learning process over time and across different locations. The proposed framework curates Twitter chatter data relevant to the education sector, identifies tweets with the sentiment, and then identifies the exact emotion and emotional triggers associated with those feelings through implicit ABSA. The produced analytics are then factored by location and time to provide more comprehensive insights that aim to assist the decision-makers and personnel in the educational sector enhance and adapt the educational process during and following the pandemic and looking toward the future. The experimental results for emotion classification show that the Linear Support Vector Classifier (SVC) outperformed other classifiers in terms of overall accuracy, precision, recall, and F-measure of 91%. Moreover, the Logistic Regression classifier outperformed all other classifiers in terms of overall accuracy, recall, an F-measure of 81%, and precision of 83% for aspect classification. In online experiments using UAE COVID-19 education-related data, the analytics show high relevance with the public concerns around the education process that were reported during the experiment’s timeframe. © 2022 by the authors.

Effect of the COVID-19 Pandemic on Antenatal Care

Objective: To assess how the antenatal population of a hospital was affected by the COVID-19 Pandemic. Study Design: Prospective longitudinal study. Place and Duration of Study: Antenatal Clinic of Government Hospital, Rawalpindi Pakistan, for the month of August 2020. Methodology: The population in the antenatal clinic of a hospital were given a questionnaire with simple directed questions after consent. Results: All (150, 100%) of the antenatal population received their COVID-19 pandemic information from television. Most 147 (98%) did not feel embarrassed if they contracted COVID-19 infection, and 147 (98%) took precautions against it. The majority, 146 (97%) of women, had an antenatal check-up. Out of the total, 126 (84%) had a private check-up, but only 36 (24%) had more private visits than prior pregnancies. A significant number, 56 (37%), had to spend more than in prior pregnancies, but only 28 (18.6%) had fewer antenatal visits than before. Most 141 (94%) of women wanted a higher frequency of antenatal visits than the recommended 08 visits by the WHO. Conclusion: The COVID-19 pandemic did not affect antenatal care because of a well-established private health care system. The patients in prior pregnancies were already using the private sector. © 2022, Army Medical College. All rights reserved.

Maternal and perinatal outcomes of SARS-CoV-2 infection in unvaccinated pregnancies during Delta and Omicron waves.

OBJECTIVE: There is little evidence related to the effects of the Omicron severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant on pregnancy outcomes, particularly in unvaccinated women. This study aimed to compare pregnancy outcomes of unvaccinated women infected with SARS-CoV-2 during the pre-Delta, Delta and Omicron waves. METHODS: This was a retrospective cohort study conducted at two tertiary care facilities: Sancaktepe Training and Research Hospital, Istanbul, Turkey, and St George's University Hospitals NHS Foundation Trust, London, UK. Included were women who tested positive for SARS-CoV-2 by real-time reverse-transcription polymerase chain reaction (RT-PCR) during pregnancy, between 1 April 2020 and 14 February 2022. The cohort was divided into three periods according to the date of their positive RT-PCR test: (i) pre-Delta (1 April 2020 to 8 June 2021 in Turkey, and 1 April 2020 to 31 July 2021 in the UK), (ii) Delta (9 June 2021 to 27 December 2021 in Turkey, and 1 August 2021 to 27 December 2021 in the UK) and (iii) Omicron (after 27 December 2021 in both Turkey and the UK). Baseline data collected included maternal age, parity, body mass index, gestational age at diagnosis and comorbidities. The primary outcome was the need for oxygen supplementation, classified as oxygen support via nasal cannula or breather mask, non-invasive mechanical ventilation with continuous positive airway pressure (CPAP) or high-flow oxygen, mechanical ventilation with intubation, or extracorporeal membrane oxygenation (ECMO). Inferences were made after balancing of confounders, using an evolutionary search algorithm. Selected confounders were maternal age, body mass index and gestational age at diagnosis of infection. RESULTS: During the study period, 1286 unvaccinated pregnant women with RT-PCR-proven SARS-CoV-2 infection were identified, comprising 870 cases during the pre-Delta period, 339 during the Delta wave and 77 during the Omicron wave. In the confounder-balanced cohort, infection during the Delta wave vs during the pre-Delta period was associated with increased need for nasal oxygen support (risk ratio (RR), 2.53 (95% CI, 1.75-3.65); P < 0.001), CPAP or high-flow oxygen (RR, 2.50 (95% CI, 1.37-4.56); P = 0.002), mechanical ventilation (RR, 4.20 (95% CI, 1.60-11.0); P = 0.003) and ECMO (RR, 11.0 (95% CI, 1.43-84.7); P = 0.021). The maternal mortality rate was 3.6-fold higher during the Delta wave compared to the pre-Delta period (5.3% vs 1.5%, P = 0.010). Infection during the Omicron wave was associated with a similar need for nasal oxygen support (RR, 0.62 (95% CI, 0.25-1.55); P = 0.251), CPAP or high-flow oxygen (RR, 1.07 (95% CI, 0.36-3.12); P = 0.906) and mechanical ventilation (RR, 0.44 (95% CI, 0.06-3.45); P = 0.438) with that in the pre-Delta period. The maternal mortality rate was similar during the Omicron wave and the pre-Delta period (1.3% vs 1.3%, P = 0.999). The need for nasal oxygen support during the Omicron wave was significantly lower compared to the Delta wave (RR, 0.26 (95% CI, 0.11-0.64); P = 0.003). Perinatal outcomes were available for a subset of the confounder-balanced cohort. Preterm birth before 34 weeks' gestation was significantly increased during the Delta wave compared with the pre-Delta period (15.4% vs 4.9%, P < 0.001). CONCLUSIONS: Among unvaccinated pregnant women, SARS-CoV-2 infection during the Delta wave, in comparison to the pre-Delta period, was associated with increased requirement for oxygen support (including ECMO) and higher maternal mortality. Disease severity and pregnancy complications were similar between the Omicron wave and pre-Delta period. SARS-CoV-2 infection of unvaccinated pregnant women carries considerable risks of morbidity and mortality regardless of variant, and vaccination remains key. Miscommunication of the risks of Omicron infection may impact adversely vaccination uptake among pregnant women, who are at increased risk of complications related to SARS-CoV-2. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.