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During the COVID-19 pandemic, pneumonia was the leading cause of respiratory failure and death. In addition to SARS-COV-2, it can be caused by several other bacterial and viral agents. Even today, variants of SARS-COV-2 are endemic and COVID-19 cases are common in many places. The symptoms of COVID-19 are highly diverse and robust, ranging from invisible to severe respiratory failure. Current detection methods for the disease are time-consuming and expensive with low accuracy and precision. To address such situations, we have designed a framework for COVID-19 and Pneumonia detection using multiple deep learning algorithms further accompanied by a deployment scheme. In this study, we have utilized four prominent deep learning models, which are VGG-19, ResNet-50, Inception V3 and Xception, on two separate datasets of CT scan and X-ray images (COVID/Non-COVID) to identify the best models for the detection of COVID-19. We achieved accuracies ranging from 86% to 99% depending on the model and dataset. To further validate our findings, we have applied the four distinct models on two more supplementary datasets of X-ray images of bacterial pneumonia and viral pneumonia. Additionally, we have implemented a flask app to visualize the outcome of our framework to show the identified COVID and Non-COVID images. The findings of this study will be helpful to develop an AI-driven automated tool for the cost effective and faster detection and better management of COVID-19 patients. [ABSTRACT FROM AUTHOR]

To control the SARS-CoV-2 pandemic, healthcare systems have focused on ramping up their capacity for epidemiological surveillance through viral whole genome sequencing. In this paper, we tested the performance of two protocols of SARS-CoV-2 nucleic acid enrichment, an amplicon enrichment using different versions of the ARTIC primer panel and a hybrid-capture method using KAPA RNA Hypercap. We focused on the challenge of the Omicron variant sequencing, the advantages of automated library preparation and the influence of the bioinformatic analysis in the final consensus sequence. All 94 samples were sequenced using Illumina iSeq 100 and analysed with two bioinformatic pipelines: a custom-made pipeline and an Illumina-owned pipeline. We were unsuccessful in sequencing six samples using the capture enrichment due to low reads. On the other hand, amplicon dropout and mispriming caused the loss of mutation G21987A and the erroneous addition of mutation T15521A respectively using amplicon enrichment. Overall, we found high sequence agreement regardless of method of enrichment, bioinformatic pipeline or the use of automation for library preparation in eight different SARS-CoV-2 variants. Automation and the use of a simple app for bioinformatic analysis can simplify the genotyping process, making it available for more diagnostic facilities and increasing global vigilance. [ABSTRACT FROM AUTHOR]

Background: Data on SARS-CoV-2 infection in pregnancy and infancy has accumulated throughout the course of the pandemic, though evidence regarding asymptomatic SARS-CoV-2 infection and adverse birth outcomes are scarce. Limited information is available from countries in sub-Saharan Africa (SSA). The pregnant woman and infant COVID in Africa study (PeriCOVID Africa) is a South-South-North partnership involving hospitals and health centres in five countries: Malawi, Uganda, Mozambique, The Gambia, and Kenya. The study leveraged data from three ongoing prospective cohort studies: Preparing for Group B Streptococcal Vaccines (GBS PREPARE), SARS-CoV-2 infection and COVID-19 in women and their infants in Kampala and Mukono (COMAC) and Pregnancy Care Integrating Translational Science Everywhere (PRECISE). In this paper we describe the seroepidemiology of SARS-CoV-2 infection in pregnant women enrolled in sites in Uganda and Malawi, and the impact of SARS-CoV-2 infection on pregnancy and infant outcomes. Outcome: Seroprevalence of SARS-CoV-2 antibodies in maternal blood, reported as the proportion of seropositive women by study site and wave of COVID-19 within each country. Methods: The PeriCOVID study was a prospective mother-infant cohort study that recruited pregnant women at any gestation antenatally or on the day of delivery. Maternal and cord blood samples were tested for SARS-CoV-2 antibodies using Wantai and Euroimmune ELISA. In periCOVID Uganda and Malawi nose and throat swabs for SARS-Cov-2 RT-PCR were obtained. Results: In total, 1379 women were enrolled, giving birth to 1387 infants. Overall, 63% of pregnant women had a SARS-CoV-2 positive serology. Over subsequent waves (delta and omicron), in the absence of vaccination, seropositivity rose from 20% to over 80%. The placental transfer GMR was 1.7, indicating active placental transfer of anti-spike IgG. There was no association between SARS-CoV-2 antibody positivity and adverse pregnancy or infancy outcomes. [ABSTRACT FROM AUTHOR]

Since the emergence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), its genetic and geographical origins remain unclear, resulting in suspicions about its natural origin. In one of our previous studies, we reported the presence of a furin cleavage site RRAR in the junction region between S1 and S2 subunits of the spike protein, which was discovered as the first crucial clue for the origin tracing of SARS-CoV-2. In the present study, we conducted an integrative analysis of new genome data from bat Sarbecovirus strains reported after the COVID-19 outbreak. The primary results included the identification of BANAL-20-52, Rp22DB159, and S18CXBatR24 as three close relatives of SARS-CoV-2 and the successful detection of seven out of nine key genomic features (designated as RC0-7 and ORF8) observed in wild types of SARS-CoV-2 in the three close relatives from Laos, Vietnam, and Yunnan province of China, respectively. The most significant contribution of the present study lies in the detection of RC1 in wild genotype in a bat Sarbecovirus population BANAL-20-52 belonging to. Encoding a segment of the NSP3 protein, RC1 was discovered as the second crucial clue for the origin tracing of SARS-CoV-2. Although RC0, encoding the junction furin cleavage site, remains undetected outside of the SARS-CoV-2 genome, Feuang of Laos is the sole place where eight of the nine wild-type features (RC1-7 and ORF8) have been detected. [ABSTRACT FROM AUTHOR]

During the COVID-19 pandemic, the scientific literature related to SARS-COV-2 has been growing dramatically. These literary items encompass a varied set of topics, ranging from vaccination to protective equipment efficacy as well as lockdown policy evaluations. As a result, the development of automatic methods that allow an in-depth exploration of this growing literature has become a relevant issue, both to identify the topical trends of COVID-related research and to zoom-in on its sub-themes. This work proposes a novel methodology, called LDA2Net, which combines topic modelling and network analysis, to investigate topics under their surface. More specifically, LDA2Net exploits the frequencies of consecutive words pairs (i.e. bigram) to build those network structures underlying the hidden topics extracted from large volumes of text by Latent Dirichlet Allocation (LDA). Results are promising and suggest that the topic model efficacy is magnified by the network-based representation. In particular, such enrichment is noticeable when it comes to displaying and exploring the topics at different levels of granularity. [ABSTRACT FROM AUTHOR]

The global impact of the SARS-CoV-2 pandemic has underscored the need for a deeper understanding of viral evolution to anticipate new viruses or variants. Genetic recombination is a fundamental mechanism in viral evolution, yet it remains poorly understood. In this study, we conducted a comprehensive research on the genetic regions associated with genetic recombination features in SARS-CoV-2. With this aim, we implemented a two-phase transfer learning approach using genomic spectrograms of complete SARS-CoV-2 sequences. In the first phase, we utilized a pre-trained VGG-16 model with genomic spectrograms of HIV-1, and in the second phase, we applied HIV-1 VGG-16 model to SARS-CoV-2 spectrograms. The identification of key recombination hot zones was achieved using the Grad-CAM interpretability tool, and the results were analyzed by mathematical and image processing techniques. Our findings unequivocally identify the SARS-CoV-2 Spike protein (S protein) as the pivotal region in the genetic recombination feature. For non-recombinant sequences, the relevant frequencies clustered around 1/6 and 1/12. In recombinant sequences, the sharp prominence of the main hot zone in the Spike protein prominently indicated a frequency of 1/6. These findings suggest that in the arithmetic series, every 6 nucleotides (two triplets) in S may encode crucial information, potentially concealing essential details about viral characteristics, in this case, recombinant feature of a SARS-CoV-2 genetic sequence. This insight further underscores the potential presence of multifaceted information within the genome, including mathematical signatures that define an organism's unique attributes. [ABSTRACT FROM AUTHOR]

While the early effects of the COVID-19 pandemic on the United States labor market are well-established, less is known about the long-term impact of SARS-CoV-2 infection and Long COVID on employment. To address this gap, we analyzed self-reported data from a prospective, national cohort study to estimate the effects of SARS-CoV-2 symptoms at three months post-infection on missed workdays and return to work. The analysis included 2,939 adults in the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE) study who tested positive for their initial SARS-CoV-2 infection at the time of enrollment, were employed before the pandemic, and completed a baseline and three-month electronic survey. At three months post-infection, 40.8% of participants reported at least one SARS-CoV-2 symptom and 9.6% of participants reported five or more SARS-CoV-2 symptoms. When asked about missed work due to their SARS-CoV-2 infection at three months, 7.2% of participants reported missing ≥10 workdays and 13.9% of participants reported not returning to work since their infection. At three months, participants with ≥5 symptoms had a higher adjusted odds ratio of missing ≥10 workdays (2.96, 95% CI 1.81–4.83) and not returning to work (2.44, 95% CI 1.58–3.76) compared to those with no symptoms. Prolonged SARS-CoV-2 symptoms were common, affecting 4-in-10 participants at three-months post-infection, and were associated with increased odds of work loss, most pronounced among adults with ≥5 symptoms at three months. Despite the end of the federal Public Health Emergency for COVID-19 and efforts to "return to normal", policymakers must consider the clinical and economic implications of the COVID-19 pandemic on people's employment status and work absenteeism, particularly as data characterizing the numerous health and well-being impacts of Long COVID continue to emerge. Improved understanding of risk factors for lost work time may guide efforts to support people in returning to work. [ABSTRACT FROM AUTHOR]

Background: The coronavirus Disease 2019 (COVID-19) pandemic has brought about unique challenges in healthcare and nutrition, particularly for people living with HIV (PLHIV). Understanding their dietary patterns and nutritional status is crucial for developing targeted interventions and improving health outcomes. Therefore, this study assessed the dietary diversity and nutritional status of PLHIV during the COVID-19 era. Methods: We adopted a facility-based cross-sectional study design to enroll 220 PLHIV from two hospitals in the Central Region of Ghana. Dietary intakes were assessed using 24-hour recall. Anthropometric and body composition data were collected with a stadiometer and a body composition monitor. Dietary diversity was evaluated using the FAO's Individual Dietary Diversity Score (IDDS). Data analysis was conducted with SPSS version 20. Significance level was set p-value less than 0.05. Results: A significant proportion (33.2%) of PLHIV had low dietary diversity, with the majority (55.5%) categorized as needing dietary improvement. Approximately 2 out of every 10 of the participants were identified as underweight. Participants aged 40 to 59 years were more likely to exhibit higher dietary diversity (adjusted odds ratio (AOR) = 1.966, 95% Confidence Interval (CI): 1.045–4.987). Participants who consumed meals at least three times daily were more likely to have a high IDDS (AOR = 1.641, 95% CI: 1.221, 8.879). Employed participants (public sector and private sector) were also more likely to have a high IDDS compared to unemployed participants (AOR = 1.448, 95% CI: 1.028–3.042; AOR = 1.165, 95% CI: 1.030–9.329, respectively). Factors associated with undernutrition included being female (AOR = 1.829, 95% CI: 1.294, 3.872) and first-line antiretroviral therapy ART (AOR = 1.683, 95% CI: 1.282–2.424). Conclusion: The study emphasizes the need for nutritional interventions for PLHIV, particularly during crises. It advocates for a policy collaboration to address food insecurity and promote resilient health outcomes. [ABSTRACT FROM AUTHOR]

Robust testing capacity was necessary for public health agencies to respond to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during the coronavirus disease 19 (COVID-19) pandemic. As the nation faced the need for robust testing capacity, it became necessary to use all possible resources. In many cases, veterinary diagnostic laboratories rose to meet this demand because these facilities routinely perform high throughput diagnostic testing of large animal populations and are typically familiar with pathogens of high pandemic concern. In this study, we evaluated the impact of veterinary diagnostic laboratories in the United States on SARS-CoV-2 testing. Results of surveys, semi-structured interviews, and analysis of publicly available information showed that veterinary diagnostic laboratories had a substantial impact on human health through population-level testing in the COVID-19 response, supporting timely and informed public health interventions. This success was not without significant hurdles, as many participating veterinary diagnostic laboratories experienced restriction in their response due to difficulties obtaining the Clinical Laboratory Improvement Amendments (CLIA) certification required to conduct human diagnostic testing. Our results point out the importance of reducing hurdles before the next major public health emergency to enhance access to testing resources overall and to ultimately improve population health. [ABSTRACT FROM AUTHOR]

There has been a lot of discussion about the role of schools in the transmission of severe acute respiratory coronavirus 2 (SARS-CoV-2) during the coronavirus 2019 (COVID-19) pandemic, where many countries responded with school closures in 2020. Reopening of primary schools in the Netherlands in February 2021 was sustained by various non-pharmaceutical interventions (NPIs) following national recommendations. Our study attempted to assess the degree of regional implementation and effectiveness of these NPIs in South Limburg, Netherlands. We approached 150 primary schools with a structured questionnaire containing items on the implementation of NPIs, including items on ventilation. Based on our registry of cases, we determined the number of COVID-19 cases linked to each school, classifying cases by their source of transmission. We calculated a crude secondary attack rate by dividing the number of cases of within-school transmission by the total number of children and staff members. Two-sample proportion tests were performed to compare these rates between schools stratified by the presence of a ventilation system and mask mandates for staff members. A total of 69 schools responded. Most implemented NPIs were aimed at students, except for masking mandates, which preferentially targeted teachers over students (63% versus 22%). We observed lower crude secondary attack rates in schools with a ventilation system compared to schools without a ventilation system (1.2% versus 2.8%, p<0.01). Mandatory masking for staff members had no effect on the overall crude secondary attack rate (2.0% versus 2.1%, p = 0.03) but decreased the crude secondary attack rate among staff members (2.3% versus 1.7%, p<0.01). Schools varied in their implementation of NPIs, most of which targeted students. Rates of within-school transmission were higher compared to other studies, possibly due to a lack of proper ventilation. Our research may help improve guidance for primary schools in future outbreaks. [ABSTRACT FROM AUTHOR]

During the SARS-CoV-2 pandemic, many countries established wastewater (WW) surveillance to objectively monitor the level of infection within the population. As new variants continue to emerge, it has become clear that WW surveillance is an essential tool for the early detection of variants. The EU Commission published a recommendation suggesting an approach to establish surveillance of SARS-CoV-2 and its variants in WW, besides specifying the methodology for WW concentration and RNA extraction. Therefore, different groups have approached the issue with different strategies, mainly focusing on WW concentration methods, but only a few groups highlighted the importance of prefiltering WW samples and/or purification of RNA samples. Aiming to obtain high-quality sequencing data allowing variants detection, we compared four experimental conditions generated from the treatment of: i) WW samples by WW filtration and ii) the extracted RNA by DNase treatment, purification and concentration of the extracted RNA. To evaluate the best condition, the results were assessed by focusing on several sequencing parameters, as the outcome of SARS-CoV-2 sequencing from WW is crucial for variant detection. Overall, the best sequencing result was obtained by filtering the WW sample. Moreover, the present study provides an overview of some sequencing parameters to consider when optimizing a method for monitoring SARS-CoV-2 variants from WW samples, which can also be applied to any sample preparation methodology. [ABSTRACT FROM AUTHOR]

Objective: To describe the implementation of a test-negative design case-control study in California during the Coronavirus Disease 2019 (COVID-19) pandemic. Study design: Test-negative case-control study Methods: Between February 24, 2021 ‐ February 24, 2022, a team of 34 interviewers called 38,470 Californians, enrolling 1,885 that tested positive for SARS-CoV-2 (cases) and 1,871 testing negative for SARS-CoV-2 (controls) for 20-minute telephone survey. We estimated adjusted odds ratios for answering the phone and consenting to participate using mixed effects logistic regression. We used a web-based anonymous survey to compile interviewer experiences. Results: Cases had 1.29-fold (95% CI: 1.24–1.35) higher adjusted odds of answering the phone and 1.69-fold (1.56–1.83) higher adjusted odds of consenting to participate compared to controls. Calls placed from 4pm to 6pm had the highest adjusted odds of being answered. Some interviewers experienced mental wellness challenges interacting with participants with physical (e.g., food, shelter, etc.) and emotional (e.g., grief counseling) needs, and enduring verbal harassment from individuals called. Conclusions: Calls placed during afternoon hours may optimize response rate when enrolling controls to a case-control study during a public health emergency response. Proactive check-ins and continual collection of interviewer experience(s) and may help maintain mental wellbeing of investigation workforce. Remaining adaptive to the dynamic needs of the investigation team is critical to a successful study, especially in emergent public health crises, like that represented by the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

A dynamic of virus adaptation and a mass vaccination campaign could significantly reduce the severity of clinical manifestations of COVID-19 and transmission. Hence, COVID-19 may become an endemic disease globally. Moreover, mass infection as the COVID-19 pandemic progressed affected the serology of the patients as a result of virus mutation and vaccination. Therefore, a need exists to acquire accurate serological testing to monitor the emergence of new outbreaks of COVID-19 to promptly prevent and control the disease spreading. In this study, the anti-Orf8 antibodies among samples collected in Thailand's first, fourth, and fifth waves of COVID-19 outbreaks compared with pre-epidemic sera were determined by indirect ELISA. The diagnostic sensitivity and specificity of the anti-Orf8 IgG ELISA for COVID-19 samples from the first, fourth, and fifth waves of outbreaks was found to be 100% compared with pre-epidemic sera. However, the diagnostic sensitivity and specificity of the anti-Orf8 IgG ELISA for a larger number of patient samples and controls from the fifth wave of outbreaks which were collected on day 7 and 14 after an RT-PCR positive result were 58.79 and 58.44% and 89.19 and 58.44%, respectively. Our data indicated that some of the controls might have antibodies from natural past infections. Our study highlighted the potential utility of anti-Orf8 IgG antibody testing for seroprevalence surveys but still warrants further investigations. [ABSTRACT FROM AUTHOR]

Background: Community-based mask wearing has been shown to reduce the transmission of SARS-CoV-2. However, few studies have conducted an economic evaluation of mask mandates, specifically in public transportation settings. This study evaluated the cost-effectiveness of implementing mask mandates for subway passengers in the United States by evaluating its potential to reduce COVID-19 transmission during subway travel. Materials and methods: We assessed the health impacts and costs of subway mask mandates compared to mask recommendations based on the number of infections that would occur during subway travel in the U.S. Using a combined box and Wells-Riley infection model, we estimated monthly infections, hospitalizations, and deaths averted under a mask mandate scenario as compared to a mask recommendation scenario. The analysis included costs of implementing mask mandates and COVID-19 treatment from a limited societal perspective. The cost-effectiveness (net cost per averted death) of mandates was estimated for three different periods based on dominant SARS-CoV-2 variants: Alpha, Beta, and Gamma (November 2020 to February 2021); Delta (July to October 2021); and early Omicron (January to March 2022). Results: Compared with mask recommendations only, mask mandates were cost-effective across all periods, with costs per averted death less than a threshold of $11.4 million (ranging from cost-saving to $3 million per averted death). Additionally, mask mandates were more cost-effective during the early Omicron period than the other two periods and were cost saving in January 2022. Our findings showed that mandates remained cost-effective when accounting for uncertainties in input parameters (e.g., even if mandates only resulted in small increases in mask usage by subway ridership). Conclusions: The findings highlight the economic value of mask mandates on subways, particularly during high virus transmissibility periods, during the COVID-19 pandemic. This study may inform stakeholders on mask mandate decisions during future outbreaks of novel viral respiratory diseases. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic was characterised by rapid waves of disease, carried by the emergence of new and more infectious SARS-CoV-2 virus variants. How the pandemic unfolded in various locations during its first two years has yet to be sufficiently covered. To this end, here we are looking at the circulating SARS-CoV-2 variants, their diversity, and hospitalisation rates in Estonia in the period from March 2000 to March 2022. Methods: We sequenced a total of 27,550 SARS-CoV-2 samples in Estonia between March 2020 and March 2022. High-quality sequences were genotyped and assigned to Nextstrain clades and Pango lineages. We used regression analysis to determine the dynamics of lineage diversity and the probability of clade-specific hospitalisation stratified by age and sex. Results: We successfully sequenced a total of 25,375 SARS-CoV-2 genomes (or 92%), identifying 19 Nextstrain clades and 199 Pango lineages. In 2020 the most prevalent clades were 20B and 20A. The various subsequent waves of infection were driven by 20I (Alpha), 21J (Delta) and Omicron clades 21K and 21L. Lineage diversity via the Shannon index was at its highest during the Delta wave. About 3% of sequenced SARS-CoV-2 samples came from hospitalised individuals. Hospitalisation increased markedly with age in the over-forties, and was negligible in the under-forties. Vaccination decreased the odds of hospitalisation in over-forties. The effect of vaccination on hospitalisation rates was strongly dependent upon age but was clade-independent. People who were infected with Omicron clades had a lower hospitalisation likelihood in age groups of forty and over than was the case with pre-Omicron clades regardless of vaccination status. Conclusions: COVID-19 disease waves in Estonia were driven by the Alpha, Delta, and Omicron clades. Omicron clades were associated with a substantially lower hospitalisation probability than pre-Omicron clades. The protective effect of vaccination in reducing hospitalisation likelihood was independent of the involved clade. [ABSTRACT FROM AUTHOR]

Background and aims: The coronavirus disease 2019 (COVID-19) public health emergency has had a huge impact worldwide. We analyzed news headlines and keywords from the initial period of COVID-19, and explored the dissemination timeline of news related to the epidemic, and the impact of Internet-based media on the public using lifecycle theory and agenda-setting theory. We aimed to explore the impact of Baidu news headlines on public attention during the first wave of COVID-19, as well as the management mechanism of regulatory departments for social public opinion. Methods: We searched Baidu News using the keywords "Novel Coronavirus" and "COVID-19" from 8 January to 21 February 2020, a total of 45 days, and used Python V3.6 to extract news samples during the first wave of the epidemic. We used text analysis software to structurally process captured news topics and content summaries, applied VOSviewer V6.19 and Ucinet V6.0 to examine key aspects of the data. Results: We analyzed the impact of Baidu News headlines on social opinion during the first wave of COVID-19 in the budding, spread, and outbreak stage of the information lifecycle. From clustering visualization and social network analysis perspectives, we explored the characteristics of Baidu News during the initial stage of the COVID-19. The results indicated that agenda-setting coverage through online media helped to mitigate the negative impact of COVID-19. The findings revealed that news reporting generated a high level of public attention toward a specific emergency event. Conclusions: The public requires accurate and objective information on the progress of COVID-19 through Baidu News headlines to inform their planning for the epidemic. Meanwhile, government can enhance the management mechanism of news dissemination, correct false and inaccurate news, and guide public opinion in a positive direction. In addition, timely official announcements on the progress of the COVID-19 outbreak and responses to matters of public concern can help calm tensions and maintain social stability. [ABSTRACT FROM AUTHOR]

Background: Conducting a study in rural pre-dominant areas will help to understand the penetration of the vaccination campaign during the COVID-19 health crisis. This study aimed to investigate vaccination coverage against COVID-19 among the rural adult population in India and to identify factors associated with vaccination coverage. Methods: A population-based cross-sectional study was conducted among the rural population in one district of north India from January to February 2023. A semi-structured questionnaire was designed on the SurveyMonkey digital platform for interviewing the participants, which consisted of questions related to socio-demographic profile, health problems, vaccination status, types of vaccine, re-infection after vaccination, and functional difficulties. The data regarding infection with COVID-19 was collected based on self-reported positive testing for SARS-CoV 2 on RT-PCR. Findings: A total of 3700 eligible individuals were enumerated for the survey, out of which 2954 (79.8%) were interviewed. The infection rate of past COVID-19 infection, based on self-report of testing positive, was 6.2% (95%CI: 5.3–7.1). Covishield vaccine was received by most participants (81.3%, 2380) followed by Covaxin (12.3%, 361) and Pfizer manufactured vaccine (0.03,1). The coverage for first, second, and booster doses of the vaccine was 98.2% (2902), 94.8% (2802), and 10.7% (315) respectively. The risk of reinfection at 12 months or more among participants with two doses of vaccine was 1.6% (46/2802, 95%CI: 1.2–2.1). The coverage among those with severe functional difficulties was lesser as compared to those with some or no difficulties. Interpretation: Vaccination coverage against COVID-19 in rural Haryana, India is not dependent on factors like gender or occupation but is dependent on age and education. Although the full and partial vaccination coverage is high, the booster dose coverage is poor. In addition, the presence of severe disability was significantly associated with reduced vaccination coverage. [ABSTRACT FROM AUTHOR]

Considering sex as a biological variable in modern digital health solutions, we investigated sex-specific differences in the trajectory of four physiological parameters across a COVID-19 infection. A wearable medical device measured breathing rate, heart rate, heart rate variability, and wrist skin temperature in 1163 participants (mean age = 44.1 years, standard deviation [SD] = 5.6; 667 [57%] females). Participants reported daily symptoms and confounders in a complementary app. A machine learning algorithm retrospectively ingested daily biophysical parameters to detect COVID-19 infections. COVID-19 serology samples were collected from all participants at baseline and follow-up. We analysed potential sex-specific differences in physiology and antibody titres using multilevel modelling and t-tests. Over 1.5 million hours of physiological data were recorded. During the symptomatic period of infection, men demonstrated larger increases in skin temperature, breathing rate, and heart rate as well as larger decreases in heart rate variability than women. The COVID-19 infection detection algorithm performed similarly well for men and women. Our study belongs to the first research to provide evidence for differential physiological responses to COVID-19 between females and males, highlighting the potential of wearable technology to inform future precision medicine approaches. [ABSTRACT FROM AUTHOR]

The novel coronavirus, COVID-19, first identified in Wuhan, China, in December 2019, rapidly spread across the globe and resulted in significant public concern. In response, numerous countries have implemented guidelines aimed at promoting social distancing, limiting movement and gatherings, instituting lockdowns and curfews, and closing institutions. As a result, the media, including news releases, has become a primary source of information for many individuals (Laor & Lissitsa, 2022). The present study seeks to investigate differences between major television programs featured on public and commercial channels in Israel, utilizing the lens of framing theory. Specifically, twelve monologues broadcast simultaneously on both channels were analyzed to compare differences in content, topics, format, and accompanying visuals. The study's results indicate that both commercial and public channels exhibited similar behavior in shaping public opinion during the crisis period. Specifically, both channels displayed criticism of the government's conduct and utilized negative framing techniques while neglecting to provide space for popular voices. Nevertheless, certain distinctions between the commercial and public broadcasting spheres still persist, particularly in the realm of visual presentation, as some long-standing elements that typify each channel have endured over time. [ABSTRACT FROM AUTHOR]

Purpose: Since identified in December 2019, the novel coronavirus disease 2019 (COVID-19) has had a global impact on medical resource use and costs for patients with cancer in South Korea. This study aimed to identify the medical use and costs among patients with cancer during the COVID-19 pandemic, to predict these patterns in South Korea in the future. Methods: We conducted a secondary claims data analysis using the National Health Insurance Service database for the calendar period of 2019–2020. Monthly relative percent changes in cancer incidence, medical use, and billing costs for medical care utilization by cancer type were calculated. Then, the medical use and costs after January 2020 were predicted using a time series model with data before the COVID-19 outbreak (2014–2019). Results: The incidence of cancer diagnoses has seen a notable decline since the outbreak of the COVID-19 in 2020 as compared to 2019. Despite the impact of COVID-19, there hasn't been a distinct decline in outpatient utilization when compared to inpatient utilization. While medical expenses for both inpatient and outpatient visits have slightly increased, the number of patients treated for cancer has decreased significantly compared to the previous year. In June 2020, overall outpatient costs experienced the highest increase (21.1%), while individual costs showed the most significant decrease (-4.9%) in June 2020. Finally, the number of hospitalisations and outpatient visits increased slightly from June–July in 2020, reducing the difference between the actual and predicted values. The decrease in the number of inpatient hospitalisations (-22~-6%) in 2020 was also high. Conclusions: The overall use of medical services by patients with cancer decreased in 2020 compared with that in the pre-COVID-19 pandemic period. In the future, the government should consider how to recover from the COVID-19 pandemic, and establish permanent health policies for patients with cancer. [ABSTRACT FROM AUTHOR]

The coronavirus disease (COVID-19) pandemic has significantly affected blood donors worldwide. It is important for the blood service to return to its pre-pandemic level as soon as possible and to perform its functions fully. This study compared the donation and demographic profiles of blood and its component donors one year before and during three pandemic years in Lithuania. All blood and blood component donations (n = 413,358) and demographic characteristics of all donors from April 1, 2019, to March 31, 2023, were analyzed. All data were obtained from annual publications, and statistics were obtained from the Blood Donor Register. Data were analyzed using descriptive statistics. Following a 9.41 percent decrease in the first year of the pandemic, the quantity of blood and blood component donations increased by 3.49 percent in the third year compared to the pre-pandemic year. Throughout the three years of the pandemic, a statistically significant decrease in the proportion of first-time blood and blood component donations was observed. Both the number and proportion of donations by donors under 25 years old decreased during the pandemic. The proportion of pre-donation deferrals for all attempts to donate significantly decreased during the pandemic. There was a statistically significant lower prevalence of all positive transfusion-transmitted infectious (TTI) markers among all donations compared to the pre-pandemic year for all three pandemic years. The odds for hepatitis B virus, hepatitis C virus, and all TTI markers during the second and third pandemic years were significantly lower than those in the pre-pandemic year. In conclusion, most dimensions of blood and its component donations and donor characteristics have returned to pre-pandemic levels or show positive trends. However, the major concern is the remaining decrease in donations from first-time and donors under 25 years old. [ABSTRACT FROM AUTHOR]

Several studies have revealed that SARS-CoV-2 damages brain function and produces significant neurological disability. The SARS-CoV-2 coronavirus, which causes COVID-19, may infect the heart, kidneys, and brain. Recent research suggests that monoamine oxidase B (MAO-B) may be involved in metabolomics variations in delirium-prone individuals and severe SARS-CoV-2 infection. In light of this situation, we have employed a variety of computational to develop suitable QSAR model using PyDescriptor and genetic algorithm-multilinear regression (GA-MLR) models (R2 = 0.800–793, Q2LOO = 0.734–0.727, and so on) on the data set of 106 molecules whose anti-SARS-CoV-2 activity was empirically determined. QSAR models generated follow OECD standards and are predictive. QSAR model descriptors were also observed in x-ray-resolved structures. After developing a QSAR model, we did a QSAR-based virtual screening on an in-house database of 200 compounds and found a potential hit molecule. The new hit's docking score (-8.208 kcal/mol) and PIC50 (7.85 M) demonstrated a significant affinity for SARS-CoV-2's main protease. Based on post-covid neurodegenerative episodes in Alzheimer's and Parkinson's-like disorders and MAO-B's role in neurodegeneration, the initially disclosed hit for the SARS-CoV-2 main protease was repurposed against the MAO-B receptor using receptor-based molecular docking, which yielded a docking score of -12.0 kcal/mol. This shows that the compound that inhibits SARS-CoV-2's primary protease may bind allosterically to the MAO-B receptor. We then did molecular dynamic simulations and MMGBSA tests to confirm molecular docking analyses and quantify binding free energy. The drug-receptor complex was stable during the 150-ns MD simulation. The first computational effort to show in-silico inhibition of SARS-CoV-2 Mpro and allosteric interaction of novel inhibitors with MAO-B in post-covid neurodegenerative symptoms and other disorders. The current study seeks a novel compound that inhibits SAR's COV-2 Mpro and perhaps binds MAO-B allosterically. Thus, this study will enable scientists design a new SARS-CoV-2 Mpro that inhibits the MAO-B receptor to treat post-covid neurological illness. [ABSTRACT FROM AUTHOR]