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Background: The Covid-19 pandemic has created substantial and profound barriers to several forms of healthcare engagement. For Black sexual minority men, this may include engagement with pre-exposure prophylaxis (PrEP) to prevent HIV infection, with significant implications for HIV disparities. Our study explored how the Covid-19 pandemic affected Black sexual minority men, with a focus on relationships between Covid-19 and PrEP engagement. Setting: We sampled 24 Black sexual minority men attending HIV prevention-related events in the greater D.C. Metropolitan area (D.C., Maryland, Virginia). Methods: We conducted qualitative phone interviews among our sample. Questions were primarily focused on the Covid-19 pandemic and how it affected engagement and considerations of PrEP use. Interviews were transcribed and qualitatively analyzed using the six stages of thematic analysis. Results: We identified three major themes from our thematic analysis: Changes in the healthcare system, changes in sexual and relationship contexts, and Covid-19 vaccine hesitancy and misinformation. Relationships between Covid-19 vaccine hesitancy and PrEP hesitancy were especially prevalent, with participants describing that Covid-19 hesitancy can directly deter PrEP use through eroding medical trust further. Conclusion: We identified changes in the healthcare system, sexual and relationship contexts, and Covid-19 vaccine hesitancy as important issues driven by Covid-19 with significant implications for PrEP use. The Covid-19 pandemic has changed the healthcare and social landscape in profound ways that impact PrEP access, sexual networks, and associated HIV vulnerability. Future research further exploring relationships between specific pandemic stressors and HIV prevention among Black sexual minority men is recommended. Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.

Science Advances, Volume 9, Issue 38, September 2023.

ObjectiveCOVID-19 would kill fewer people if health programmes can predict who is at higher risk of mortality because resources can be targeted to protect those people from infection. We predict mortality in a very large population in Mexico with machine learning using demographic variables and pre-existing conditions. DesignCohort study. SettingMarch 2020 to November 2021 in Mexico, nationally represented. Participants1.4 million laboratory-confirmed patients with COVID-19 in Mexico at or over 20 years of age. Primary and secondary outcome measuresAnalysis is performed on data from March 2020 to November 2021 and over three phases: (1) from March to October in 2020, (2) from November 2020 to March 2021 and (3) from April to November 2021. We predict mortality using an ensemble machine learning method, super learner, and independently estimate the adjusted mortality relative risk of each pre-existing condition using targeted maximum likelihood estimation. ResultsSuper learner fit has a high predictive performance (C-statistic: 0.907), where age is the most predictive factor for mortality. After adjusting for demographic factors, renal disease, hypertension, diabetes and obesity are the most impactful pre-existing conditions. Phase analysis shows that the adjusted mortality risk decreased over time while relative risk increased for each pre-existing condition. ConclusionsWhile age is the most important predictor of mortality, younger individuals with hypertension, diabetes and obesity are at comparable mortality risk as individuals who are 20 years older without any of the three conditions. Our model can be continuously updated to identify individuals who should most be protected against infection as the pandemic evolves. …

Abstract Background Coronavirus disease 2019 (COVID-19) is a rapidly developing and sometimes lethal pulmonary disease. Accurately predicting COVID-19 mortality will facilitate optimal patient treatment and medical resource deployment, but the clinical practice still needs to address it. Both complete blood counts and cytokine levels were observed to be modified by COVID-19 infection. This study aimed to use inexpensive and easily accessible complete blood counts to build an accurate COVID-19 mortality prediction model. The cytokine fluctuations reflect the inflammatory storm induced by COVID-19, but their levels are not as commonly accessible as complete blood counts. Therefore, this study explored the possibility of predicting cytokine levels based on complete blood counts. Methods We used complete blood counts to predict cytokine levels. The predictive model includes an autoencoder, principal component analysis, and linear regression models. We used classifiers such as support vector machine and feature selection models such as adaptive boost to predict the mortality of COVID-19 patients. Results Complete blood counts and original cytokine levels reached the COVID-19 mortality classification area under the curve (AUC) values of 0.9678 and 0.9111, respectively, and the cytokine levels predicted by the feature set alone reached the classification AUC value of 0.9844. The predicted cytokine levels were more significantly associated with COVID-19 mortality than the original values. Conclusions Integrating the predicted cytokine levels and complete blood counts improved a COVID-19 mortality prediction model using complete blood counts only. Both the cytokine level prediction models and the COVID-19 mortality prediction models are publicly available at http://www.healthinformaticslab.org/supp/resources.php. …

by Suely Deysny de Matos Celino, Nailton José Brandão de Albuquerque Filho, Monalisa da Nóbrega Cesarino Gomes, Gabriela Maria Cavalcanti Costa, Ana Elza Oliveira de Mendonça Objective To evaluate the primary health care (PHC) attributes and associated factors during the COVID-19 pandemic using the perspective of users. Methods This cross-sectional, quantitative study included 422 PHC users from 96 Family Health Teams in a city in Brazil. The assessment used the Primary Care Assessment Tool (PCATool) and a structured questionnaire on the sociodemographic and epidemiological characteristics of users and basic health units (BHU). The Person’s chi-square test was used to analyze the association between high overall scores in PCATool and characteristics of users and BHU. Crude and adjusted prevalence ratios (PR) with a 95% confidence interval were also calculated. Poisson regression and Rao Scott’s Chi-square test were used to estimate crude PR. Results Most users were aged 30 to 39 years (26.3%), women (75.4%), registered at the BHU for over ten years (59.5%), and had incomplete secondary education (30.6%). The mean of PHC essential attributes and overall scores were low (6.10 ± 0.81 and 5.78 ± 0.77, respectively). \'First-contact care–use\' received the highest score (9.22 ± 1.62), while \'first-contact care–accessibility\' received the lowest (2.82 ± 0.90). High overall scores were associated with an average employment time of professionals (doctors and nurses) at the BHU (PR = 1.31; 95% CI 1.17–1.48; p < 0.001) and lower educational level of users (PR = 1.71; 95% CI 1.54–1.90; p < 0.001. Conclusion \'First-contact care–use\' was the best evaluated, while \'first-contact care–accessibility\' was the worst. High scores were associated with a lower educational level of users and BHU with more experienced professionals. …

by Jeremy Bingham, Stefano Tempia, Harry Moultrie, Cecile Viboud, Waasila Jassat, Cheryl Cohen, Juliet R.C. Pulliam Objectives The aim of this study was to quantify transmission trends in South Africa during the first four waves of the COVID-19 pandemic using estimates of the time-varying reproduction number (R) and to compare the robustness of R estimates based on three different data sources, and using data from public and private sector service providers. Methods R was estimated from March 2020 through April 2022, nationally and by province, based on time series of rt-PCR-confirmed cases, hospitalisations, and hospital-associated deaths, using a method that models daily incidence as a weighted sum of past incidence, as implemented in the R package EpiEstim. R was also estimated separately using public and private sector data. Results Nationally, the maximum case-based R following the introduction of lockdown measures was 1.55 (CI: 1.43–1.66), 1.56 (CI: 1.47–1.64), 1.46 (CI: 1.38–1.53) and 3.33 (CI: 2.84–3.97) during the first (Wuhan-Hu), second (Beta), third (Delta), and fourth (Omicron) waves, respectively. Estimates based on the three data sources (cases, hospitalisations, deaths) were generally similar during the first three waves, but higher during the fourth wave for case-based estimates. Public and private sector R estimates were generally similar except during the initial lockdowns and in case-based estimates during the fourth wave. Conclusion Agreement between R estimates using different data sources during the first three waves suggests that data from any of these sources could be used in the early stages of a future pandemic. The high R estimates for Omicron relative to earlier waves are interesting given a high level of exposure pre-Omicron. The agreement between public and private sector R estimates highlights that clients of the public and private sectors did not experience two separate epidemics, except perhaps to a limited extent during the strictest lockdowns in the first wave. …

We have read with great interest the article by Velavan et al. [1]. In this study, the authors showed how several soft and alcoholic drinks could be used to create false positive results with COVID-19 rapid antigen test (RAT) when using the Abott Panbio COVID-19 Ag Lateral Flow Test Cassette. RAT were massively introduced in 2021 as a point-of-care diagnosis tool. With a good specificity and sensitivity for several brands in the market [2], the speed and convenience of RAT made them available for self-testing worldwide.

ObjectivesThere is limited in-depth research exploring persistent symptoms and conditions among children and adolescents who contracted COVID-19 illness that required hospitalisation. The main objective of this study was to conduct qualitative interviews among families who had a child hospitalised with COVID-19 illness to elucidate their child’s physical, mental and social health outcomes months after initial acute infection. Design, setting and participantsA qualitative study that composed of in-depth interviews among families with a child hospitalised with COVID-19 illness in one large urban US paediatric healthcare system. Parents (N=25) were recruited from an ongoing quantitative study to estimate the prevalence of long COVID in children hospitalised with COVID-19 illness. During in-depth interviews, parents were invited to describe their child’s post-COVID-19 symptoms and experiences. Interviews were audiotaped, transcribed and coded in NVivo. ResultsSeven themes were identified concerning the child’s prolonged COVID-19 experiences: (1) post-traumatic stress disorder, (2) social anxiety, (3) severe symptoms on reinfection, (4) worsened pre-existing conditions, (5) lack of insurance coverage for costly treatments, (6) access and utilisation of support systems and (7) overall resilience and recovery. Four parent-specific themes were identified: (1) fear of COVID-19 unknowns, (2) mixed messaging from health information sources, (3) schools being both a support system and a hindrance and (4) desire for and access to support systems. ConclusionsA subset of children who were hospitalised with COVID-19 illness are experiencing a range of serious mental health impacts related to persistent COVID-19 symptoms. Clinical and public health support strategies should be developed to support these children and their families as they reintegrate in school, social and community activities. …

ObjectivesDespite growing evidence suggesting increased COVID-19 mortality among people from ethnic minorities, little is known about milder forms of SARS-CoV-2 infection. We sought to explore the association between ethnic background and the probability of testing, testing positive, hospitalisation, COVID-19 mortality and vaccination uptake. DesignA multistate cohort analysis. Participants were followed between 8 April 2020 and 30 September 2021. SettingThe UK Biobank, which stores medical data on around half a million people who were recruited between 2006 and 2010. Participants405 541 subjects were eligible for analysis, limited to UK Biobank participants living in England. 23 891 (6%) of participants were non-white. Primary and secondary outcome measuresThe associations between ethnic background and testing, testing positive, hospitalisation and COVID-19 mortality were studied using multistate survival analyses. The association with single and double-dose vaccination was also modelled. Multistate models adjusted for age, sex and socioeconomic deprivation were fitted to estimate adjusted HRs (aHR) for each of the multistate transitions. Results18 172 (4.5%) individuals tested positive, 3285 (0.8%) tested negative and then positive, 1490 (6.9% of those tested positive) were hospitalised, and 129 (0.6%) tested positive at the moment of hospital admission (ie, direct hospitalisation). Finally, 662 (17.4%) died after admission. Compared with white participants, Asian participants had an increased risk of negative to positive transition (aHR 1.24 (95% CI 1.02 to 1.52)), testing positive (95% CI 1.44 (1.33 to 1.55)) and direct hospitalisation (1.61 (95% CI 1.28 to 2.03)). Black participants had an increased risk of hospitalisation following a positive test (1.71 (95% CI 1.29 to 2.27)) and direct hospitalisation (1.90 (95% CI 1.51 to 2.39)). Although not the case for Asians (aHR 1.00 (95% CI 0.98 to 1.02)), black participants had a reduced vaccination probability (0.63 (95% CI 0.62 to 0.65)). In contrast, Chinese participants had a reduced risk of testing negative (aHR 0.64 (95% CI 0.57 to 0.73)), of testing positive (0.40 (95% CI 0.28 to 0.57)) and of vaccination (0.78 (95% CI 0.74 to 0.83)). ConclusionsWe identified inequities in testing, vaccination and COVID-19 outcomes according to ethnicity in England. Compared with whites, Asian participants had increased risks of infection and admission, and black participants had almost double hospitalisation risk, and a 40% lower vaccine uptake. …

Abstract Background COVID-19 is a global pandemic. Understanding the immune responses in pregnant women recovering from COVID-19 may suggest new therapeutic approaches. Methods We performed a cross-sectional study between March 1, 2020, and September 1, 2020. Participants were assigned into the convalescent COVID-19 group if they had a previous COVID-19 infection during pregnancy or the healthy control group. RNA-Seq was performed on human umbilical cord mesenchymal stem cells (hUMSCs) and human amniotic mesenchymal stem cells (hAMSCs). Immunohistochemical staining, cytokine testing, lymphocyte subset analysis, RNA-Seq, and functional analyses were performed on the placental and umbilical cord blood (UCB) and compared between the two groups. Results A total of 40 pregnant women were enrolled, with 13 in the convalescent group and 27 in the control group. There were 1024, 46, and 32 differentially expressed genes (DEGs) identified in the placental tissue, hUMSCs, and hAMSCs between the convalescent and control groups, respectively. Enrichment analysis showed those DEGs were associated with immune homeostasis, antiviral activity, cell proliferation, and tissue repair. Levels of IL-6, TNF-α, total lymphocyte counts, B lymphocytes, Tregs percentages, and IFN-γ expressing CD4+ and CD8+ T cells were statistically different between two groups (p ≤ 0.05). ACE2 and TMPRSS2 expressed on the placenta were not different between the two groups (p > 0.05). Conclusion Multiple changes in immune responses occurred in the placental tissue, hUMSCs, and hAMSCs after maternal recovery from COVID-19, which might imply their protective roles against COVID-19 infection. …

by Yongxian Fan, Meng Liu, Guicong Sun Coronaviruses have affected the lives of people around the world. Increasingly, studies have indicated that the virus is mutating and becoming more contagious. Hence, the pressing priority is to swiftly and accurately predict patient outcomes. In addition, physicians and patients increasingly need interpretability when building machine models in healthcare. We propose an interpretable machine framework(KISM) that can diagnose and prognose patients based on blood test datasets. First, we use k-nearest neighbors, isolated forests, and SMOTE to pre-process the original blood test datasets. Seven machine learning tools Support Vector Machine, Extra Tree, Random Forest, Gradient Boosting Decision Tree, eXtreme Gradient Boosting, Logistic Regression, and ensemble learning were then used to diagnose and predict COVID-19. In addition, we used SHAP and scikit-learn post-hoc interpretability to report feature importance, allowing healthcare professionals and artificial intelligence models to interact to suggest biomarkers that some doctors may have missed. The 10-fold cross-validation of two public datasets shows that the performance of KISM is better than that of the current state-of-the-art methods. In the diagnostic COVID-19 task, an AUC value of 0.9869 and an accuracy of 0.9787 were obtained, and ultimately Leukocytes, platelets, and Proteina C reativa mg/dL were found to be the most indicative biomarkers for the diagnosis of COVID-19. An AUC value of 0.9949 and an accuracy of 0.9677 were obtained in the prognostic COVID-19 task and Age, LYMPH, and WBC were found to be the most indicative biomarkers for identifying the severity of the patient.

by Daniel T. L. Shek, Tingyin Wong, Xiang Li, Lu Yu The use of online teaching mode has grown rapidly in recent years, particularly under the COVID-19 pandemic. To promote the learning motivation of students and teaching effectiveness, development of attractive online teaching material such as videos is important. In the present study, we developed 15 theory-related videos and 9 case-based videos in the context of a leadership course focusing on psychological well-being and psychosocial competence. Using a qualitative research methodology via focus groups (N = 48 students) to evaluate these videos, six themes emerged from the data, including video arrangement, design of videos, content of videos, benefits to students’ pre-lesson self-learning, benefits to students’ learning of course content, and contribution to students’ class participation. The findings suggest that the videos can elicit positive perceptions of the students in a flipped classroom arrangement. Students also benefit from the videos in terms of their understanding of course content and their participation in class discussion. Besides, the study suggests that the videos promote the learning efficiency of the students. The present qualitative findings concurred with the previous quantitative findings, suggesting the value of using virtual teaching and learning to promote psychosocial competence in university students.

Since the early phase of SARS-CoV-2 pandemic it has been questioned which groups of subjects were at higher risk of worse COVID-19 outcomes. This would have allowed firstly to implement specific preventing interventions, allocate therapeutic resources, and in the later phases of the pandemic prioritize COVID-19 vaccination. Demographic factors shortly appeared to be the main determinants of COVID-19 outcomes, with older age, male sex and social deprivation as strongly associated with hospitalization and death [1].

New England Journal of Medicine, Volume 389, Issue 12, Page 1085-1095, September 2023.

IntroductionThe implementation of COVID-19 pandemic-related restrictions resulted in limitations for physical activity (PA) opportunities, which may have initiated a longer-term behavioural change. The protocol describes the methodology for a planned systematic review that aims to summarise changes in PA and physical fitness (PF) in children and adolescents in the WHO European Region after the onset of the COVID-19 pandemic. Methods and analysisThe protocol adheres to the ‘Preferred Reporting Items for Systematic Review and Meta-Analysis for Protocols’ (PRISMA-P) statement. Using a peer-reviewed search strategy according to the evidence-based checklist ‘Peer Review of Electronic Search Strategies’ (PRESS), we will perform a systematic literature search in seven databases. Inclusion criteria are all primary studies that gathered data on children and adolescents ≤19 years living in the WHO European Region and made a comparison to pre-pandemic data. Primary outcomes are PA and PF. We will assess the risk of bias with the ‘Risk of Bias Instrument for Non-Randomized Studies of Exposures’ (ROBINS-E). The ‘Grading of Recommendations Assessment, Development and Evaluation’ (GRADE) approach will be used for the evaluation of the certainty of evidence. Also, subgroup analyses will be performed (eg, for gender, age, stringency of pandemic restrictions). Ethics and disseminationEthical approval is not required, as primary data will not be collected in this study. The results will be presented in a peer-reviewed publication and at congresses relevant to the research field. PROSPERO registration numberCRD42023395871. …

ObjectivesThe COVID-19 pandemic affected provision and use of maternal health services. This study describes changes in obstetric complications, referrals, stillbirths and maternal deaths during the first year of the pandemic and elucidates pathways to these changes. DesignProspective observational mixed-methods study, combining monthly routine data (March 2019–February 2021) and qualitative data from prospective semi-structured interviews. Data were analysed separately, triangulated during synthesis and presented along three country-specific pandemic periods: first wave, slow period and second wave. SettingSix referral maternities in four sub-Saharan African countries: Guinea, Nigeria, Tanzania and Uganda. Participants22 skilled health personnel (SHP) working in the maternity wards of various cadres and seniority levels. ResultsPercentages of obstetric complications were constant in four of the six hospitals. The percentage of obstetric referrals received was stable in Guinea and increased at various times in other hospitals. SHP reported unpredictability in the number of referrals due to changing referral networks. All six hospitals registered a slight increase in stillbirths during the study period, the highest increase (by 30%–40%) was observed in Uganda. Four hospitals registered increases in facility maternal mortality ratio; the highest increase was in Guinea (by 158%), which had a relatively mild COVID-19 epidemic. These increases were not due to mortality among women with COVID-19. The main pathways leading to these trends were delayed care utilisation and disruptions in accessing care, including sub-optimal referral linkages and health service closures. ConclusionsMaternal and perinatal survival was negatively affected in referral hospitals in sub-Saharan Africa during COVID-19. Routine data systems in referral hospitals must be fully used as they hold potential in informing adaptations of maternal care services. If combined with information on women’s and care providers’ needs, this can contribute to ensuring continuation of essential care provision during emergency. …

ObjectiveTo identify, review and synthesise qualitative literature on healthcare professionals’ adaptations to changes and challenges resulting from the COVID-19 pandemic. DesignSystematic review with meta-synthesis. Data sourcesAcademic Search Elite, CINAHL, MEDLINE, PubMed, Science Direct and Scopus. Eligibility criteriaQualitative or mixed-methods studies published between 2019 and 2021 investigating healthcare professionals’ adaptations to changes and challenges resulting from the COVID-19 pandemic. Data extraction and synthesisData were extracted using a predesigned data extraction form that included details about publication (eg, authors, setting, participants, adaptations and outcomes). Data were analysed using thematic analysis. ResultsForty-seven studies were included. A range of adaptations crucial to maintaining healthcare delivery during the COVID-19 pandemic were found, including taking on new roles, conducting self and peer education and reorganising workspaces. Triggers for adaptations included unclear workflows, lack of guidelines, increased workload and transition to digital solutions. As challenges arose, many health professionals reported increased collaboration across wards, healthcare teams, hierarchies and healthcare services. ConclusionHealthcare professionals demonstrated significant adaptive capacity when faced with challenges imposed by the COVID-19 pandemic. Several adaptations were identified as beneficial for future organisational healthcare service changes, while others exposed weaknesses in healthcare system designs and capacity, leading to dysfunctional adaptations. Healthcare professionals’ experiences working during the COVID-19 pandemic present a unique opportunity to learn how healthcare systems rapidly respond to changes, and how resilient healthcare services can be built globally. …

Abstract Background Omicron variant of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has rapidly become a global threat to public health. Numerous asymptomatic and mild cases had been admitted in shelter hospitals to quickly win the fight against Omicron pandemic in Shanghai. However, little is known about influencing factors for deterioration and length of stay (LOS) in hospitals among these non-severe cases. Methods This study included 12,555 non-severe cases with COVID-19 in largest shelter hospital of Shanghai, aiming to explore prognostic factors and build effective models for prediction of LOS. Results Data showed that 75.0% of participants were initially asymptomatic. In addition, 94.6% were discharged within 10 days, only 0.3% with deterioration in hospitals. The multivariate analysis indicated that less comorbidities (OR = 1.792, P = 0.012) and booster vaccination (OR = 0.255, P = 0.015) was associated with the decreased risk of deterioration. Moreover, age (HR = 0.991, P 

Abstract Background The development of scoring systems to predict the short-term mortality and the length of hospital stay (LOS) in patients with bacteraemia is essential to improve the quality of care and reduce the occupancy variance in the hospital bed. Methods Adults hospitalised with community-onset bacteraemia in the coronavirus disease 2019 (COVID-19) and pre-COVID-19 eras were captured as the validation and derivation cohorts in the multicentre study, respectively. Model I incorporated all variables available on day 0, Model II incorporated all variables available on day 3, and Models III, IV, and V incorporated the variables that changed from day 0 to day 3. This study adopted the statistical and machine learning (ML) methods to jointly determine the prediction performance of these models in two study cohorts. Results A total of 3,639 (81.4%) and 834 (18.6%) patients were included in the derivation and validation cohorts, respectively. Model IV achieved the best performance in predicting 30-day mortality in both cohorts. The most frequently identified variables incorporated into Model IV were deteriorated consciousness from day 0 to day 3 and deteriorated respiration from day 0 to day 3. Model V achieved the best performance in predicting LOS in both cohorts. The most frequently identified variables in Model V were deteriorated consciousness from day 0 to day 3, a body temperature ≤ 36.0 °C or ≥ 39.0 °C on day 3, and a diagnosis of complicated bacteraemia. Conclusions For hospitalised adults with community-onset bacteraemia, clinical variables that dynamically changed from day 0 to day 3 were crucial in predicting the short-term mortality and LOS. …

Abstract Background Severe COVID-19 is a disease characterized by profound dysregulation of the innate immune system. There is a need to identify highly reliable prognostic biomarkers that can be rapidly assessed in body fluids for early identification of patients at higher risk for hospitalization and/or death. This study aimed to assess whether differential gene expression of immune response molecules and cellular enzymes, detected in saliva samples of COVID-19 patients, occurs according to disease severity staging. Methods In this cross-sectional study, subjects with a COVID-19 diagnosis were classified as having mild, moderate, or severe disease based on clinical features. Transcripts of genes encoding 6 biomarkers, IL-1β, IL-6, IL-10, C-reactive protein, IDO1 and ACE2, were measured by RT‒qPCR in saliva samples of patients and COVID-19-free individuals. Results The gene expression levels of all 6 biomarkers in saliva were significantly increased in severe disease patients compared to mild/moderate disease patients and healthy controls. A significant strong inverse relationship between oxemia and the level of expression of the 6 biomarkers (Spearman’s correlation coefficient between -0.692 and -0.757; p 

Little is known about the real-world effectiveness of oral antivirals against the SARS-CoV-2 omicron (B.1.1.529) variant. We aimed to assess the clinical effectiveness of two oral antiviral drugs among community-dwelling COVID-19 outpatients in Hong Kong.

Data on the effectiveness of oral antivirals in patients with mild-to-moderate COVID-19 are urgently needed. This retrospective cohort study aimed to evaluate the clinical and virological outcomes associated with molnupiravir or nirmatrelvir-ritonavir use in hospitalised patients with mild-to-moderate COVID-19 during a pandemic wave dominated by the omicron BA.2 subvariant.

The oral protease inhibitor nirmatrelvir has shown substantial efficacy in high-risk, unvaccinated patients infected with the B.1.617.2 (delta) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Data regarding the effectiveness of nirmatrelvir in preventing severe coronavirus disease 2019 (Covid-19) outcomes from the B.1.1.529 (omicron) variant are limited.

Treatment of coronavirus disease 2019 (COVID-19) with nirmatrelvir plus ritonavir (NMV-r) in high-risk nonhospitalized unvaccinated patients reduced the risk of progression to severe disease. However, the potential benefits of NMV-r among vaccinated patients are unclear.

Nirmatrelvir is an orally administered severe acute respiratory syndrome coronavirus 2 main protease (M) inhibitor with potent pan-human-coronavirus activity in vitro.

Coronavirus disease 2019 (Covid-19) disproportionately results in hospitalization or death in older patients and those with underlying conditions. Sotrovimab is a pan-sarbecovirus monoclonal antibody that was designed to prevent progression of Covid-19 in high-risk patients early in the course of disease.

A daily dose with 6 mg of dexamethasone is recommended for up to 10 days in patients with severe and critical COVID-19, but a higher dose may benefit those with more severe disease.

Monoclonal antibodies (mAbs) are laboratory-produced molecules derived from the B cells of an infected host. They are being investigated as a potential therapy for coronavirus disease 2019 (COVID-19).

REGEN-COV (previously known as REGN-COV2), a combination of the monoclonal antibodies casirivimab and imdevimab, has been shown to markedly reduce the risk of hospitalization or death among high-risk persons with coronavirus disease 2019 (Covid-19). Whether subcutaneous REGEN-COV prevents severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and subsequent Covid-19 in persons at high risk for infection because of household exposure to a person with SARS-CoV-2 infection is unknown.

The acute clinical manifestations of COVID-19 have been well characterized, but the post-acute sequelae of this disease have not been comprehensively described. Here we use the national healthcare databases of the US Department of Veterans Affairs to systematically and comprehensively identify 6-month incident sequelae-including diagnoses, medication use and laboratory abnormalities-in patients with COVID-19 who survived for at least 30 days after diagnosis. We show that beyond the first 30 days of illness, people with COVID-19 exhibit a higher risk of death and use of health resources. Our high-dimensional approach identifies incident sequelae in the respiratory system, as well as several other sequelae that include nervous system and neurocognitive disorders, mental health disorders, metabolic disorders, cardiovascular disorders, gastrointestinal disorders, malaise, fatigue, musculoskeletal pain and anaemia. We show increased incident use of several therapeutic agents-including pain medications (opioids and non-opioids) as well as antidepressant, anxiolytic, antihypertensive and oral hypoglycaemic agents-as well as evidence of laboratory abnormalities in several organ systems. Our analysis of an array of prespecified outcomes reveals a risk gradient that increases according to the severity of the acute COVID-19 infection (that is, whether patients were not hospitalized, hospitalized or admitted to intensive care). Our findings show that a substantial burden of health loss that spans pulmonary and several extrapulmonary organ systems is experienced by patients who survive after the acute phase of COVID-19. These results will help to inform health system planning and the development of multidisciplinary care strategies to reduce chronic health loss among individuals with COVID-19.

The degree to which infection with SARS-CoV-2 confers protection towards subsequent reinfection is not well described. In 2020, as part of Denmark's extensive, free-of-charge PCR-testing strategy, approximately 4 million individuals (69% of the population) underwent 10·6 million tests. Using these national PCR-test data from 2020, we estimated protection towards repeat infection with SARS-CoV-2.

The efficacy of interleukin-6 receptor antagonists in critically ill patients with coronavirus disease 2019 (Covid-19) is unclear.

Coronavirus disease 2019 (Covid-19) pneumonia is often associated with hyperinflammation. Despite the disproportionate incidence of Covid-19 among underserved and racial and ethnic minority populations, the safety and efficacy of the anti-interleukin-6 receptor antibody tocilizumab in patients from these populations who are hospitalized with Covid-19 pneumonia are unclear.

Recent data suggest that complications and death from coronavirus disease 2019 (Covid-19) may be related to high viral loads.

The COVID-19 pandemic has created a public health crisis. Because SARS-CoV-2 can spread from individuals with presymptomatic, symptomatic, and asymptomatic infections, the reopening of societies and the control of virus spread will be facilitated by robust population screening, for which virus testing will often be central. After infection, individuals undergo a period of incubation during which viral titers are too low to detect, followed by exponential viral growth, leading to peak viral load and infectiousness and ending with declining titers and clearance. Given the pattern of viral load kinetics, we model the effectiveness of repeated population screening considering test sensitivities, frequency, and sample-to-answer reporting time. These results demonstrate that effective screening depends largely on frequency of testing and speed of reporting and is only marginally improved by high test sensitivity. We therefore conclude that screening should prioritize accessibility, frequency, and sample-to-answer time; analytical limits of detection should be secondary.

Viral epidemics or pandemics of acute respiratory infections (ARIs) pose a global threat. Examples are influenza (H1N1) caused by the H1N1pdm09 virus in 2009, severe acute respiratory syndrome (SARS) in 2003, and coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 in 2019. Antiviral drugs and vaccines may be insufficient to prevent their spread. This is an update of a Cochrane Review published in 2007, 2009, 2010, and 2011. The evidence summarised in this review does not include results from studies from the current COVID-19 pandemic.

The efficacy of interleukin-6 receptor blockade in hospitalized patients with coronavirus disease 2019 (Covid-19) who are not receiving mechanical ventilation is unclear.

Severe pneumonia with hyperinflammation and elevated interleukin-6 is a common presentation of coronavirus disease 2019 (COVID-19).

The coronavirus disease 2019 (COVID-19) pandemic is threatening billions of people worldwide. Tocilizumab has shown promising results in retrospective studies in patients with COVID-19 pneumonia with a good safety profile.

Population-level knowledge on individuals at high risk of severe and fatal coronavirus disease 2019 (COVID-19) is urgently needed to inform targeted protection strategies in the general population.

This is the thirteenth version (twelfth update) of the living guideline, replacing earlier versions (available as data supplements). New recommendations will be published as updates to this guideline.

Remdesivir demonstrated clinical benefit in a placebo-controlled trial in patients with severe coronavirus disease 2019 (COVID-19), but its effect in patients with moderate disease is unknown.

Coronavirus disease 2019 (Covid-19) is associated with diffuse lung damage. Glucocorticoids may modulate inflammation-mediated lung injury and thereby reduce progression to respiratory failure and death.

Remdesivir is an RNA polymerase inhibitor with potent antiviral activity in vitro and efficacy in animal models of coronavirus disease 2019 (Covid-19).

Although several therapeutic agents have been evaluated for the treatment of coronavirus disease 2019 (Covid-19), no antiviral agents have yet been shown to be efficacious.

The clinical presentation of European patients with mild-to-moderate COVID-19 infection is still unknown.

There is no specific antiviral therapy recommended for coronavirus disease 2019 (COVID-19). In vitro studies indicate that the antiviral effect of chloroquine diphosphate (CQ) requires a high concentration of the drug.

Since the outbreak of coronavirus disease (COVID-19) in Wuhan in December 2019, by March 10, 2020, a total of 80,932 confirmed cases have been reported in China. Two consecutively negative RT-PCR test results in respiratory tract specimens is required for the evaluation of discharge from hospital, and oropharyngeal swabs were the most common sample. However, false negative results occurred in the late stage of hospitalization, and avoiding false negative result is critical essential.

Coronavirus disease 2019 (COVID-19) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus strain disease, has recently emerged in China and rapidly spread worldwide. This novel strain is highly transmittable and severe disease has been reported in up to 16% of hospitalized cases. More than 600,000 cases have been confirmed and the number of deaths is constantly increasing. COVID-19 hospitalized patients, especially those suffering from severe respiratory or systemic manifestations, fall under the spectrum of the acutely ill medical population, which is at increased venous thromboembolism risk. Thrombotic complications seem to emerge as an important issue in patients infected with COVID-19. Preliminary reports on COVID-19 patients' clinical and laboratory findings include thrombocytopenia, elevated D-dimer, prolonged prothrombin time, and disseminated intravascular coagulation. As the pandemic is spreading and the whole picture is yet unknown, we highlight the importance of coagulation disorders in COVID-19 infected patients and review relevant data of previous coronavirus epidemics caused by the severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) and the Middle East Respiratory Syndrome coronavirus (MERS-CoV).

The pandemic of coronavirus disease 2019 (COVID-19) caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents an unprecedented challenge to identify effective drugs for prevention and treatment. Given the rapid pace of scientific discovery and clinical data generated by the large number of people rapidly infected by SARS-CoV-2, clinicians need accurate evidence regarding effective medical treatments for this infection.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of a rapidly spreading illness, Coronavirus Disease 2019 (COVID-19), affecting thousands of people around the world. Urgent guidance for clinicians caring for the sickest of these patients is needed.

No therapeutics have yet been proven effective for the treatment of severe illness caused by SARS-CoV-2.

The 2019 novel coronavirus (2019-nCoV) causing an outbreak of pneumonia in Wuhan, Hubei province of China was isolated in January 2020. This study aims to investigate its epidemiologic history, and analyze the clinical characteristics, treatment regimens, and prognosis of patients infected with 2019-nCoV during this outbreak.