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Genomic surveillance (GS) programmes were crucial in identifying and quantifying the mutating patterns of SARS-CoV-2 during the COVID-19 pandemic. In this work, we develop a Bayesian framework to quantify the relative transmissibility of different variants tailored for regions with limited GS. We use it to study the relative transmissibility of SARS-CoV-2 variants in Chile. Among the 3443 SARS-CoV-2 genomes collected between January and June 2021, where sampling was designed to be representative, the Gamma (P.1), Lambda (C.37), Alpha (B.1.1.7), B.1.1.348, and B.1.1 lineages were predominant. We found that Lambda and Gamma variants' reproduction numbers were 5% (95% CI: [1%, 14%]) and 16% (95% CI: [11%, 21%]) larger than Alpha's, respectively. Besides, we observed a systematic mutation enrichment in the Spike gene for all circulating variants, which strongly correlated with variants' transmissibility during the studied period (r = 0.93, p-value = 0.025). We also characterised the mutational signatures of local samples and their evolution over time and with the progress of vaccination, comparing them with those of samples collected in other regions worldwide. Altogether, our work provides a reliable method for quantifying variant transmissibility under subsampling and emphasises the importance of continuous genomic surveillance., (© 2024. The Author(s).)

Without a cure, vaccine, or proven long-term immunity against SARS-CoV-2, test-trace-and-isolate (TTI) strategies present a promising tool to contain its spread. For any TTI strategy, however, mitigation is challenged by pre- and asymptomatic transmission, TTI-avoiders, and undetected spreaders, which strongly contribute to "hidden" infection chains. Here, we study a semi-analytical model and identify two tipping points between controlled and uncontrolled spread: (1) the behavior-driven reproduction number [Formula: see text] of the hidden chains becomes too large to be compensated by the TTI capabilities, and (2) the number of new infections exceeds the tracing capacity. Both trigger a self-accelerating spread. We investigate how these tipping points depend on challenges like limited cooperation, missing contacts, and imperfect isolation. Our results suggest that TTI alone is insufficient to contain an otherwise unhindered spread of SARS-CoV-2, implying that complementary measures like social distancing and improved hygiene remain necessary.

During the COVID-19 pandemic, many advocacy groups and individuals criticized governments on social media for doing either too much or too little to mitigate the pandemic. In this article, we review advocacy for COVID-19 elimination or "zero-covid" on the social media platform X (Twitter). We present a thematic analysis of tweets by 20 influential co-signatories of the World Health Network letter on ten themes, covering six topics of science and mitigation (zero-covid, epidemiological data on variants, long-term post-acute sequelae (Long COVID), vaccines, schools and children, views on monkeypox/Mpox) and four advocacy methods (personal advice and promoting remedies, use of anecdotes, criticism of other scientists, and of authorities). The advocacy, although timely and informative, often appealed to emotions and values using anecdotes and strong criticism of authorities and other scientists. Many tweets received hundreds or thousands of likes. Risks were emphasized about children's vulnerability, Long COVID, variant severity, and Mpox, and via comparisons with human immunodeficiency viruses (HIV). Far-reaching policies and promotion of remedies were advocated without systematic evidence review, or sometimes, core field expertise. We identified potential conflicts of interest connected to private companies. Our study documents a need for public health debates to be less polarizing and judgmental, and more factual. In order to protect public trust in science during a crisis, we suggest the development of mechanisms to ensure ethical guidelines for engagement in "science-based" advocacy, and consideration of cost-benefit analysis of recommendations for public health decision-making., Competing Interests: Declarations. Competing interests: The authors do research in public health, epidemiology, biochemistry, virology, biostatistics, policy, politics, education and student experience, pediatrics, mathematical modeling, data science, and psychology relevant to the claims made by the studied advocacy in the paper but with no direct association to the studied advocacy. Kasper P. Kepp has unpaid research affiliations with METRICS, Stanford, and Epistudia, Bern, has published or submitted a dozen papers on COVID-19-related research (SARS-CoV-2 mutation evolution, public health, and epidemiology), has been engaged in the pandemic debate in Danish media and social media, where he has been critical of the studied zero-covid groups, and is without any financial conflicts of interests. Kevin Bardosh is Director of Collateral Global, a UK-based research and education charity that is focused on understanding the impact of COVID policies around the world, and has been active in the pandemic debate on social media and in the popular press. Tijl De Bie was an active participant in the pandemic debate in the Belgian media, on social media, and in personal conversations, and is without any financial conflicts of interests. He has co-led the writing of the so-called Wintermanifesto, a public call for a more sustainable pandemic policy in Belgium, supported by around 100 Belgian academics and other public figures and published in January 2022. Also in January 2022, he was heard as an expert in the Belgian federal parliament regarding a possible Covid19-vaccination mandate. During the pandemic, he took part in exploratory conversations with Johnson & Johnson about a possible academic collaboration unrelated to COVID-19, for which he received no compensation of any kind. Louise Emilsson works as head and senior consultant at a primary care practice in Region Värmland, Sweden. She is also Associate Professor at Oslo University, affiliated to Karolinska Institutet and has published several papers on COVID. She has no financial conflict of interest. Justin Greaves is Director of Student Experience and Progression in the Department of Politics and International Studies at the University of Warwick. He has engaged in the pandemic debate on social media. His research background includes work on a Rural Economy and Land Use (RELU) funded project on the Governance of Livestock Diseases (2007-2010). The Principal Investigator of this project was Graham Medley, currently Chair of the SPI-M modelling sub-committee of the Scientific Advisory Group for Emergencies (Sage), in the UK. Tea Lallukka has provided an invited report for the Committee for the Future (an established, standing committee in the Parliament of Finland) in late 2022, where she was asked to describe the future of public health. Her report covered e.g. inequalities in health, population aging, oral health, mental health, COVID-19 and potential new pandemics. Taulant Muka is co-founder, co-owner, and CEO at Epistudia GmbH, acts as unpaid advisor for the Academic Parity Movement, a non-profit organization uprooting academic bullying, discrimination, and violence and has written systematic reviews and meta-analyses on Covid-19 related topics. He received research funds from Merz Aesthetics not related to this work. In addition, he has written a book on academic silencing and mobbing during the Covid-19 pandemic (ISBN-13. ‎979-8801214009). J. Cristian Rangel, PhD. is the PI in a Social Sciences and Humanities Research Council (SSHRC) funded project mapping scientific networks influencing Public Health pandemic response in Ontario, Canada. He’s also a co-PI in a New Frontiers SSHRC grant studying the social effects of pandemic response in Canada and selected countries. He has been engaged in public critique on the role of academics in pandemic response. Michaéla Schippers is founder of Ikigaitv.nl: positive psychology interventions for the general public, to enhance mental wellbeing and co-founder of Great Citizens Movement (greatcitizensmovement.org). She also served as expert witness of extra-parliamentary inquiry regarding the COVID-19 crisis handling in the Netherlands (2020); she signed the Great Barrington declaration and owns the podcast followthescience.nl and does contract research on improving study success: https://www.erim.eur.nl/erasmus-centre-for-study-and-career-success/ . Jonas Schmidt-Chanasit declares that the following conflicts of interest may exist, which may result from an employment relationship, a shareholding, a consultancy activity or grants for research projects, lectures or other activities: Blusense Diagnostics, Mahidol University, Vietnam Military Medical University, Deutsche Forschungsgemeinschaft (DFG), Bundesministerium für Bildung und Forschung (BMBF), Bundesministerium für Gesundheit (BMG), Bundesministerium für Ernährung und Landwirtschaft (BMEL), Instand e.V., Auswärtiges Amt, QCMD, Takeda, AstraZeneca, Pfizer, Wynn Macau, Sonic Healthcare, Chulalongkorn University, Valneva, Bavarian Nordic, Hermes Arzneimittel, CRM - Centrum für Reisemedizin, Johnson & Johnson, EUROIMMUN, BASF, Siemens, Roche, Bangkok Bank, China Construction Bank, Deutsche Bank, Diasorin, Sanofi, and Mikrogen. He is an active participant in the pandemic debate in the German media, on social media (X), and advised the Government of the City of Hamburg during the COVID-19 pandemic. Tracy Vaillancourt is the Chair of the COVID-19 Task Force for the Royal Society of Canada (RSC). She also chaired the RSC’s Children and Schools Policy Report which covered all aspects of education during the COVID-19 pandemic. She is the current chair of the Canada Learning Loss Policy Report in partnership with the RSC and the Canadian Commission UNESCO, which is funded by the Social Sciences and Humanities Research Council (Canada). She provided consultation to the Canadian government on education, child development, and behavioural sciences during the pandemic. She is the president of the International Society for Research on Aggression, a Senior Fellow of the Centre for International Governance Innovation, a member of the National Expert Committee on Countering Radicalization to Violence, Government of Canada, and the Chief Editor, Frontiers in Child and Adolescent Psychiatry – Child Mental Health and Interventions Ethics approval: No ethics approval was obtained as all data studied in the paper are fully available in public., (© 2024. The Author(s) under exclusive licence to Monash University.)

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is the ongoing global pandemic that poses substantial challenges to public health worldwide. A subset of COVID-19 patients experience systemic inflammatory response, known as cytokine storm, which may lead to death. Receptor-interacting serine/threonine-protein kinase 1 (RIPK1) is an important mediator of inflammation and cell death. Here, we examined the interaction of RIPK1-mediated innate immunity with SARS-CoV-2 infection. We found evidence of RIPK1 activation in human COVID-19 lung pathological samples, and cultured human lung organoids and ACE2 transgenic mice infected by SARS-CoV-2. Inhibition of RIPK1 using multiple small-molecule inhibitors reduced the viral load of SARS-CoV-2 in human lung organoids. Furthermore, therapeutic dosing of the RIPK1 inhibitor Nec-1s reduced mortality and lung viral load, and blocked the CNS manifestation of SARS-CoV-2 in ACE2 transgenic mice. Mechanistically, we found that the RNA-dependent RNA polymerase of SARS-CoV-2, NSP12, a highly conserved central component of coronaviral replication and transcription machinery, promoted the activation of RIPK1. Furthermore, NSP12 323L variant, encoded by the SARS-CoV-2 C14408T variant first detected in Lombardy, Italy, that carries a Pro323Leu amino acid substitution in NSP12, showed increased ability to activate RIPK1. Inhibition of RIPK1 downregulated the transcriptional induction of proinflammatory cytokines and host factors including ACE2 and EGFR that promote viral entry into cells. Our results suggest that SARS-CoV-2 may have an unexpected and unusual ability to hijack the RIPK1-mediated host defense response to promote its own propagation and that inhibition of RIPK1 may provide a therapeutic option for the treatment of COVID-19., (© 2021. The Author(s).)

We conducted a longitudinal cohort study of SARS-CoV-2 and influenza rates in childcare centers and schools in Wuxi, China, collecting 1,760 environmental samples and 9,214 throat swabs from 593 students (regardless of symptoms) in weekly collections during February–June 2023. We estimated a cumulative infection rate of 124.8 (74 episodes)/1,000 persons for SARS-CoV-2 and 128.2 (76 episodes)/1,000 persons for influenza. The highest SARS-CoV-2 infection rate was in persons 18 years of age, and for influenza, in children 4 years of age. The asymptomatic proportion of SARS-CoV-2 was 59.6% and 66.7% for influenza; SARS-CoV-2 symptomatic proportion was lower in 16–18-year-olds than in 4–6-year-olds. Only samples from frequently touched surface tested positive for SARS-CoV-2 (4/1,052) and influenza (1/1,052). We found asynchronous circulation patterns of SARS-CoV-2 and influenza, similar to trends in national sentinel surveillance. The results support vaccination among pediatric populations and other interventions, such as environmental disinfection in educational settings. [ABSTRACT FROM AUTHOR]

Background: Conflicting evidence exists regarding the effects of ursodeoxycholic acid (UDCA) on coronavirus disease 2019 (COVID-19). This study investigates the association between UDCA administration and COVID-19 infection and its related outcomes in individuals with chronic liver disease (CLD). Methods: A customized COVID-19 research database (n = 3,485,376) was created by integrating data from the National Health Insurance Service (NHIS) and the Korea Disease Control and Prevention Agency's COVID-19 databases. The study focused on patients diagnosed with COVID-19 in 2021, using the NHIS data from 365 days before diagnosis. To create comparable groups with and without UDCA administration before COVID-19, we used propensity score matching. The primary endpoint was the first confirmed positive result for severe acute respiratory syndrome coronavirus-2. In addition, we identified severe COVID-19-related outcomes. Subgroup analysis were conducted based on the dose of UDCA exposure. Results: Data from 74,074 individuals with CLD was analyzed. The participants' average age was 57.5 years, and 52.1% (19,277) of those in each group were male. Those with prior UDCA exposure had a significantly lower risk of COVID-19 infection (adjusted OR: 0.80, 95% CI [0.76–0.85]) compared to the non-UDCA group. Additionally, the UDCA group had a lower risk of severe COVID-19 outcomes (adjusted OR: 0.67, 95% CI [0.46–0.98]). Subgroup analyses indicated that there was a decrease in COVID-19 infection and its related outcomes with increasing UDCA exposure dose. Conclusions: Our large observational study highlights the potential use of readily available UDCA as an adjunctive therapy for COVID-19 in individuals with CLD. [ABSTRACT FROM AUTHOR]

Background: Long-lasting symptoms with a possible relation to psychosomatic comorbidity have been described following COVID-19. However, data is sparse in general practice. The trial's objective was to investigate the time-dependent frequency of disease symptoms and relation to psychosomatic comorbidity and daily life impairment (DLI). Methods: Comparative cohort study of patients reporting a previous SARS-CoV-2 infection and uninfected controls in general practice. Participants were recruited in 14 general practices in the greater Munich area. Data collection was questionnaire based with a 12 months follow-up. Descriptive statistics, multivariable regression and bivariate correlations were used for analysis. Results: A total of n = 204 cases infected up to 42 months ago (n = 141 Omicron, n = 63 earlier variants), and n = 119 controls were included. Disease symptoms were substantially more prevalent in cases (55–79% vs. 43% within one year of infection). This difference also appeared in the multivariable analysis adjusting for socio-demographics and psychosomatic comorbidity with odds ratios (OR) of 4.15 (p < 0.001) and 3.51 (p = 0.054) for the cohorts with Omicron or earlier variants infection (vs. controls), respectively. It was persistent with earlier variants (OR 1.00 per month, p = 0.903), while a decreasing trend was observed for Omicron (OR 0.89 per month, p < 0.001). DLI was especially correlated with fatigue (r = 0.628). Conclusion: DLI, psychosomatic comorbidity and independently increased disease symptoms require holistic treatment of the patient in general practice according to the bio-psycho-social model. A key role in restoring the daily life capability may be attributed to the symptom fatigue. [ABSTRACT FROM AUTHOR]

The surface spike (S) glycoprotein mediates cell entry of SARS-CoV-2 into the host through fusion at the plasma membrane or endocytosis. Omicron lineages/sublineages have acquired extensive mutations in S to gain transmissibility advantages and altered antigenicity. The fusogenicity, antigenicity, and evasion of Omicron subvariants have been extensively investigated at unprecedented speed to align with the mutation rate of S. Cells that overexpress receptors/cofactors are mostly used as hosts to amplify infection sensitivity to tested variants. However, systematic cell entry comparisons of most prior dominant Omicron subvariants using human lung epithelium cells are yet to be well-studied. Here, with human bronchial epithelium BEAS-2B cells as the host, we compared single-round virus-to-cell entry and cell-to-cell fusion of Omicron BA.1, BA.5, BQ.1.1, CH.1.1, XBB.1.5, and XBB.1.16 based upon split NanoLuc fusion readout assays and the S-pseudotyped lentivirus system. Virus-to-cell entry of tested S variants exhibited cell-type dependence. The parental Omicron BA.1 required more time to develop full entry to HEK293T-ACE2-TMPRSS2 than BEAS-2B cells. Compared to unchanged P681, S-cleavage constructs of P681H/R did not have any noticeable advantages in cell entry. Omicron BA.1 and its descendants entered BEAS-2B cells more efficiently than D614G, and it was slightly less or comparable to that of Delta. Serine protease-pretreated Omicron subvariants enhanced virus-to-cell entry in a dose-dependent manner, suggesting fusion at the plasma membrane persists as a productive cell entry route. Spike-mediated cell-to-cell fusion and total S1/S2 processing of Omicron descendants were similar. Our results indicate no obvious entry or fusion advantages of recent Omicron descendants over preceding variants since Delta, thus supporting immune evasion conferred by antigenicity shifts due to altered S sequences as probably the primary viral fitness driver. [ABSTRACT FROM AUTHOR]

We conduct a large (N = 6567) online experiment to measure the features of non-pharmaceutical interventions (NPIs) that citizens of six European countries perceive to lower the risk of transmission of SARS-Cov-2 the most. We collected data in Bulgaria (n = 1069), France (n = 1108), Poland (n = 1104), Italy (n = 1087), Spain (n = 1102) and Sweden (n = 1097). Based on the features of the most widely adopted public health guidelines to reduce SARS-Cov-2 transmission (mask wearing vs not, outdoor vs indoor contact, short vs 90 min meetings, few vs many people present, and physical distancing of 1 or 2 m), we conducted a discrete choice experiment (DCE) to estimate the public's perceived risk of SARS-CoV-2 transmission in scenarios that presented mutually exclusive constellations of these features. Our findings indicate that participants' perception of transmission risk was most influenced by the NPI attributes of mask-wearing and outdoor meetings and the least by NPI attributes that focus on physical distancing, meeting duration, and meeting size. Differentiating by country, gender, age, cognitive style (reflective or intuitive), and perceived freight of COVID-19 moreover allowed us to identify important differences between subgroups. Our findings highlight the importance of improving health policy communication and citizens' health literacy about the design of NPIs and the transmission risk of SARS-Cov-2 and potentially future viruses. [ABSTRACT FROM AUTHOR]

Describing viral outbreaks, such as the COVID-19 pandemic, often involves employing compartmental models composed of ordinary differential equation (ODE) systems. Estimating the parameter values for these ODE models is crucial and relies on accessible data. To accurately represent realistic pandemic scenarios with diverse situations, it is necessary to consider model parameters as time dependent. However, estimating such time-dependent parameters, like transition rates in compartmental models, is notoriously challenging due to the unknown function class of these parameters. In this study, we propose a novel approach by using an Augmented Kalman Smoother (AKS) combined with an Expectation-Maximization (EM) algorithm to simultaneously estimate all time-dependent parameters in an SIRD compartmental model. Our approach can be applied to general ODE systems with time-varying parameters, requiring no prior knowledge of model parameters or additional assumptions on the function class of the ODE time dependencies. A key advantage of our method compared to other methods is that it does not require assumptions about the parameterization of the serial interval distribution for estimating SIRD model parameters. Applying our approach to COVID-19 data in Germany, we adequately describe time-series data with strong fluctuations and multiple waves, obtaining non-parametric model-based time-course estimates for the effective reproduction number. [ABSTRACT FROM AUTHOR]

The occurrence of SARS-CoV-2 infections during the pandemic was mainly based on PCR testing of symptomatic patients. However, with new variants, vaccinations, and the changing of the clinical disease severity, knowledge about general immunity is elusive. For public health systems, timely knowledge of these conditions is essential, but it is particularly scarce for the pediatric population. Therefore, in this study, we wanted to investigate the spike and nucleocapsid seroprevalence in pediatric patients using routine residual blood tests collected during the pandemic. This prospective observational study was conducted over seven one-month periods. Herein, the latest four time periods (November 2021, January 2022, March 2022, and May 2022) are depicted. Each patient of a tertiary-care center in Germany was anonymized after collection of clinical diagnosis (ICD-10) and then routinely tested for the respective spike and nucleocapsid SARS-CoV-2 antibody titer. A total of 3235 blood samples from four time periods were included. Spike seroprevalence rose from 37.6% to 51.9% to 70.5% to 85.1% and nucleocapsid seroprevalence from 11.6% to 17.0% to 36.7% to 58.1% in May 2022. In detail, significant changes in seroprevalence between age groups but not between sex or diagnosis groups were found. Quantitative measures revealed rising spike and constant nucleocapsid antibody levels over the pandemic with a half-life of 102 days for spike and 45 days for nucleocapsid antibodies. Routine laboratory assessment of SARS-CoV-2 in residual blood specimens of pediatric hospitals enables monitoring of the seroprevalence and may allow inferences about general immunity in this cohort. [ABSTRACT FROM AUTHOR]

The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a global threat. Despite strict control measures implemented worldwide and immunization using novel vaccines, the pandemic continues to rage due to emergence of several variants of SARS-CoV-2 with increased transmission and immune escape. The rapid spread of variants of concern (VOC) in the recent past has created a massive challenge for the control of COVID-19 pandemic via the currently used vaccines. Vaccines that are safe and effective against the current and future variants of SARS-CoV-2 are essential in controlling the COVID-19 pandemic. Rapid production and massive rollout of next-generation vaccines against the variants are key steps to control the COVID-19 pandemic and to help us return to normality. Coordinated surveillance of SARS-CoV-2, rapid redesign of new vaccines and extensive vaccination are needed to counter the current SARS-CoV-2 variants and prevent the emergence of new variants. In this article, we review the latest information on the VOCs and variants of interest (VOIs) and present the information on the clinical trials that are underway on evaluating the effectiveness of COVID-19 vaccines on VOCs. We also discuss the current challenges posed by the VOCs in controlling the COVID-19 pandemic and future strategies to overcome the threat posed by the highly virulent and rapidly transmissible variants of SARS-CoV2. The COVID-19 is a contagious respiratory disease caused by a virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that emerged in 2019. The COVID-19 has now spread to all part of the world and has become a global threat. Even after the strict control measures and immunization programs to prevent the disease, COVID-19 is still causing destruction due to appearance of new strains of SARS-CoV-2 that transmit faster and capable of escaping the immunity. The faster spread of the new strains of viruses that cause more severe disease is the biggest challenge to control the COVID-19 pandemic by using the presently available vaccines. To control the COVID-19 pandemic we urgently need safe and effective vaccines against the corona viral variants. This can be achieved by tracking the appearance of new viral types, design and rapid production and supply of new vaccines against the virus. This article presents the latest information on the new types of SARS-CoV-2, and on the status of vaccine trials and their effectiveness against these viruses. Similarly, the information on the challenges posed by the new viral strains in controlling the COVID-19 and future strategies to overcome the threat posed by corona viruses is also provided. [ABSTRACT FROM AUTHOR]

Background: Recent studies have raised the issue of delayed cancer care during the COVID-19 pandemic, but the extent of delays and cancellations in cancer treatment, screening and diagnosis varied widely by geographic region and study design, highlighting the need for further research. Methods: We used the Oncology Dynamics (OD) database featuring data from a cross-sectional, partially retrospective survey to analyze treatment delays in 30,171 GI cancer patients from five European countries (Germany, France, UK, Spain, and Italy). Risk factors for treatment delays were identified using multivariable logistic regression models. Results: Treatment delays were documented in 1342 (4.5%) of the study patients, with most patients having a delay of less than 3 months (3.2%). We observed decisive differences of treatment delay in relation to geographical, healthcare- and patient-related factors. Treatment delay was highest in France (6.7%) and Italy (6.5%) and lowest in Spain (1.9%, p < 0.001). 5.9% of patients treated at general hospitals but only 1.9% of those treated by office-based physicians experienced treatment delays (p < 0.001). Moreover, the difference between lines of therapy was highly significant and ranged from 7.2% for early-stage patients in primary therapy to 2.6% in advanced/metastatic cancer patients receiving 4th or later line therapy (p < 0.001). Finally, the proportion of cases with delayed treatments increased from 3.5% in asymptomatic patients (ECOG 0) to 9.9% in bedridden patients (ECOG IV, p < 0.001). Results were confirmed in multivariable logistic regression models. Summary: Our data highlight the problem of delayed treatment of tumor patients in the context of the COVID-19 pandemic. Identified risk factors for delayed treatment, such as poor general health or treatment in smaller hospitals, offer starting points for future concepts of "pandemic preparedness". [ABSTRACT FROM AUTHOR]

The coronavirus SARS-CoV-2 has highlighted the criticality of an accurate and rapid diagnosis in order to contain the spread of the virus. Knowledge of the viral structure and its genome is essential for diagnosis development. The virus is still quickly evolving and the global scenario could easily change. Thus, a greater range of diagnostic options is essential to face this threat to public health. In response to the global demand, there has been a rapid advancement in the understanding of current diagnostic methods. In fact, innovative approaches have emerged, leveraging the benefits of nanomedicine and microfluidic technologies. Although this development has been incredibly fast, several key areas require further investigation and optimization, such as sample collection and preparation, assay optimization and sensitivity, cost effectiveness, scalability device miniaturization, and portability and integration with smartphones. Addressing these gaps in the knowledge and these technological challenges will contribute to the development of reliable, sensitive, and user-friendly NAAT-based POCTs for the diagnosis of SARS-CoV-2 and other infectious diseases, facilitating rapid and effective patient management. This review aims to provide an overview of current SARS-CoV-2 detection methods based on nucleic acid detection tests (NAATs). Additionally, it explores promising approaches that combine nanomedicine and microfluidic devices with high sensitivity and relatively fast 'time to answer' for integration into point-of-care testing (POCT). [ABSTRACT FROM AUTHOR]

In this study, the intrinsic surface-enhanced Raman spectroscopy (SERS)-based approach coupled with chemometric analysis was adopted to establish the biochemical fingerprint of SARS-CoV-2 infected human fluids: saliva and nasopharyngeal swabs. The numerical methods, partial least squares discriminant analysis (PLS-DA) and support vector machine classification (SVMC), facilitated the spectroscopic identification of the viral-specific molecules, molecular changes, and distinct physiological signatures of pathetically altered fluids. Next, we developed the reliable classification model for fast identification and differentiation of negative CoV(−) and positive CoV(+) groups. The PLS-DA calibration model was described by a great statistical value—RMSEC and RMSECV below 0.3 and R2cal at the level of ~0.7 for both type of body fluids. The calculated diagnostic parameters for SVMC and PLS-DA at the stage of preparation of calibration model and classification of external samples simulating real diagnostic conditions evinced high accuracy, sensitivity, and specificity for saliva specimens. Here, we outlined the significant role of neopterin as the biomarker in the prediction of COVID-19 infection from nasopharyngeal swab. We also observed the increased content of nucleic acids of DNA/RNA and proteins such as ferritin as well as specific immunoglobulins. The developed SERS for SARS-CoV-2 approach allows: (i) fast, simple and non-invasive collection of analyzed specimens; (ii) fast response with the time of analysis below 15 min, and (iii) sensitive and reliable SERS-based screening of COVID-19 disease. [ABSTRACT FROM AUTHOR]

Aim: To use a Delphi-panel-based assessment of the effectiveness of different non-pharmaceutical interventions (NPI) in order to retrospectively approximate and to prospectively predict the SARS-CoV-2 pandemic progression via a SEIR model (susceptible, exposed, infectious, removed). Methods: We applied an evidence-educated Delphi-panel approach to elicit the impact of NPIs on the SARS-CoV-2 transmission rate R0 in Germany. Effectiveness was defined as the product of efficacy and compliance. A discrete, deterministic SEIR model with time step of 1 day, a latency period of 1.8 days, duration of infectiousness of 5 days, and a share of the total population of 15% assumed to be protected by immunity was developed in order to estimate the impact of selected NPI measures on the course of the pandemic. The model was populated with the Delphi-panel results and varied in sensitivity analyses. Results: Efficacy and compliance estimates for the three most effective NPIs were as follows: test and isolate 49% (efficacy)/78% (compliance), keeping distance 42%/74%, personal protection masks (cloth masks or other face masks) 33%/79%. Applying all NPI effectiveness estimates to the SEIR model resulted in a valid replication of reported occurrence of the German SARS-CoV-2 pandemic. A combination of four NPIs at consented compliance rates might curb the CoViD-19 pandemic. Conclusion: Employing an evidence-educated Delphi-panel approach can support SARS-CoV-2 modelling. Future curbing scenarios require a combination of NPIs. A Delphi-panel-based NPI assessment and modelling might support public health policy decision making by informing sequence and number of needed public health measures. [ABSTRACT FROM AUTHOR]

China is experiencing the same situation that we observed in Europe at the beginning of 2022, where all cases are due the Omicron-related variants and recombinations. Transmission dynamics of SARS-CoV-2 Omicron variant infections in Hangzhou, Zhejiang, China, January-February 2022. Figure 1 summarizes the distribution of the observed lineages in the last few weeks in Europe, USA, Italy, and China. Is a new COVID-19 wave coming from China due to an unknown variant of concern?. [Extracted from the article]

As coronavirus variants are constantly occurring, we tried to understand more about the omicron and delta variants that have hit the world. We provided dynamic information on the case fatality rate (CFR) of the Omicron variant over time and to compare it with that of the Delta variant through meta‐analysis. Twenty‐four countries were selected by submission counts, submission dates, and confirmed cases. We defined the Delta or the Omicron epidemic period for individual countries as when each variant is over 90%. We further analyzed the Omicron period by dividing it into the initial plateau, increasing, and decreasing phases according to the number of newly confirmed daily cases. Finally, the meta‐analysis examined the summary and between‐study heterogeneity. The CFR of COVID‐19 during the Omicron epidemic was lower than that during the Delta epidemic (odds ratio [OR]: 0.252, 95% confidence interval [CI] 0.205−0.309). The CFR of COVID‐19 during the initial plateau phase of Omicron was higher than during other phases. (OR: 1.962, 95% CI 1.607−2.397). The CFR of COVID‐19 during the increasing phase was lower than during the decreasing phases (OR: 0.412, 95% CI 0.342–0.498). The Omicron variant had lower CFR compared to the Delta variant, and the initial plateau phase had higher CFR compared to the noninitial phases. These results can help establish global health policies for COVID‐19 in the future. [ABSTRACT FROM AUTHOR]

Reverse transcription polymerase chain reaction (RT-PCR) on respiratory tract swabs has become the gold standard for sensitive and specific detection of influenza virus, respiratory syncytial virus (RSV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this retrospective analysis, we report on the successive implementation and routine use of multiplex RT-PCR testing for patients admitted to the Internal Medicine Emergency Department (ED) at a tertiary care center in Western Austria, one of the hotspots in the early coronavirus disease 2019 (COVID-19) pandemic in Europe. Our description focuses on the use of the Cepheid® Xpert® Xpress closed RT-PCR system in point-of-care testing (POCT). Our indications for RT-PCR testing changed during the observation period: From the cold season 2016/2017 until the cold season 2019/2020, we used RT-PCR to diagnose influenza or RSV infection in patients with fever and/or respiratory symptoms. Starting in March 2020, we used the RT-PCR for SARS-CoV-2 and a multiplex version for the combined detection of all these three respiratory viruses to also screen subjects who did not present with symptoms of infection but needed in-hospital medical treatment for other reasons. Expectedly, the switch to a more liberal RT-PCR test strategy resulted in a substantial increase in the number of tests. Nevertheless, we observed an immediate decline in influenza virus and RSV detections in early 2020 that coincided with public SARS-CoV-2 containment measures. In contrast, the extensive use of the combined RT-PCR test enabled us to monitor the re-emergence of influenza and RSV detections, including asymptomatic cases, at the end of 2022 when COVID-19 containment measures were no longer in place. Our analysis of PCR results for respiratory viruses from a real-life setting at an ED provides valuable information on the epidemiology of those infections over several years, their contribution to morbidity and need for hospital admission, the risk for nosocomial introduction of such infection into hospitals from asymptomatic carriers, and guidance as to how general precautions and prophylactic strategies affect the dynamics of those infections. [ABSTRACT FROM AUTHOR]

Since the start of the pandemic of COVID-19, it was clear that vaccination was the best way to combat it. A few vaccines were produced and approved in the last year. Many questions about the vaccinations' efficacy and safety arose due to this unprecedented vaccine development effort. This study aimed to evaluate the short-term side effects after receiving the available COVID-19 vaccines by the students of the Kut university college. This research was conducted as a cross-sectional, retrospective study using an online questionnaire distributed among COVID-19 vaccine recipients. The number of students who are enrolled in this study is 804, nearly (81%) of our study subjects were symptomatic after receiving the vaccination. Participants with a history of SARS-CoV-2 infection, comorbid diseases, females, non-smokers, and AstraZeneca vaccine receivers showed significantly (p<0.05) more severe side effects. In conclusion, the side effects described by our undergraduate students after receiving vaccinations from Pfizer BioNTech, Oxford AstraZeneca, and Sinopharm are similar to those reported in clinical trials, showing that these vaccines have safe profiles. More research is needed to assess the efficiency of current vaccinations in preventing SARS-CoV-2 reinfections. [ABSTRACT FROM AUTHOR]

During infectious disease outbreaks, inference of summary statistics characterizing transmission is essential for planning interventions. An important metric is the time-dependent reproduction number (Rt), which represents the expected number of secondary cases generated by each infected individual over the course of their infectious period. The value of Rt varies during an outbreak due to factors such as varying population immunity and changes to interventions, including those that affect individuals' contact networks. While it is possible to estimate a single population-wide Rt, this may belie differences in transmission between subgroups within the population. Here, we explore the effects of this heterogeneity on Rt estimates. Specifically, we consider two groups of infected hosts: those infected outside the local population (imported cases), and those infected locally (local cases). We use a Bayesian approach to estimate Rt, made available for others to use via an online tool, that accounts for differences in the onwards transmission risk from individuals in these groups. Using COVID-19 data from different regions worldwide, we show that different assumptions about the relative transmission risk between imported and local cases affect Rt estimates significantly, with implications for interventions. This highlights the need to collect data during outbreaks describing heterogeneities in transmission between different infected hosts, and to account for these heterogeneities in methods used to estimate Rt. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'. [ABSTRACT FROM AUTHOR]

Using the recently proposed Susceptible–Asymptomatic–Infected–Vaccinated–Removed (SAIVR) model, we study the impact of key factors affecting COVID-19 vaccine rollout effectiveness and the susceptibility to resurgent epidemics. The SAIVR model expands the widely used Susceptible–Infectious–Removed (SIR) model for describing epidemics by adding compartments to include the asymptomatic infected (A) and the vaccinated (V) populations. We solve the model numerically to make predictions on the susceptibility to resurgent COVID-19 epidemics depending on initial vaccination coverage, importation loads, continuing vaccination, and more contagious SARS-CoV-2 variants, under persistent immunity and immunity waning conditions. The parameters of the model represent reported epidemiological characteristics of the SARS-CoV-2 virus such as the disease spread in countries with high levels of vaccination coverage. Our findings help explain how the combined effects of different vaccination coverage levels and waning immunity lead to distinct patterns of resurgent COVID-19 epidemics (either surges or endemic), which are observed in countries that implemented different COVID-19 health policies and achieved different vaccinated population plateaus after the vaccine rollouts in the first half of 2021. [ABSTRACT FROM AUTHOR]

The COVID-19 outbreak seems to be the most dangerous challenge of the third millennium due to its highly contagious nature. Amongst natural molecules for COVID-19 treatment, the flavonoid molecule quercetin (QR) is currently considered one of the most promising. QR is an active agent against SARS and MERS due to its antimicrobial, antiviral, anti-inflammatory, antioxidant, and some other beneficial effects. QR may hold therapeutic potential against SARS-CoV-2 due to its inhibitory effects on several stages of the viral life cycle. In fact, QR inhibits viral entry, absorption, and penetration in the SARS-CoV virus, which might be at least partly explained by the ability of QR and its derivatives to inhibit 3-chymotrypsin-like protease (3CLpro) and papain-like protease (PLpro). QR is a potent immunomodulatory molecule due to its direct modulatory effects on several immune cells, cytokines, and other immune molecules. QR-based nanopreparations possess enhanced bioavailability and solubility in water. In this review, we discuss the prospects for the application of QR as a preventive and treatment agent for COVID-19. Given the multifactorial beneficial action of QR, it can be considered a very valid drug as a preventative, mitigating, and therapeutic agent of COVID-19 infection, especially in synergism with zinc, vitamins C, D, and E, and other polyphenols. [ABSTRACT FROM AUTHOR]

A pandemic poses particular challenges to decision-making because of the need to continuously adapt decisions to rapidly changing evidence and available data. For example, which countermeasures are appropriate at a particular stage of the pandemic? How can the severity of the pandemic be measured? What is the effect of vaccination in the population and which groups should be vaccinated first? The process of decision-making starts with data collection and modeling and continues to the dissemination of results and the subsequent decisions taken. The goal of this paper is to give an overview of this process and to provide recommendations for the different steps from a statistical perspective. In particular, we discuss a range of modeling techniques including mathematical, statistical and decision-analytic models along with their applications in the COVID-19 context. With this overview, we aim to foster the understanding of the goals of these modeling approaches and the specific data requirements that are essential for the interpretation of results and for successful interdisciplinary collaborations. A special focus is on the role played by data in these different models, and we incorporate into the discussion the importance of statistical literacy and of effective dissemination and communication of findings. [ABSTRACT FROM AUTHOR]

We analyze the relaxation of non-pharmaceutical interventions (NPIs) under an increasing number of vaccinations in Germany. For the spread of SARS-CoV-2 we employ a SIR-type model that accounts for age-dependence and includes realistic contact patterns between age groups. The implementation of NPIs occurs on changed contact patterns, improved isolation, or reduced infectiousness when, e.g., wearing masks. We account for spatial heterogeneity and commuting activities in between regions in Germany, and the testing of commuters is considered as a further NPI. We include the ongoing vaccination process and analyze the effect of the B.1.617.2 (Delta) variant, which is considered to be 40%–60% more infectious then the currently dominant B.1.1.7 (Alpha) variant. We explore different opening scenarios under the ongoing vaccination process by assuming that local restrictions are either lifted in early July or August with or without continued wearing of masks and testing. Our results indicate that we can counteract the resurgence of SARS-CoV-2 despite the Delta variant with appropriate timing for the relaxation of NPIs. In all cases, however, school children are hit the hardest. Author summary: One of the greatest challenges within the Covid-19 pandemic is to identify the timing and amount of non-pharmaceutical interventions (face masks, travel bans, school closures, etc). In the year 2021 more and more people are getting vaccinated. When can we finally lift all restrictions and stop wearing masks? In order to provide more insights to this question, we use a mathematical model which is capable of simulating the effects of non-pharmaceutical interventions in Germany while accounting for age-dependent factors as well as commuting activities between regions. We include the vaccination process and analyze the much more infectious Delta coronavirus variant. We simulate scenarios that consider the timing of the return to pre-pandemic contacts as well as when to suspend wearing masks and testing. Our results show that a later opening by 1 August in combination with masks and testing reduces the chance of a further infection wave considerably. From the retrospective view of the revision, we see that the rise in infections at the end of summer could have been well predicted by our scenarios that considered lifting of NPIs in July as it happened in many places. In all of our scenarios, the infection manifests in the younger age groups. [ABSTRACT FROM AUTHOR]

Background: In Italy, the beginning of 2021 was characterized by the emergence of new variants of SARS-CoV-2 and by the availability of effective vaccines that contributed to the mitigation of non-pharmaceutical interventions and to the avoidance of hospital collapse.Methods: We analyzed the COVID-19 propagation in Italy starting from September 2021 with a Susceptible-Exposed-Infected-Recovered (SEIR) model that takes into account SARS-CoV-2 lineages, intervention measures and efficacious vaccines. The model was calibrated with the Bayesian method Conditional Robust Calibration (CRC) using COVID-19 data from September 2020 to May 2021. Here, we apply the Conditional Robustness Analysis (CRA) algorithm to the calibrated model in order to identify model parameters that most affect the epidemic diffusion in the long-term scenario. We focus our attention on vaccination and intervention parameters, which are the key parameters for long-term solutions for epidemic control.Results: Our model successfully describes the presence of new variants and the impact of vaccinations and non-pharmaceutical interventions in the Italian scenario. The CRA analysis reveals that vaccine efficacy and waning immunity play a crucial role for pandemic control, together with asymptomatic transmission. Moreover, even though the presence of variants may impair vaccine effectiveness, virus transmission can be kept low with a constant vaccination rate and low restriction levels.Conclusions: In the long term, a policy of booster vaccinations together with contact tracing and testing will be key strategies for the containment of SARS-CoV-2 spread. [ABSTRACT FROM AUTHOR]

The drivers behind regional differences of SARS-CoV-2 spread on finer spatio-temporal scales are yet to be fully understood. Here we develop a data-driven modelling approach based on an age-structured compartmental model that compares 116 Austrian regions to a suitably chosen control set of regions to explain variations in local transmission rates through a combination of meteorological factors, non-pharmaceutical interventions and mobility. We find that more than 60% of the observed regional variations can be explained by these factors. Decreasing temperature and humidity, increasing cloudiness, precipitation and the absence of mitigation measures for public events are the strongest drivers for increased virus transmission, leading in combination to a doubling of the transmission rates compared to regions with more favourable weather. We conjecture that regions with little mitigation measures for large events that experience shifts toward unfavourable weather conditions are particularly predisposed as nucleation points for the next seasonal SARS-CoV-2 waves. Author summary: How weather modulates the spread of SARS-CoV-2 on fine spatio-temporal scales is still not fully understood. Here we use a controlled regional comparison to isolate the impact of five different meteorological factors, four types of non-pharmaceutical interventions as well as individual-level mobility on transmission rates in Austria. We find that more than 60% of regional variations can be explained by these factors. Temperature and humidity relate inversely with transmission rates whereas cloudiness and precipitation correlate with increasing transmission. We also observe a particularly strong impact of restrictions targeting large events. Our results suggest that a combination of weather shifts towards winter conditions combined with little mitigation measures for large gatherings drive the early growth of seasonal SARS-CoV-2 waves. [ABSTRACT FROM AUTHOR]

Background: Despite the vaccination process in Germany, a large share of the population is still susceptible to SARS-CoV-2. In addition, we face the spread of novel variants. Until we overcome the pandemic, reasonable mitigation and opening strategies are crucial to balance public health and economic interests.Methods: We model the spread of SARS-CoV-2 over the German counties by a graph-SIR-type, metapopulation model with particular focus on commuter testing. We account for political interventions by varying contact reduction values in private and public locations such as homes, schools, workplaces, and other. We consider different levels of lockdown strictness, commuter testing strategies, or the delay of intervention implementation. We conduct numerical simulations to assess the effectiveness of the different intervention strategies after one month. The virus dynamics in the regions (German counties) are initialized randomly with incidences between 75 and 150 weekly new cases per 100,000 inhabitants (red zones) or below (green zones) and consider 25 different initial scenarios of randomly distributed red zones (between 2 and 20% of all counties). To account for uncertainty, we consider an ensemble set of 500 Monte Carlo runs for each scenario.Results: We find that the strength of the lockdown in regions with out of control virus dynamics is most important to avoid the spread into neighboring regions. With very strict lockdowns in red zones, commuter testing rates of twice a week can substantially contribute to the safety of adjacent regions. In contrast, the negative effect of less strict interventions can be overcome by high commuter testing rates. A further key contributor is the potential delay of the intervention implementation. In order to keep the spread of the virus under control, strict regional lockdowns with minimum delay and commuter testing of at least twice a week are advisable. If less strict interventions are in favor, substantially increased testing rates are needed to avoid overall higher infection dynamics.Conclusions: Our results indicate that local containment of outbreaks and maintenance of low overall incidence is possible even in densely populated and highly connected regions such as Germany or Western Europe. While we demonstrate this on data from Germany, similar patterns of mobility likely exist in many countries and our results are, hence, generalizable to a certain extent. [ABSTRACT FROM AUTHOR]

The Bateman linear differential equations describing in time nuclear levels interconnected by transitions (in general, each with its own rate) are adapted to the epidemiology case where only two infection and recovery rates are used. Time‐dependent functions describing successive generations of infected people are thus derived. Closed mathematical expressions allow an easy calculation/prediction of the properties of these generations and therefore of the whole epidemics. The main limitation consists in reaching the point when the number of susceptible to the infection people substantially decreases. As testing ground, reasonable descriptions of the newly registered COVID‐19 cases per day is achieved for Europe and the United States till December 2020, including several so‐called Pandemic waves. The approach of the present work, by using transmission from one generation of infected people to a new generation allows a much more detailed tracking of the Pandemic spread than the approaches used so far. For example, the most widely used Susceptible Infectious Recovered (SIR) models (and their variants) use instead transitions from one big compartment of susceptible people to another new one of infected people followed by recovery leading to a third compartment. Clear correlations are found between features of the Pandemic process and the emergence of new SARS‐CoV‐2 variants, with some of them (especially the α$\alpha$ variant) immediately influencing the spread of the infection disease in the Pandemic wave of Autumn of 2020. [ABSTRACT FROM AUTHOR]

Whole-genome sequencing (WGS) has played a significant role in understanding the epidemiology and biology of SARS-CoV-2 virus. Here, we investigate the use of SARS-CoV-2 WGS in Southeast and East Asian countries as a genomic surveillance during the COVID-19 pandemic. Nottingham–Indonesia Collaboration for Clinical Research and Training (NICCRAT) initiative has facilitated collaboration between the University of Nottingham and a team in the Research Center for Biotechnology, National Research and Innovation Agency (BRIN), to carry out a small number of SARS-CoV-2 WGS in Indonesia using Oxford Nanopore Technology (ONT). Analyses of SARS- CoV-2 genomes deposited on GISAID reveal the importance of clinical and demographic metadata collection and the importance of open access and data sharing. Lineage and phylogenetic analyses of two periods defined by the Delta variant outbreak reveal that: (1) B.1.466.2 variants were the most predominant in Indonesia before the Delta variant outbreak, having a unique spike gene mutation N439K at more than 98% frequency, (2) Delta variants AY.23 sub-lineage took over after June 2021, and (3) the highest rate of virus transmissions between Indonesia and other countries was through interactions with Singapore and Japan, two neighbouring countries with a high degree of access and travels to and from Indonesia. [ABSTRACT FROM AUTHOR]

There is uncertainty about the seroprevalence of anti-SARS-CoV-2 antibodies in the general population of Austria and about the waning of antibodies over time. We conducted a seroepidemiological study between June 2020 and September 2021, enrolling blood donors aged 18–70 years across Tyrol, Austria (participation rate: 84.0%). We analyzed serum samples for antibodies against the spike or the nucleocapsid proteins of SARS-CoV-2. We performed a total of 47,363 samples taken from 35,193 individuals (median age, 43.1 years (IQR: 29.3–53.7); 45.3% women; 10.0% with prior SARS-CoV-2 infection). Seroprevalence increased from 3.4% (95% CI: 2.8–4.2%) in June 2020 to 82.7% (95% CI: 81.4–83.8%) in September 2021, largely due to vaccination. Anti-spike IgG seroprevalence was 99.6% (95% CI: 99.4–99.7%) among fully vaccinated individuals, 90.4% (95% CI: 88.8–91.7%) among unvaccinated individuals with prior infection and 11.5% (95% CI: 10.8–12.3%) among unvaccinated individuals without known prior infection. Anti-spike IgG levels were reduced by 44.0% (95% CI: 34.9–51.7%) at 5–6 months compared with 0–3 months after infection. In fully vaccinated individuals, they decreased by 31.7% (95% CI: 29.4–33.9%) per month. In conclusion, seroprevalence in Tyrol increased to 82.7% in September 2021, with the bulk of seropositivity stemming from vaccination. Antibody levels substantially and gradually declined after vaccination or infection. [ABSTRACT FROM AUTHOR]

Background Mortality is a critical measure of disease impact. The European Union (EU) countries share the same regulatory framework but different implementation policies. Methods We extracted cumulative COVID-19 mortality data across the EU countries. We evaluated the 27 member states using the location quotient (LQ) to adjust for the expected mortality in the whole EU region, where an LQ <1 signifies a more and an LQ >1 a less favorable outcome. We categorized EU members into 3 distinct profiles based on their LQ estimates: favorable profile, LQ ≤0.9; unfavorable profile, LQ >1.10; and average profile, LQ between 0.9 and 1.10. We compared LQ estimates and profiles with the prevaccination era that ended in December 2020 with the COVID-19 vaccine rollout. Results Twelve member states had a favorable profile, 4 had an average profile, and 11 had an unfavorable profile. In quantitative analysis, an improvement (negative LQ difference) was noted across countries with higher vaccination coverage (median, 71% fully vaccinated vs 57% for countries with positive LQ differences). There was a significant negative association between the share of fully vaccinated and LQ changes (ρ = –0.62, P  < .001) and a significant 4-month lag effect. After COVID-19 vaccines became available, 4 countries improved their profile and 5 moved to a worse profile. Conclusions There is significant variability in mortality and impact of COVID-19 between countries, even if they share the same regulatory framework. Extending immunization coverage may lead the transition to a more favorable profile, and alter the trajectory of COVID-19 mortality. [ABSTRACT FROM AUTHOR]

This paper considers the role of school closures in the spread of the SARS-CoV-2 virus. To isolate the impact of the closures from other containment measures and identify a causal effect, we exploit variation in the start and end dates of the summer and fall school holidays across the 16 federal states in Germany using a difference-in-differences design with staggered adoption. We show that neither the summer closures nor the closures in the fall had a significant containing effect on the spread of SARS-CoV-2 among children or a spill-over effect on older generations. There is also no evidence that the return to school at full capacity after the summer holidays increased infections among children or adults. Instead, we find that the number of children infected increased during the last weeks of the summer holiday and decreased in the first weeks after schools reopened, a pattern we attribute to travel returnees. [ABSTRACT FROM AUTHOR]

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In the first quarter of 2020, the COVID-19 pandemic brought the world to a state of paralysis. During this period, humanity saw by far the largest organized travel restrictions and unprecedented efforts and global coordination to contain the spread of the SARS-CoV-2 virus. Using large scale human mobility and fine grained epidemic incidence data, we develop a framework to understand and quantify the effectiveness of the interventions implemented by various countries to control epidemic growth. Our analysis reveals the importance of timing and implementation of strategic policy in controlling the epidemic. We also unearth significant spatial diffusion of the epidemic before and during the lockdown measures in several countries, casting doubt on the effectiveness or on the implementation quality of the proposed Governmental policies. [ABSTRACT FROM AUTHOR]

The article presents the effect of school closure and subsequent reopening on the transmission of COVID-19, by considering Denmark, Norway, Sweden and German states as case studies. Topics include the growth rates in daily hospitalizations or confirmed cases under different interventions, the school closures contribute to a reduction in the growth rate 7 days after implementation, and the large-scale reopening of schools while controlling or suppressing the epidemic appears feasible.

Societal responses crucially shape the course of a pandemic, but are difficult to predict. Mitigation measures such as social distancing are here assumed to minimize a utility function that consists of two conflicting sub-targets, the disease related mortality and the multifaceted consequences of mitigation. The relative weight of the two sub-targets defines the mitigation readiness H, which entails the political, social, and psychological aspects of decision making. The dynamics of social and behavioral mitigation thus follows an adaptive rule, which in turn is mediated by a non-adaptive dynamics of H. This framework for social dynamics is integrated into an epidemiological model and applied to the ongoing SARS-CoV-2 pandemic. Unperturbed simulations accurately reproduce diverse epidemic and mitigation trajectories from 2020 to 2021, reported from 11 European countries, Iran, and 8 US states. High regional variability in the severity and duration of the spring lockdown and in peak mortality rates of the first SARS-CoV-2 wave can be explained by differences in the reconstructed readiness H. A ubiquitous temporal decrease of H has greatly intensified second and third waves and slowed down their decay. The unprecedented skill of the model suggests that the combination of an adaptive and a non-adaptive rule may constitute a more fundamental mode in social dynamics. Its implementation in an epidemic context can produce realistic long-term scenarios relevant for strategic planning, such as on the feasibility of a zero-infection target or on the evolutionary arms race between mutations of SARS-CoV-2 and social responses. [ABSTRACT FROM AUTHOR]

There is a consensus that mass vaccination against SARS-CoV-2 will ultimately end the COVID-19 pandemic. However, it is not clear when and which control measures can be relaxed during the rollout of vaccination programmes. We investigate relaxation scenarios using an age-structured transmission model that has been fitted to age-specific seroprevalence data, hospital admissions, and projected vaccination coverage for Portugal. Our analyses suggest that the pressing need to restart socioeconomic activities could lead to new pandemic waves, and that substantial control efforts prove necessary throughout 2021. Using knowledge on control measures introduced in 2020, we anticipate that relaxing measures completely or to the extent as in autumn 2020 could launch a wave starting in April 2021. Additional waves could be prevented altogether if measures are relaxed as in summer 2020 or in a step-wise manner throughout 2021. We discuss at which point the control of COVID-19 would be achieved for each scenario. Despite the consensus that mass vaccination against SARS-CoV-2 will ultimately end the pandemic, it is not clear when and which control measures can be relaxed during the rollout of vaccination programmes. Here, the authors investigate relaxation scenarios using an age-structured transmission model that has been fitted to data for Portugal. [ABSTRACT FROM AUTHOR]

Background: The infection fatality rate (IFR) of the Coronavirus Disease 2019 (COVID-19) is one of the most discussed figures in the context of this pandemic. In contrast to the case fatality rate (CFR), the IFR depends on the total number of infected individuals - not just on the number of confirmed cases. In order to estimate the IFR, several seroprevalence studies have been or are currently conducted.Methods: Using German COVID-19 surveillance data and age-group specific IFR estimates from multiple international studies, this work investigates time-dependent variations in effective IFR over the course of the pandemic. Three different methods for estimating (effective) IFRs are presented: (a) population-averaged IFRs based on the assumption that the infection risk is independent of age and time, (b) effective IFRs based on the assumption that the age distribution of confirmed cases approximately reflects the age distribution of infected individuals, and (c) effective IFRs accounting for age- and time-dependent dark figures of infections.Results: Effective IFRs in Germany are estimated to vary over time, as the age distributions of confirmed cases and estimated infections are changing during the course of the pandemic. In particular during the first and second waves of infections in spring and autumn/winter 2020, there has been a pronounced shift in the age distribution of confirmed cases towards older age groups, resulting in larger effective IFR estimates. The temporary increase in effective IFR during the first wave is estimated to be smaller but still remains when adjusting for age- and time-dependent dark figures. A comparison of effective IFRs with observed CFRs indicates that a substantial fraction of the time-dependent variability in observed mortality can be explained by changes in the age distribution of infections. Furthermore, a vanishing gap between effective IFRs and observed CFRs is apparent after the first infection wave, while an increasing gap can be observed during the second wave.Conclusions: The development of estimated effective IFR and observed CFR reflects the changing age distribution of infections over the course of the COVID-19 pandemic in Germany. Further research is warranted to obtain timely age-stratified IFR estimates, particularly in light of new variants of the virus. [ABSTRACT FROM AUTHOR]

We present an evaluation of the effectiveness of manual contact tracing compared to bulletin board contact tracing. Classical contact tracing relies on reaching individuals who have been in proximity to an infectious person. A bulletin board approach focuses on identifying locations visited by an infectious person, and then contacting those who were at those locations. We present results comparing their effects on the overall reproductive number as well as the incidence and prevalence of disease. We evaluate them by building a new agent based simulation (ABS) model using the Susceptible Exposed Infectious and Recovered (SEIR) framework for disease spread. We conduct simulation experiments to quantify the effectiveness of these two models of contact tracing by calibrating the model to be compatible with SARS-CoV-2. We find that bulletin board contact tracing gives comparable results in terms of the reproductive number, duration, prevalence and incidence but is less resource intensive, easier to implement and offers a wider range of privacy options. Our experiments show that location-based bulletin board contact tracing can improve manual contact tracing. [ABSTRACT FROM AUTHOR]

A novel coronavirus (COVID‐19) has caused viral pneumonia worldwide, posing a major threat to international health. Our study reports that city lockdown is an effective way to reduce the number of new cases and the nitrogen dioxide (NO2) concentration can be used as an environmental lockdown indicator to evaluate the effectiveness of lockdown measures. The airborne NO2 concentration steeply decreased over the vast majority of COVID‐19‐hit areas since the lockdown. The total number of newly confirmed cases reached an inflection point about two weeks since the lockdown and could be reduced by about 50% within 30 days of the lockdown. The stricter lockdown will help newly confirmed cases to decline earlier and more rapidly, and at the same time, the reduction rate of NO2 concentration will increase. Our research results show that NO2 satellite observations can help decision makers effectively monitor and manage non‐pharmaceutical interventions in the epidemic. Plain Language Summary: Since governments adopted epidemic control measures, NO2 levels in most of the affected regions dropped significantly, and NO2 satellite data can be used as an environmental indicator of lockdown and can help explain the implementation of government non‐pharmaceutical interventions. Key Points: The global airborne NO2 concentration steeply decreased over the vast majority of COVID‐19‐hit areasThe total number of newly confirmed cases reached an inflection point about two weeks after the lockdownNO2 satellite measurement can be adopted as an environmental lockdown indicator [ABSTRACT FROM AUTHOR]

BACKGROUND The novel coronavirus (SARS-CoV-2) emerged as a global threat at the beginning of 2020, spreading around the globe at different times and rates. Within a country, such differences provide the opportunity for strategic allocations of health care resources. OBJECTIVE We aim to provide a tool to estimate and visualize differences in the spread of the pandemic at the subnational level. Specifically, we focus on the case of Italy, a country that has been harshly hit by the virus. METHODS We model the number of SARS-CoV-2 reported cases and deaths as well as the number of hospital admissions at the Italian subnational level with Poisson regression. We employ parametric and nonparametric functional forms for the hazard function. In the parametric approach, model selection is performed using an automatic criterion based on the statistical significance of the estimated parameters and on goodness-of-fit assessment. In the nonparametric approach, we employ out-of-sample forecasting error minimization. RESULTS For each province and region, fitted models are plotted against observed data, demonstrating the appropriateness of the modeling approach. Moreover, estimated counts and rates of change for each outcome variable are plotted on maps of the country. This provides a direct visual assessment of the geographic distribution of risk areas as well as insights on the evolution of the pandemic over time. [ABSTRACT FROM AUTHOR]

The present study investigates essential steps in build‐up of models for description of the spread of infectious diseases. Combining these modules, a SEI3RSD model will be developed, which can take into account a possible passive immunisation by vaccination as well as different durations of latent and incubation periods. Besides, infectious persons with and without symptoms can be distinguished. Due to the current world‐wide SARS‐CoV‐2 pandemic (COVID‐19 pandemic) models for description of the spread of infectious diseases and their application for forecasts have become into the focus of the scientific community as well as of broad public more than usual. Currently, many papers and studies have appeared and appear dealing with the virus SARS‐CoV‐2 and the COVID‐19 disease caused by it. This occurs under medical, virological, economic, sociological and further aspects as well as under mathematical points of view. Concerning the last‐mentioned point, the main focus lies on the application of existing models and their adaptation to data about the course of infection available at the current time. Clearly, the aim is to predict the possible further development, for instance in Germany. It is of particular interest to investigate how will be the influence of political and administrative measures like contact restrictions, closing or rather re‐opening of schools, restaurants, hotels etc. on the course of infection. The steps considered here for building up suitable models are well‐known for long time. However, understandably they will not be dealt with in an extended way in current application‐oriented works. Therefore, it is the aim of this study to present some existing steps of modelling without any pretension of completeness. Thus, on the one hand we give assistance and, on the other hand, we develop a model capable to take already known properties of COVID‐19 as well as a later possible passive immunisation by vaccination and a possible loss of immunity of recovered persons into account. The present study investigates essential steps in build‐up of models for description of the spread of infectious diseases. Combining these modules, a SEI3RSD model will be developed, which can take into account a possible passive immunisation by vaccination as well as different durations of latent and incubation periods. Besides, infectious persons with and without symptoms can be distinguished. Due to the current world‐wide SARS‐CoV‐2 pandemic (COVID‐19 pandemic) models for description of the spread of infectious diseases and their application for forecasts have become into the focus of the scientific community as well as of broad public more than usual.... [ABSTRACT FROM AUTHOR]

Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11–15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health. [ABSTRACT FROM AUTHOR]

Escape variants can cause new waves of COVID-19 outbreaks and put vaccination strategies at risk. To prevent or delay the global spread of these waves, virus mobility needs to be minimised through screening and testing strategies, which should also cover vaccinated people. The costs of these strategies are minimal compared to the costs to health, society and the economy from another wave. [ABSTRACT FROM AUTHOR]

Spread of the severe acute respiratory syndrome coronavirus 2 B.1.1.529 (Omicron) variant, which led to increased global hospitalizations for coronavirus disease 2019, generated concern about immune evasion and the duration of protection from vaccines, and undermined humanity's confidence in ending the epidemic. The sudden mutation and origin of Omicron is even more of a mystery. The article highlights the virological characteristics and possible origins of Omicron and the global threats and challenges it poses, as well as strategies to deal with it. [ABSTRACT FROM AUTHOR]