Developing molecular surveillance of SARS-CoV-2 in the Czech Republic (2021–2022) (preprint)

Molecular surveillance was widely used during the COVID-19 pandemic to rapidly detect emerging variants and monitor the transmission of SARS-CoV-2 within communities. In 2021, the Czech COVID-19 Genomics Consortium (COG-CZ) was set up to coordinate a new SARS-CoV-2 molecular surveillance network. In the Czech Republic, molecular surveillance employed whole genome sequencing (WGS) and variant discrimination polymerase chain reaction (VD-PCR) on samples collected through passive, active and sentinel surveillance. All WGS data was uploaded to GISAID and the PANGO lineages used by GISAID were compared to the main variants determined by VD-PCR. To assess the effectiveness and reliability of the gathered data in adapting pandemic responses, the capabilities and turnaround times of the molecular surveillance methods are evaluated.VD-PCR enabled accurate detection of changes in major variant dominance within 48 h of sample collection during the Delta/Omicron transition. WGS detected novel mutations and infection clusters, including several genetic lineages and clades of the virus, some of which were unique to the Czech Republic, such as AY.20.1. Molecular surveillance informed the implementation of public health measures and contributed to reduced cases and mortality, however further areas for improvement have been identified for monitoring and managing future pandemics.

Tip of the Iceberg: A New Wave of Iron-Sulfur Cluster Proteins Found in Viruses (preprint)

Viruses rely on host cells to replicate their genomes and assemble new viral particles. Thus, they have evolved intricate mechanisms to exploit host factors. Host cells, in turn, have developed strategies to inhibit viruses, resulting in a nuanced interplay of co-evolution between virus and host. This dynamic often involves competition for resources crucial for both host cell survival and virus replication. Iron and iron-containing cofactors, including iron-sulfur clusters, are known to be a heavily battled resource during bacterial infections where control over iron can tug the war in favor of the pathogen or the host. It is logical to assume that viruses also engage in this competition. Surprisingly, our knowledge about how viruses utilize iron (Fe) and iron-sulfur (FeS) clusters remains limited. The handful of reviews on this topic primarily emphasize the significance of iron in supporting the host immune response against viral infections. The aim of this review, however, is to organize our current understanding of how viral proteins utilize FeS clusters, to give perspectives on what questions to ask next and to propose important avenues for future investigations.

COVID-19 vaccination elicited de novo and recurrence of cluster headache: A case series.

BACKGROUND: Recent pharmacovigilance studies suggested that cluster headache could be a potential adverse effect after coronavirus disease-2019 (COVID-19) vaccination; however, the possibility of coincidence could not be excluded. Detailed case studies might help elucidate their potential link and implicate potential pathogenic mechanisms. METHODS: Patients who developed cluster headache in close temporal relationship to COVID-19 vaccination were identified from two tertiary medical centers in Japan and Taiwan respectively through 2021-2022. Detailed characteristics of the headaches and time between the onset of the index cluster episode and antecedent COVID-19 vaccination were reported. In patients with previous cluster headaches, the duration from previous bout was also recorded. RESULTS: Six patients with new cluster headache bout 3-17 days after COVID-19 vaccination were identified. Two of them were de novo cases. The others either had been attack-free for a long time or developed new cluster bout in seasons atypical to prior bouts. The vaccines included mRNA, viral vector, or protein subunit vaccines. CONCLUSIONS: COVID-19 vaccines, regardless of vaccine types, may elicit de novo or relapse of cluster headache. Future studies are needed to confirm the potential causality and explore the potential pathogenic mechanism.

Wastewater Based Epidemiology, Phylogenetic Analysis and Machine Learning Approach to Describe the Evolution of SARS-CoV-2 in the South-East of Spain (preprint)

The COVID-19 pandemic has posed a significant global threat, leading to several initiatives for its control and management. One such initiative involves wastewater-based epidemiology, which has gained attention for its potential to provide early warning of virus outbreaks and real-time information on its spread. In this study, water samples from two wastewater treatment plants (WWTPs) located at the south east of Spain (Region of Murcia) namely Murcia, and Cartagena, were analyzed by RT-qPCR, Phylogenetic Analysis, and Machine Learning Approach. The aim was to determine whether SARS-CoV-2 detection in the WWTPs of these two cities could serve as a proxy for the virus's spread in the population. The results confirmed that the levels of SARS-CoV-2 in these wastewater samples changed concerning the number of SARS-CoV-2 cases detected in the population and variant occurrences were in line with clinical reported data. Additionally, the phylogenetic analysis showed that samples obtained in close sampling times exhibited a higher similarity than those obtained more distantly in time. A second analysis using a machine learning approach based on the mutations found in the SARS-CoV-2 spike protein was also conducted. Hierarchical Clustering (HC) was used as an efficient unsupervised approach for data analysis. Results indicated that samples obtained in October 2022 in Murcia and Cartagena were significantly different, which corresponded well with the different virus variants circulating in the two locations. The proposed methods in this study are adequate for comparing the Accumulated Natural Vector (ANV) of the SARS-CoV-2 sequences as a preliminary evaluation of potential changes in the variants that are circulating in a given population at a specific time point.

Occipital neuralgia after COVID-19 vaccination: a report of two cases (preprint)

BACKGROUND A wide range of neurological complications has been described following the administration of COVID-19 vaccinations, with headache being the most commonly reported neurological adverse effect, with higher incidence after the second dose. The most common headache is a dull pain or migraine like. Still, two cases of trigeminal neuralgia and a case series of 7 patients with cluster headache who were clinically stable and had a new episode a few days after COVID-19 vaccination have also been reported. Herein, we describe the first two cases of occipital neuralgia developing after COVID-19 vaccination.CASES PRESENTATION Two cases were observed in the neurology outpatient clinic of a tertiary university referral center in Portugal between October 2021 and June 2022. Both patients developed the headache within 1 to 6 days after the second dose of BNT162b2 (Pfizer). One had no previous history of headaches, and the other had a migraine that was clearly different from the present headache. Each case is described, checked for ICHD criteria for occipital neuralgia, and its temporal relation with COVID-19 Vaccination is reported.CONCLUSIONS COVID-19 vaccination can trigger various types of headaches, far beyond the most commonly described feature of dull pain, possibly by activating an immune-inflammatory response.

COVID-19 vaccination-triggered cluster headache episodes with frequent attacks.

BACKGROUND: The pathophysiology of cluster headache and how cluster episodes are triggered, are still poorly understood. Recurrent inflammation of the trigeminovascular system has been hypothesized. It was noted that some long-term attack-free cluster headache patients suddenly developed a new cluster episode shortly after COVID-19 vaccination. METHODS: Cases are described from patients with cluster headache who reported a new cluster episode within days after COVID-19 vaccination. All cases were seen in a tertiary university referral center and a general hospital in the Netherlands between March 2021 and December 2021, when the first COVID-19 vaccinations were carried out in The Netherlands. Clinical characteristics of the previous and new cluster episodes, and time between the onset of a new cluster episode and a previous COVID-19 vaccination were reported. RESULTS: We report seven patients with cluster headache, who had been attack-free for a long time, in whom a new cluster episode occurred within a few days after a COVID-19 vaccination. INTERPRETATION: COVID-19 vaccinations may trigger new cluster episodes in patients with cluster headache, possibly by activating a pro-inflammatory state of the trigeminocervical complex. COVID-19 vaccinations may also exacerbate other neuroinflammatory conditions. .

An Early Return-to-Work Program for COVID-19 Close Contacts in Healthcare During the Omicron Wave in Japan (preprint)

During the coronavirus disease 2019 (COVID-19) pandemic, maintaining adequate staffing in healthcare facilities is important to provide a safe work environment for healthcare workers (HCWs). Japanese early return-to-work (RTW) program may be a rational strategy at a time when there is an increased demand for the services of HCWs. We assessed whether the early RTW program for HCWs who have been in close contact with a COVID-19 case in our hospital was justified. Close contacts were identified according to the guidance of the World Health Organization. Between January and March 2022, 256 HCWs were identified as close contacts (median age, 35 years; 192 female). Thirty-seven (14%) secondary attack cases of COVID-19 were detected. Among 141 HCWs who applied to the early RTW program, nurses and doctors comprised about three-quarters of participants, with a higher participation rate by doctors (78%) than nurses (59%). Eighteen HCWs tested positive for COVID-19 by the sixth day after starting the early RTW program. No COVID-19 infection clusters were reported during the observation period. These findings suggest that the early RTW program for COVID-19 close contacts was a reasonable strategy for HCWs during the Omicron wave.

Optimized infection control practices augment the robust protective effect of vaccination for ESRD patients during a hemodialysis facility SARS-CoV-2 outbreak (preprint)

Background: While dialysis patients are at greater risk of serious SARS-CoV-2 complications, stringent infection prevention measures can help mitigate the risk of infection and transmission within dialysis facilities. We describe an outbreak of 14 cases diagnosed in a 13-day period between May and June of 2021 in a hospital-based ESRD facility, and our coordinated use of epidemiology, viral genome sequencing, and infection control practices to quickly end the cycle of transmission. Methods: Symptomatic patients and staff members were diagnosed via RT-PCR tests. Facility-wide screening was conducted using rapid SARS-CoV-2 antigen tests. SARS-CoV-2 genome sequences were obtained from residual diagnostic PCR specimens. Results: Of the 106 patients who received dialysis in the facility, 10 were diagnosed with SARS-CoV-2 infection, as was one patient support person. Of three positive staff members, two were unvaccinated and had provided care for six and four of the affected patients, respectively. Sequencing demonstrated that all the cases in the cluster shared an identical B.1.1.7./Alpha substrain. Attack rates were greatest among unvaccinated patients and staff. Vaccine effectiveness was 88% among patients. Conclusions: Prompt recognition of an infection cluster and rapid intervention efforts successfully ended the outbreak. Alongside consistent adherence to core infection prevention measures, vaccination was highly effective in reducing disease incidence and morbidity in this vulnerable population.

Validating saliva as a biological sample for cost-effective, rapid and routine screening for SARS-CoV-2 (preprint)

Purpose: Compared to nasopharyngeal/oropharyngeal swabs, non-invasive saliva samples have enormous potential for scalability and routine population screening of SARS-CoV-2. In this study, we are investigating the efficacy of saliva samples relative to nasopharyngeal/oropharyngeal swabs for use as a direct source for the RT-PCR based SARS-CoV-2 detection. Methods: Paired nasopharyngeal/oropharyngeal swabs and saliva samples were collected from suspected positive SARS-CoV-2 patients and tested using RT-PCR. Generalised linear models were used to investigate factors that explain result agreement. Further, we used simulations to evaluate the effectiveness of saliva-based screening in restricting the spread of infection in a large campus such as an educational institution. Results: We observed 75.4% overall result agreement. Prospective positive samples stored for three or more days showed a drastic reduction in the probability of result agreement. We observed 83% result agreement and 74.5% test sensitivity in samples processed and tested within two days of collection. Our simulations suggest that a test with 75% sensitivity, but high daily capacity can be very effective in limiting the size of infection clusters in a workspace. Guided by these results, we successfully implemented a saliva-based screening in the Bangalore Life Sciences Cluster (BLiSC) campus. Conclusion: These results suggest that saliva may be a viable sample source for SARS-CoV-2 surveillance if samples are processed immediately. We strongly recommend the implementation of saliva-based screening strategies for large workplaces and in schools, as well as for population-level screening and routine surveillance as we learn to live with the SARS-CoV-2 virus.

SARS-CoV-2 in schools: genome analysis shows that concurrent cases in the second and third wave were often unconnected (preprint)

Background. The risk of SARS-CoV-2 (SCoV2) infection in schools and student households is typically assessed using classical epidemiology whereby transmission is based on time of symptom onset and contact tracing data. Using such methodologies may be imprecise regarding transmission events of different, simultaneous SCoV2 variants spreading with different rates and directions in a given population. We analysed with high resolution the transmission among different communities, social networks, and educational institutions and the extent of outbreaks using whole genome sequencing (WGS). Methods and Findings. We combined WGS and contact tracing spanning two pandemic waves from October 2020 to May 2021 in the Canton of Basel-City, Switzerland and performed an in-depth analysis of 235 cases relating to 22 educational institutions. We describe the caseload in educational institutions and the public health measures taken and delineate the WGS-supported outbreak surveillance. During the study period, 1,573 of 24,557 (6.4%) children and 410 of 3,726 (11%) staff members from educational institutions were reported SCoV2 positive. Thereof, WGS data from 83 children, 35 adult staff in 22 educational institutions and their 117 contacts (social network, families) was available and analysed. 353 contextual sequences from residents of the Canton of Basel-City sequenced through surveillance were identified to be related to cases in the educational institutions. In total, we identified 55 clusters and found that coinciding SCoV2-cases in individual educational institutions were mostly introduced from different sources such as social networks or the larger community. More transmission chains started in the community and were brought into the educational institutions than vice versa (31 vs. 13). Adolescents (12-19 years old) had the highest case prevalence over both waves compared to younger children or adults, especially for the emerging Alpha variant. Conclusions. Introduction of SCoV2 into schools accounts for most events and reflects transmission closely related to social activity, whereby teenagers and young adults contribute to significant parallel activity. Combining WGS with contact tracing is pivotal to properly inform authorities about SCoV2 infection clusters and transmission directions in educational settings and the effectiveness of enacted public health measures. The gathered data showing more clusters to seed in the community than vice versa as well as few subsequent in-school transmissions indicate that the agilely employed health measures for educational institutions helped to prevent outbreaks among staff and children. The clinical trial accession number is NCT04351503 (clinicaltrials.gov).

Covariant Fitness Clusters Reveal Structural Evolution of SARS-CoV-2 Polymerase Across the Human Population (preprint)

Understanding the fitness landscape of viral mutations is crucial for uncovering the evolutionary mechanisms contributing to pandemic behavior. Here, we apply a Gaussian process regression (GPR) based machine learning approach that generates spatial covariance (SCV) relationships to construct stability fitness landscapes for the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2. GPR generated fitness scores capture on a residue-by-residue basis a covariant fitness cluster centered at the C487-H642-C645-C646 Zn2+ binding motif that iteratively evolves since the early phase pandemic. In the Alpha and Delta variant of concern (VOC), multi-residue SCV interactions in the NiRAN domain form a second fitness cluster contributing to spread. Strikingly, a novel third fitness cluster harboring a Delta VOC basal mutation G671S augments RdRp structural plasticity to potentially promote rapid spread through viral load. GPR principled SCV provides a generalizable tool to mechanistically understand evolution of viral genomes at atomic resolution contributing to fitness at the pathogen-host interface.

A Patient-Focused Questionnaire Designed to Support Headache Diagnosis in General Practice (preprint)

Background: There is an unmet need for the correct diagnosis of primary headache disorders, such as migraine, in primary care. Misdiagnosis is associated with suboptimal management of patients, and it is now widely accepted internationally that better diagnostic support is needed for general practitioners (GPs). In this study, we describe the development of a short, patient-directed questionnaire and supporting documents that aim to help with the diagnosis of headache disorders in primary care. We have also prepared patient feedback material and collected preliminary input from patients, but the main aim of this report is to invite comment and debate on the use of the questionnaire in real-life clinical practice. Methods: : This questionnaire was developed over 18 months using the clinical experience of the authors, current literature review and the International Classification of Headache Disorders (ICHD), 3 rd edition, for migraine, tension-type headache, cluster headache and medication-overuse headache. The questionnaire and two supporting documents will hopefully assist the GP to make a correct diagnosis. A patient survey was used to gather feedback from a small number of patients, and based on these comments, the questionnaire and the supporting documents were modified and updated. Results: : Feedback gathering was attempted in Austria, Germany, Switzerland, Ireland and Spain, but was only possible in Austria due to the COVID-19 pandemic restrictions. From the 18 patients who participated, 17 responded about how easy or difficult the questionnaire was to complete, with 14/17 (82%) being able to complete the questionnaire easily on their own. Overall, the patients found the questionnaire averagely helpful in reminding them of and communicating their headache triggers, symptoms and behaviour changes; on a scale of 1–5, with 1 being very helpful and 5 being not helpful at all, the mean scores were 2.8 and 2.7 (n=18), respectively. Conclusions: : This questionnaire and associated documents were developed with a view to helping GPs to make an accurate headache diagnosis quickly in primary care. Following feedback from patients, updates have been made, including changes to reduce the time it takes to complete the questionnaire. Next steps include wider validation and feedback from primary care physicians.

Epidemic Surveillance Models for Containing the Spread of SARS-CoV-2 Variants: Taiwan Experience (preprint)

Objectives: Two kinds of epidemic surveillance models are presented for containing the spread of SARS-CoV-2 variants so as to avert and stamp out a community-acquired outbreak (CAO) with non-pharmaceutical interventions (NPIs), tests, and vaccination. Design: The surveillance of domestic cluster infections transmitted from imported cases with one-week time lag assessed by the Poisson model and the surveillance of whether, how and when NPIs and test contained the CAO with the SEIR model. Settings: Border and Community of Taiwan. Main Outcome Measurements: The expected number and the upper bound of the 95% credible interval (CrI) of weekly covid-19 cases compared with the observed number for assessing the threshold of a CAO; effective reproductive number (Rt) and the effectiveness of NPIs for containing a CAO. Results: For the period of January-September 2020 when the wild type and the D614G period were prevailing, an increase in one imported case prior to one week would lead to 9.54% (95% CrI 6.44% to 12.59%) higher risk of domestic cluster infection that provides a one-week prior alert signal for more stringent NPIs and active testing locally. Accordingly, there was an absence of CAO until the Alpha VOC period of February 2021. However, given level one of NPI alert the risk of domestic cluster infections was gradually elevated to 14.14% (95% CrI 5.41% to 25.10%), leading to the Alpha VOC CAOs of six hotspots around mid-May 2021. It took two-and-half months for containing this CAO mainly with level three of NPI alert and rapid test and partially by the rolling out of vaccination. By applying the SEIR model, the Rt decreased from 4.0 at beginning to 0.7 on 31 July 2021 in parallel with the escalating NPIs from 30% to 90%. Containing a small outbreak of Delta VOC during this CAO period was also evaluated and demonstrated. After controlling the CAO, it again returned to imported-domestic transmission for Delta VOC from July until September 2021, giving an estimate of 10.16% (95% CrI: 7.01% to 13.59%) for the risk of several small cluster infections. However, there was an absence of CAO that resulted from the effectiveness of NPIs and tests, and the rapid expansion of vaccination. Conclusions: Averting and containing CAOs of SARS-CoV-2 variants are demonstrated by two kinds of epidemic surveillance models that have been applied to Taiwan scenario. These two models can be accommodated to monitor the epidemic of forthcoming emerging SARS-CoV-2 VOCs with various circumstances of vaccine coverage, NPIs, and tests in countries worldwide.

Characterizing the effective reproduction number during the COVID-19 epidemic: Insights from Qatar experience (preprint)

Background: The effective reproduction number, Rt, is a tool to track and understand epidemic dynamics. This investigation of Rt estimations was conducted to guide the national COVID-19 response in Qatar, from the onset of the epidemic until August 18, 2021. Methods: Real-time empirical RtEmpirical was estimated using five methods, including the Robert Koch Institute, Cislaghi, Systrom-Bettencourt and Ribeiro, Wallinga and Teunis, and Cori et al. methods. Rt was also estimated using a transmission dynamics model (RtModel-based). Uncertainty and sensitivity analyses were conducted. Agreements between different Rt estimates were assessed by calculating correlation coefficients. Results: RtEmpirical captured the evolution of the epidemic through three waves, public health response landmarks, effects of major social events, transient fluctuations coinciding with significant clusters of infection, and introduction and expansion of the B.1.1.7 variant. The various estimation methods produced consistent and overall comparable RtEmpirical estimates with generally large correlation coefficients. The Wallinga and Teunis method was the fastest at detecting changes in epidemic dynamics. RtEmpirical estimates were consistent whether using time series of symptomatic PCR-confirmed cases, all PCR-confirmed cases, acute-care hospital admissions, or ICU-care hospital admissions, to proxy trends in true infection incidence. RtModel-based correlated strongly with RtEmpirical and provided an average RtEmpirical. Conclusions: Rt estimations were robust and generated consistent results regardless of the data source or the method of estimation. Findings affirmed an influential role for Rt estimations in guiding national responses to the COVID-19 pandemic, even in resource-limited settings.

Characteristics of Long Covid: findings from a social media surve (preprint)

Many people are not recovering for months after being infected with SARS-CoV-2. Long Covid has emerged as a major public health concern that needs defining, quantifying, and describing. We aimed to explore the initial and ongoing symptoms of Long Covid following SARS-CoV-2 infection and describe its impact on daily life in people who were not admitted to hospital during the first two weeks of the illness. We co-produced a survey with people living with Long Covid. We collected the data through an online survey using convenience non-probability sampling, with the survey posted both specifically on Long Covid support groups and generally on social media. The criteria for inclusion were adults with lab-confirmed (PCR or antibody) or suspected COVID-19 managed in the community (non-hospitalised) in the first two weeks of illness. We used agglomerative hierarchical clustering to identify specific symptom clusters, and their demographic and functional correlates. We analysed data from 2550 participants with a median duration of illness of 7.7 months (interquartile range (IQR) 7.4-8.0). The mean age was 46.5 years (standard deviation 11 years) with 82.8% females and 79.9% of participants based in the UK. 89.5% described their health as good, very good or excellent before COVID-19. The most common initial symptoms that persisted were exhaustion, chest pressure/tightness, shortness of breath and headache. Cough, fever, and chills were common initial symptoms that became less prevalent later in the illness, whereas cognitive dysfunction and palpitations became more prevalent later in the illness. 26.5% reported lab-confirmation of infection. The biggest difference in ongoing symptoms between those who reported testing positive and those who did not was loss of smell/taste. Ongoing symptoms affected at least 3 organ systems in 83.5% of participants. Most participants described fluctuating (57.7%) or relapsing symptoms (17.6%). Physical activity, stress and sleep disturbance commonly triggered symptoms. A third (32%) reported they were unable to live alone without any assistance at six weeks from start of illness. 16.9% reported being unable to work solely due to COVID-19 illness. 66.4% reported taking time off sick (median of 60 days, IQR 20, 129). 37.0% reported loss of income due to illness, and 64.4% said they were unable to perform usual activities/duties. Acute systems clustered broadly into two groups: a majority cluster (n=2235, 88%) with cardiopulmonary predominant symptoms, and a minority cluster (n=305, 12%) with multisystem symptoms. Similarly, ongoing symptoms broadly clustered in two groups; a majority cluster (n=2243, 88.8%) exhibiting mainly cardiopulmonary, cognitive symptoms and exhaustion, and a minority cluster (n=283, 11.2%) exhibited more multisystem symptoms. Belonging to the more severe multisystem cluster was associated with more severe functional impact, lower income, younger age, being female, worse baseline health, and inadequate rest in the first two weeks of the illness, with no major differences in the cluster patterns when restricting analysis to the lab-confirmed subgroup. This is an exploratory survey of Long Covid characteristics. Whilst it is important to acknowledge that it is a non-representative population sample, it highlights the heterogeneity of persistent symptoms, and the significant functional impact of prolonged illness following confirmed or suspected SARS-CoV-2 infection. To study prevalence, predictors and prognosis, research is needed in a representative population sample using standardised case definitions (to include those not lab-confirmed in the first pandemic wave).

Characterization of SARS-CoV-2 genetic structure and infection clusters in a large German city based on integrated genomic surveillance, outbreak analysis, and contact tracing (preprint)

Viral genome sequencing can address key questions about SARS-CoV-2 evolution and viral transmission. Here, we present an integrated system of genomic surveillance in the German city of Dusseldorf, combining a) viral surveillance sequencing, b) genetically based identification of infection clusters in the population, c) analysis of hospital outbreaks, d) integration of public health authority contact tracing data, and e) a user-friendly dashboard application as a central data analysis platform. The generated surveillance sequencing data (n = 320 SARS-CoV-2 genomes) showed that the development of the local viral population structure from August to December 2020 was consistent with European trends, with the notable absence of SARS-CoV-2 variants 20I/501Y.V1/B.1.1.7 and B.1.351 until the end of the local sampling period. Against a background of local surveillance and other publicly available SARS-CoV-2 data, four putative SARS-CoV-2 outbreaks at Dusseldorf University Hospital between October and December 2020 (n = 44 viral genomes) were investigated and confirmed as clonal, contributing to the development of improved infection control and prevention measures. An analysis of the generated surveillance sequencing data with respect to infection clusters in the population based on a greedy clustering algorithm identified five candidate clusters, all of which were subsequently confirmed by the integration of public health authority contact tracing data and shown to be represent transmission settings of particular relevance (schools, care homes). A joint analysis of outbreak and surveillance data identified a potential transmission of an outbreak strain from the local population into the hospital and back; and an in-depth analysis of one population infection cluster combining genetic with contact tracing data enabled the identification of a previously unrecognized population transmission chain involving a martial arts gym. Based on these results and a real-time sequencing experiment in which we demonstrated the feasibility of achieving sample-to-turnaround times of <30 hours with the Oxford Nanopore technology, we discuss the potential benefits of routine ultra-fast sequencing of all detected infections for contact tracing, infection cluster detection, and, ultimately, improved management of the SARS-CoV-2 pandemic.

Contrastive analysis for scatterplot-based representations of dimensionality reduction (preprint)

Cluster interpretation after dimensionality reduction (DR) is a ubiquitous part of exploring multidimensional datasets. DR results are frequently represented by scatterplots, where spatial proximity encodes similarity among data samples. In the literature, techniques support the understanding of scatterplots' organization by visualizing the importance of the features for cluster definition with layout enrichment strategies. However, current approaches usually focus on global information, hampering the analysis whenever the focus is to understand the differences among clusters. Thus, this paper introduces a methodology to visually explore DR results and interpret clusters' formation based on contrastive analysis. We also introduce a bipartite graph to visually interpret and explore the relationship between the statistical variables employed to understand how the data features influence cluster formation. Our approach is demonstrated through case studies, in which we explore two document collections related to news articles and tweets about COVID-19 symptoms. Finally, we evaluate our approach through quantitative results to demonstrate its robustness to support multidimensional analysis.

Hospital-based headache care during the Covid-19 pandemic in Denmark and Norway.

BACKGROUND: The Covid-19 pandemic is causing changes in delivery of medical care worldwide. It is not known how the management of headache patients was affected by the lockdown during the pandemic. The aim of the present study was to investigate how the initial phase of the Covid-19 pandemic affected the hospital management of headache in Denmark and Norway. METHODS: All neurological departments in Denmark (n = 14) and Norway (n = 18) were invited to a questionnaire survey. The study focused on the lockdown and all questions were answered in regard to the period between March 12th and April 15th, 2020. RESULTS: The responder rate was 91% (29/32). Of the neurological departments 86% changed their headache practice during the lockdown. The most common change was a shift to more telephone consultations (86%). Video consultations were offered by 45%. The number of new headache referrals decreased. Only 36% administered botulinum toxin A treatment according to usual schemes. Sixty% reported that fewer patients were admitted for in-hospital emergency diagnostics and treatment. Among departments conducting headache research 57% had to halt ongoing projects. Overall, 54% reported that the standard of care was worse for headache patients during the pandemic. CONCLUSION: Hospital-based headache care and research was impacted in Denmark and Norway during the initial phase of the Covid-19-pandemic.

Social network-based strategies for classroom size reduction can help limit outbreaks of SARS-CoV-2 in high schools. A simulation study in classrooms of four European countries. (preprint)

Background Until pharmaceutical measures are widely available to slow the spread of SARS-CoV-2, social distancing strategies are key to avert overwhelmed health systems. Since schools host large numbers of students in enclosed spaces, they are feared to produce infection clusters. With school closures coming at high social and economic costs, social distancing measures within schools are needed to make them as safe as possible. One widely discussed distancing measure in the school context is to use cohorting strategies, i.e., to split larger clusters such as classrooms into smaller groups that are instructed separately. In addition to facilitating social distancing within these cohorts, cohorting strategies also aim to prevent transmission across cohorts. However, little is known about which cohorting strategies are particularly effective to prevent disease transmission between cohorts in schools. Methods Using nationally representative data on adolescents in classrooms in four European countries, we simulate how four different cohorting strategies can mitigate the spread of SARS-CoV-2 in high schools. We model the effect of forming two cohorts randomly, splitting cohorts by gender, optimizing cohorts by minimizing students' out-of-school cross-cohort contacts, and approximating this optimization strategy by network chains. The rationale of all non-random cohorting strategies is to prevent the spread of SARS-CoV-2 from one cohort to the other by reducing cross-cohort out-of-school contact. We also compare the overall effect of cohorting to no cohorting and differentiate between a rota-system in which cohorts receive in-person instruction in alternating weeks and a system with separate but same-day in-person instruction for both cohorts. Data were collected between 2010 and 2011 as part of the CILS4EU project, a network panel study of 14-15-year-olds in England, Germany, the Netherlands, and Sweden. Across all four countries, we model the transmission of SARS-CoV-2 in 507 classrooms, capturing a total of 12,291 students. Findings Our simulations suggest that all four cohorting strategies reduce the spread of SARS-CoV-2 in classrooms, but vary in their effectiveness. Relative to random cohorting, all strategies that factor in out-of-school cross-cohort ties have particularly strong effects on the frequency of cross-cohort transmission but also substantively reduce the total number of infections and the share of students in quarantine when transmission dynamics are strong. Cohorting that explicitly minimizes out-of-school contact between students in different cohorts is most effective, but network-based approximation also breaks many cross-cohort ties and thus performs well. Because adolescents' out-of-school contacts tend to be strongly segregated by gender, dividing classrooms by gender also outperforms random cohorting but is less effective than directly using network information. For all cohorting strategies, rota-systems with instruction in alternating weeks contain outbreaks more effectively than same-day in-person instruction. Interpretation Cohorting of school classes as a social distancing measure can help to effectively curb SARS-CoV-2 outbreaks in the school context. If schools consider splitting up classes into two smaller cohorts, factoring in out-of-school contacts can help achieve a more effective separation of cohorts. The paper proposes effective cohorting strategies that outperform naive random cohorting in preventing the spread of SARS-CoV-2. These strategies may limit outbreaks to one cohort, keep the size of infection clusters low, and reduce the number of students in quarantine if an index case occurs in the student body. Our findings thus suggest that if schools consider cohorting, they should assign students who meet after school to the same cohort. In particular, cohorting on the basis of gender or network chains is effective and may be successfully implemented within the constraints posed by the classroom context.

A Major Outbreak of COVID-19 in the Diamond Princess Cruise Ship (preprint)

The COVID-19 pandemic broke out in Wuhan, China, and declared an international public health emergency by the World Health Organization in 2019. It mainly manifests as symptoms of respiratory infections, and severe cases can cause pneumonia and death. The Diamond Princess cruise ship outbroke cluster infection outside China during the early pandemic. The incident occurred on February 1, 2020, and an 80-year-old Hong Kong man was diagnosed with COVID-19. The cruise docked in Yokohama, Japan, for 14 days on-board quarantine; however, cluster infection outbroke rapidly. The results show that after 14 days of quarantine, 634 (17.1%) cases were diagnosed with a total of 3,711 population, and 328 (51.7%) cases were asymptomatic. As of April 24, 2020, 712 cases have been diagnosed and 14 deaths have occurred. A cumulative mortality rate reaches 1.96%. Using a nonlinear least-squares curve fitting with Microsoft Excel Solver, we obtain the parameters of the SIR mathematical model of infectious disease and the reproduction number (R0) of the COVID-19 outbreak is 2.37±0.26. Without an emergency evacuation plan, the total infection rate will reach 88.47%. These data show “only one” COVID-19 case could still outbreak cluster infection on large cruise ships. The possible causes and countermeasures are discussed.