Determinants of SARS-CoV-2 transmission to guide vaccination strategy in an urban area.

Transmission chains within small urban areas (accommodating ∼30 per cent of the European population) greatly contribute to case burden and economic impact during the ongoing coronavirus pandemic and should be a focus for preventive measures to achieve containment. Here, at very high spatio-temporal resolution, we analysed determinants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in a European urban area, Basel-City (Switzerland). We combined detailed epidemiological, intra-city mobility and socio-economic data sets with whole-genome sequencing during the first SARS-CoV-2 wave. For this, we succeeded in sequencing 44 per cent of all reported cases from Basel-City and performed phylogenetic clustering and compartmental modelling based on the dominating viral variant (B.1-C15324T; 60 per cent of cases) to identify drivers and patterns of transmission. Based on these results we simulated vaccination scenarios and corresponding healthcare system burden (intensive care unit (ICU) occupancy). Transmissions were driven by socio-economically weaker and highly mobile population groups with mostly cryptic transmissions which lacked genetic and identifiable epidemiological links. Amongst more senior population transmission was clustered. Simulated vaccination scenarios assuming 60-90 per cent transmission reduction and 70-90 per cent reduction of severe cases showed that prioritising mobile, socio-economically weaker populations for vaccination would effectively reduce case numbers. However, long-term ICU occupation would also be effectively reduced if senior population groups were prioritised, provided there were no changes in testing and prevention strategies. Reducing SARS-CoV-2 transmission through vaccination strongly depends on the efficacy of the deployed vaccine. A combined strategy of protecting risk groups by extensive testing coupled with vaccination of the drivers of transmission (i.e. highly mobile groups) would be most effective at reducing the spread of SARS-CoV-2 within an urban area.

Mimics and chameleons of COVID-19: patient presentation and accuracy of triage during the first wave.

STUDY AIMS: To quantify mimics and chameleons of coronavirus disease 2019 (COVID-19), to analyse the diagnostic accuracy of the triage protocol, and to describe the resulting groups of mimics and chameleons - including their presenting symptoms and final diagnoses. METHODS: Diagnostic accuracy study including all adult patients tested for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) at the emergency department of the University Hospital Basel, Switzerland during the first wave of pandemic in spring 2020. Diagnostic accuracy of triage was determined by calculating sensitivity, specificity, positive and negative predictive value, and positive and negative likelihood ratio. Triage to the group of suspected (+) and not suspected (-) COVID-19 was considered the index test, whereas a SARS-CoV-2 polymerase chain reaction test result was used as reference standard. Mimics were defined as false positives and chameleons as false negatives. RESULTS: Of 2898 patients included in the analysis, 191 were true positives, 895 were false positives (mimics), 9 were false negatives (chameleons) and 1803 were true negatives. This resulted in a sensitivity of 0.95 (95% confidence interval [CI] 0.92-0.98) and a specificity of 0.67 (95% CI 0.65-0.69) for standardised triage. Among mimics, the main categories of final diagnoses were other infections (n = 513, 57.3%), cardiovascular diseases (excluding cerebrovascular) (n = 125, 14%), and non-infectious diseases of the respiratory system (n = 84, 9.4%). Fever (n = 357, 39.9% vs n = 104, 54.5%), cough (n = 466, 52.1% vs n = 126 66%), and smell or taste dysfunction (n = 60, 6.7% vs n = 24, 12.6%) were less frequently observed in mimics than in COVID-19 patients. Eight of nine COVID-19 chameleons presented with either nonspecific complaints (weakness and/or fatigue) or gastrointestinal symptoms. CONCLUSION: The quantitative assessment of COVID-19 mimics and chameleons showed a high prevalence of mimics. Clinical differentiation between true positives and false positives is not feasible due to largely overlapping symptoms. Prevalence of chameleons was very low.

Comparing Immunoassays for SARS-CoV-2 Antibody Detection in Patients with and without Laboratory-Confirmed SARS-CoV-2 Infection.

Commercially available SARS-CoV-2-directed antibody assays may assist in diagnosing past exposure to SARS-CoV-2 antigens. We cross-compared the following eight immunoassays detecting antibodies against SARS-CoV-2 nucleocapsid (N) or spike (S) antigens in three cohorts consisting of 859 samples from 622 patients: (#1) EDI novel coronavirus COVID-19 (Epitope), (#2) RecomWell SARS-CoV-2 (Mikrogen), (#3) COVID-19 ELISA (VirCell), (#4) Elecsys anti-SARS-CoV-2 N (Roche), (#5) Liaison SARS-CoV-2 S1/S2 (DiaSorin), (#6) anti-SARS-CoV-2 ELISA (EuroImmun), (#7) Elecsys anti-SARS-CoV-2 S (Roche), and (#8) Liaison SARS-CoV-2 TrimericS (DiaSorin). In cross-sectional cohort 1 (68 sera from 38 patients with documented SARS-CoV-2 infection), agreement between assays #1 to #6 ranged from 75% to 93%, whereby discordance mostly resulted from N-based assays #1 to #4. In cross-sectional cohort 2 (510 sera from 510 patients; 56 documented, 454 unknown SARS-CoV-2 infection), assays #4 to #6 were analyzed further together with assays #7 and #8, revealing 94% concordance (44 [9%] positives and 485 [85%] negatives). Discordance was highest within 2 weeks after SARS-CoV-2/COVID-19 diagnosis and confirmed in the longitudinal cohort 3 (281 sera from 74 COVID-19 patients), using assays #4, #6, #7, and #8. Subanalysis of 20 (27%) initially seronegative cohort 3 patients revealed assay-dependent 50% and 90% seroconversion rates after 8 to 11 days and 14 to 18 days, respectively. Increasing SARS-CoV-2 antibodies were significantly associated with declining levels of viral loads, lactate dehydrogenase, interleukin-6, and C-reactive protein and preceded clearance of SARS-CoV-2 detection in the upper respiratory tract by approximately 1 week. SARS-CoV-2-specific antibody assays show substantial agreement, but interpretation of qualitative and semiquantitative results depends on the time elapsed postdiagnosis and the choice of viral antigen. Mounting of systemic SARS-CoV-2-specific antibodies may predict recovery from viral injury and clearance of mucosal replication.

Direct Comparison of Clinical Characteristics, Outcomes, and Risk Prediction in Patients with COVID-19 and Controls-A Prospective Cohort Study.

Most studies investigating early risk predictors in coronavirus disease 19 (COVID-19) lacked comparison with controls. We aimed to assess and directly compare outcomes and risk predictors at time of emergency department (ED) presentation in COVID-19 and controls. Consecutive patients presenting to the ED with suspected COVID-19 were prospectively enrolled. COVID-19-patients were compared with (i) patients tested negative (overall controls) and (ii) patients tested negative, who had a respiratory infection (respiratory controls). Primary outcome was the composite of intensive care unit (ICU) admission and death at 30 days. Among 1081 consecutive cases, 191 (18%) were tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and 890 (82%) were tested negative (overall controls), of which 323 (30%) had a respiratory infection (respiratory controls). Incidence of the composite outcome was significantly higher in COVID-19 (23%) as compared with the overall control group (10%, adjusted-HR 2.45 (95%CI, 1.61-3.74), p < 0.001) or the respiratory control group (10%, adjusted-HR 2.93 (95%CI, 1.66-5.17), p < 0.001). Blood oxygen saturation, age, high-sensitivity troponin, c-reactive protein, and lactate dehydrogenase were identified as the strongest predictors of poor outcome available at time of ED presentation in COVID-19 with highly comparable prognostic utility in overall and respiratory controls. In conclusion, patients presenting to the ED with COVID-19 have a worse outcome than controls, even after adjustment for differences in baseline characteristics. Most predictors of poor outcome in COVID-19 were not restricted to COVID-19, but of comparable prognostic utility in controls and therefore generalizable to unselected patients with suspected COVID-19.

Association of Frailty with Adverse Outcomes in Patients with Suspected COVID-19 Infection.

Older age and frailty are predictors of adverse outcomes in patients with COVID-19. In emergency medicine, patients do not present with the diagnosis, but with suspicion of COVID-19. The aim of this study was to assess the association of frailty and age with death or admission to intensive care in patients with suspected COVID-19. This single-centre prospective cohort study was performed in the Emergency Department of a tertiary care hospital. Patients, 65 years and older, with suspected COVID-19 presenting to the Emergency Department during the first wave of the pandemic were consecutively enrolled. All patients underwent nasopharyngeal SARS-CoV-2 PCR swab tests. Patients with a Clinical Frailty Scale (CFS) > 4, were considered to be frail. Associations between age, gender, frailty, and COVID-19 status with the composite adverse outcome of 30-day-intensive-care-admission and/or 30-day-mortality were tested. In the 372 patients analysed, the median age was 77 years, 154 (41.4%) were women, 44 (11.8%) were COVID-19-positive, and 125 (33.6%) were frail. The worst outcome was seen in frail COVID-19-patients with six (66.7%) adverse outcomes. Frailty (CFS > 4) and COVID-19-positivity were associated with an adverse outcome after adjustment for age and gender (frailty: OR 5.01, CI 2.56-10.17, p < 0.001; COVID-19: OR 3.47, CI 1.48-7.89, p = 0.003). Frailty was strongly associated with adverse outcomes and outperformed age as a predictor in emergency patients with suspected COVID-19.

Global Genomic Analysis of SARS-CoV-2 RNA Dependent RNA Polymerase Evolution and Antiviral Drug Resistance.

A variety of antiviral treatments for COVID-19 have been investigated, involving many repurposed drugs. Currently, the SARS-CoV-2 RNA-dependent RNA polymerase (RdRp, encoded by nsp12-nsp7-nsp8) has been targeted by numerous inhibitors, e.g., remdesivir, the only provisionally approved treatment to-date, although the clinical impact of these interventions remains inconclusive. However, the potential emergence of antiviral resistance poses a threat to the efficacy of any successful therapies on a wide scale. Here, we propose a framework to monitor the emergence of antiviral resistance, and as a proof of concept, we address the interaction between RdRp and remdesivir. We show that SARS-CoV-2 RdRp is under purifying selection, that potential escape mutations are rare in circulating lineages, and that those mutations, where present, do not destabilise RdRp. In more than 56,000 viral genomes from 105 countries from the first pandemic wave, we found negative selective pressure affecting nsp12 (Tajima's D = -2.62), with potential antiviral escape mutations in only 0.3% of sequenced genomes. Potential escape mutations included known key residues, such as Nsp12:Val473 and Nsp12:Arg555. Of the potential escape mutations involved globally, in silico structural models found that they were unlikely to be associated with loss of stability in RdRp. No potential escape mutation was found in a local cohort of remdesivir treated patients. Collectively, these findings indicate that RdRp is a suitable drug target, and that remdesivir does not seem to exert high selective pressure. We anticipate our framework to be the starting point of a larger effort for a global monitoring of drug resistance throughout the COVID-19 pandemic.

Epidemiology and precision of SARS-CoV-2 detection following lockdown and relaxation measures.

OBJECTIVES: Detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is key to the clinical and epidemiological assessment of CoVID-19. We cross-validated manual and automated high-throughput testing for SARS-CoV-2-RNA, evaluated SARS-CoV-2 loads in nasopharyngeal-oropharyngeal swabs (NOPS), lower respiratory fluids, and plasma, and analyzed detection rates after lockdown and relaxation measures. METHODS: Basel-S-gene, Roche-E-gene, and Roche-cobas®6800-Target1 and Target2 were prospectively validated in 1344 NOPS submitted during the first pandemic peak (Week 13). Follow-up cohort (FUP) 1, 2, and 3 comprised 10,999, 10,147, and 19,389 NOPS submitted during a 10-week period until Weeks 23, 33, and 43, respectively. RESULTS: Concordant results were obtained in 1308 cases (97%), including 97 (9%) SARS-CoV-2-positives showing high quantitative correlations (Spearman's r > .95; p < .001) for all assays and high precision by Bland-Altman analysis. Discordant samples (N = 36, 3%) had significantly lower SARS-CoV-2 loads (p < .001). Following lockdown, detection rates declined to <1% in FUP-1, reducing single-test positive predictive values from 99.3% to 85.1%. Following relaxation, rates flared up to 4% and 12% in FUP-2 and -3, but infected patients were younger than during lockdown (34 vs. 52 years, p < .001). In 261 patients providing 936 NOPS, SARS-CoV-2 loads declined by three orders of magnitude within 10 days postdiagnosis (p < .001). SARS-CoV-2 loads in NOPS correlated with those in time-matched lower respiratory fluids or in plasma but remained detectable in some cases with negative follow-up NOPS, respectively. CONCLUSION: Manual and automated assays significantly correlated qualitatively and quantitatively. Following a successful lockdown, declining positive predictive values require independent dual-target confirmation for reliable assessment. Confirmatory and quantitative follow-up testing should be obtained within <5 days and consider lower respiratory fluids in symptomatic patients with SARS-CoV-2-negative NOPS.

SARS-CoV-2 outbreak in a tri-national urban area is dominated by a B.1 lineage variant linked to a mass gathering event.

The first case of SARS-CoV-2 in Basel, Switzerland was detected on February 26th 2020. We present a phylogenetic study to explore viral introduction and evolution during the exponential early phase of the local COVID-19 outbreak from February 26th until March 23rd. We sequenced SARS-CoV-2 naso-oropharyngeal swabs from 746 positive tests that were performed at the University Hospital Basel during the study period. We successfully generated 468 high quality genomes from unique patients and called variants with our COVID-19 Pipeline (COVGAP), and analysed viral genetic diversity using PANGOLIN taxonomic lineages. To identify introduction and dissemination events we incorporated global SARS-CoV-2 genomes and inferred a time-calibrated phylogeny. Epidemiological data from patient questionnaires was used to facilitate the interpretation of phylogenetic observations. The early outbreak in Basel was dominated by lineage B.1 (83·6%), detected first on March 2nd, although the first sample identified belonged to B.1.1. Within B.1, 68·2% of our samples fall within a clade defined by the SNP C15324T ('Basel cluster'), including 157 identical sequences at the root of the 'Basel cluster', some of which we can specifically trace to regional spreading events. We infer the origin of B.1-C15324T to mid-February in our tri-national region. The other genomes map broadly over the global phylogenetic tree, showing several introduction events from and/or dissemination to other regions of the world via travellers. Family transmissions can also be traced in our data. A single lineage variant dominated the outbreak in the Basel area while other lineages, such as the first (B.1.1), did not propagate. A mass gathering event was the predominant initial source of cases, with travel returners and family transmissions to a lesser extent. We highlight the importance of adding specific questions to epidemiological questionnaires, to obtain data on attendance of large gatherings and their locations, as well as travel history, to effectively identify routes of transmissions in up-coming outbreaks. This phylogenetic analysis in concert with epidemiological and contact tracing data, allows connection and interpretation of events, and can inform public health interventions. Trial Registration: ClinicalTrials.gov NCT04351503.

Community-acquired and hospital-acquired respiratory tract infection and bloodstream infection in patients hospitalized with COVID-19 pneumonia.

OBJECTIVES: SARS-CoV-2 may cause acute lung injury, and secondary infections are thus relevant complications in patients with COVID-19 pneumonia. However, detailed information on community- and hospital-acquired infections among patients with COVID-19 pneumonia is scarce. METHODS: We identified 220 SARS-CoV-2-positive patients hospitalized at the University Hospital Basel, Switzerland (between 25 February and 31 May 2020). We excluded patients who declined the general consent (n = 12), patients without clinical evidence of pneumonia (n = 29), and patients hospitalized for < 24 h (n = 17). We evaluated the frequency of community- and hospital-acquired infections using respiratory and blood culture materials with antigen, culture-based, and molecular diagnostics. For ICU patients, all clinical and microbial findings were re-evaluated interdisciplinary (intensive care, infectious disease, and clinical microbiology), and agreement reached to classify patients with infections. RESULTS: In the final cohort of 162 hospitalized patients (median age 64.4 years (IQR, 50.4-74.2); 61.1% male), 41 (25.3%) patients were admitted to the intensive care unit, 34/41 (82.9%) required mechanical ventilation, and 17 (10.5%) of all hospitalized patients died. In total, 31 infections were diagnosed including five viral co-infections, 24 bacterial infections, and three fungal infections (ventilator-associated pneumonia, n = 5; tracheobronchitis, n = 13; pneumonia, n = 1; and bloodstream infection, n = 6). Median time to respiratory tract infection was 12.5 days (IQR, 8-18) and time to bloodstream infection 14 days (IQR, 6-30). Hospital-acquired bacterial and fungal infections were more frequent among ICU patients than other patients (36.6% vs. 1.7%). Antibiotic or antifungal treatment was administered in 71 (43.8%) patients. CONCLUSIONS: Community-acquired viral and bacterial infections were rare among COVID-19 pneumonia patients. By contrast, hospital-acquired bacterial or fungal infections were frequently complicating the course among ICU patients.

COVID-19 Triage and Test Center: Safety, Feasibility, and Outcomes of Low-Threshold Testing.

This prospective observational study evaluated the safety and feasibility of a low threshold testing process in a Triage and Test Center (TTC) during the early course of the coronavirus disease 19 (COVID-19) pandemic. In addition, we aimed to identify clinical predictors for a positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) swab result. Patients underwent informal triage, standardized history taking, and physician evaluation, only where indicated. Patients were observed for 30 days. Safety was the primary outcome and was defined as a COVID-19-related 30 day re-presentation rate <5% and mortality rate <1% in patients presenting to the TTC. Feasibility was defined as an overruling of informal triage <5%. Among 4815 presentations, 572 (11.9%) were tested positive for SARS-CoV-2, and 4774 were discharged. Mortality at 30-days was 0.04% (2 patients, one of which related to COVID-19). Fever (OR 2.03 [95% CI 1.70;2.42]), myalgia (OR 1.94 [1.63;2.31]), chills (OR 1.77 [1.44;2.16]), headache (OR 1.61 [1.34;1.94]), cough (OR 1.50 [1.24;1.83]), weakness (OR 1.46 [1.21;1.76]), and confusion (OR 1.39 [1.06;1.80]) were associated with test positivity. Re-presentation rate was 8% overall and 1.4% in COVID-19 related re-presentation (69 of 4774). The overruling rate of informal triage was 1.5%. According to our study, a low-threshold testing process in a TTC appeared to be safe (low re-presentation and low mortality) and is feasible (low overruling of informal triage). A COVID-19 diagnosis based on clinical parameters only does not appear possible.

Epidemiology of Severe Acute Respiratory Syndrome Coronavirus 2 Emergence Amidst Community-Acquired Respiratory Viruses.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China as the cause of coronavirus disease 2019 in December 2019 and reached Europe by late January 2020, when community-acquired respiratory viruses (CARVs) are at their annual peak. We validated the World Health Organization (WHO)-recommended SARS-CoV-2 assay and analyzed the epidemiology of SARS-CoV-2 and CARVs. METHODS: Nasopharyngeal/oropharyngeal swabs (NOPS) from 7663 patients were prospectively tested by the Basel S-gene and WHO-based E-gene (Roche) assays in parallel using the Basel N-gene assay for confirmation. CARVs were prospectively tested in 2394 NOPS by multiplex nucleic acid testing, including 1816 (75%) simultaneously for SARS-CoV-2. RESULTS: The Basel S-gene and Roche E-gene assays were concordant in 7475 cases (97.5%) including 825 (11%) SARS-CoV-2 positives. In 188 (2.5%) discordant cases, SARS-CoV-2 loads were significantly lower than in concordant positive ones and confirmed in 105 (1.4%). Adults were more frequently SARS-CoV-2 positive, whereas children tested more frequently CARV positive. CARV coinfections with SARS-CoV-2 occurred in 1.8%. SARS-CoV-2 replaced CARVs within 3 weeks, reaching 48% of all detected respiratory viruses followed by rhinovirus/enterovirus (13%), influenza virus (12%), coronavirus (9%), respiratory syncytial virus (6%), and metapneumovirus (6%). CONCLUSIONS: Winter CARVs were dominant during the early SARS-CoV-2 pandemic, impacting infection control and treatment decisions, but were rapidly replaced, suggesting competitive infection. We hypothesize that preexisting immune memory and innate immune interference contribute to the different SARS-CoV-2 epidemiology among adults and children.

Reproductive number of the COVID-19 epidemic in Switzerland with a focus on the Cantons of Basel-Stadt and Basel-Landschaft.

The reproductive number in Switzerland was between 1.5 and 2 during the first third of March, and has consistently decreased to around 1. After the announcement of the latest strict measure on 20 March 2020, namely that gatherings of more than five people in public spaces are prohibited, the reproductive number dropped significantly below 1; the authors of this study estimate the reproductive number to be between 0.6 and 0.8 in the first third of April.