Bat coronaviruses related to SARS–CoV–2 and infectious for human cells
The animal reservoir of SARS-CoV-2 is unknown despite reports of various SARS-CoV-2-related viruses in Asian Rhinolophus bats1-4, including the closest virus from R. affinis, RaTG135,6 and in pangolins7-9. SARS-CoV-2 presents a mosaic genome, to which different progenitors contribute. The spike sequence determines the binding affinity and accessibility of its receptor-binding domain (RBD) to the cellular angiotensin-converting enzyme 2 (ACE2) receptor and is responsible for host range10-12. SARS-CoV-2 progenitor bat viruses genetically close to SARS-CoV-2 and able to enter human cells through a human ACE2 pathway have not yet been identified, though they would be key in understanding the origin of the epidemics.
Here we show that such viruses indeed circulate in cave bats living in the limestone karstic terrain in North Laos, within the Indochinese peninsula. We found that the RBDs of these viruses differ from that of SARS-CoV-2 by only one or two residues at the interface with ACE2, bind more efficiently to the hACE2 protein than the SARS-CoV-2 Wuhan strain isolated in early human cases, and mediate hACE2-dependent entry and replication in human cells, which is inhibited by antibodies neutralizing SARS-CoV-2. None of these bat viruses harbors a furin cleavage site in the spike. Our findings therefore indicate that bat-borne SARS-CoV-2-like viruses potentially infectious for humans circulate in Rhinolophus spp. in the Indochinese peninsula.
<em>SARS</em>-<em>CoV</em>-<em>2</em>-<em>related</em> mortality and treatment delays for cancer patients in Austria : Findings of a multicentric nationwide study
Background: Cancer patients infected with severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) have an increased risk of mortality. Here, we investigated predictive factors for coronavirus disease 2019 (COVID-19) associated mortality in patients with neoplastic diseases treated throughout Austria.
Methods: In this multicentric nationwide cohort study, data on patients with active or previous malignant diseases and SARS-CoV‑2 infections diagnosed between 13 March 2020 and 06 April 2021 were collected. Collected data included the stage of the malignant disease and outcome parameters 30 days after the diagnosis of SARS-CoV‑2 infection.
Results: The cohort consisted of 230 individuals of which 75 (32.6%) patients were diagnosed with hematologic malignancies and 155 (67.4%) with solid tumors. At a median follow-up of 31 days after COVID-19 diagnosis, 38 (16.5%) patients had died due to COVID-19. Compared to survivors, patients who died were older (62.4 vs. 71.4 years, p < 0.001) and had a higher ECOG performance status (0.7 vs. 2.43, p < 0.001). Furthermore, higher neutrophil counts (64.9% vs. 73.8%, p = 0.03), lower lymphocyte counts (21.4% vs. 14%, p = 0.006) and lower albumin levels (32.5 g/l vs. 21.6 g/l, p < 0.001) were observed to be independent risk factors for adverse outcomes. No association between mortality and systemic antineoplastic therapy was found (p > 0.05). In 60.6% of the patients, therapy was postponed due to quarantine requirements or hospital admission.
Conclusion: Mortality of Austrian cancer patients infected with SARS-CoV‑2 is comparable to that of other countries. Furthermore, risk factors associated with higher mortality were evident and similar to the general population. Treatment delays were frequently observed.
Incidence of <em>SARS</em>-<em>CoV</em>-<em>2</em> Infection and <em>Related</em> Mortality by Education Level during Three Phases of the <em>2</em>0<em>2</em>0 Pandemic: A Population-Based Cohort Study in Rome
Evidence on social determinants of health on the risk of SARS-CoV-2 infection and adverse outcomes is still limited. Therefore, this work investigates educational disparities in the incidence of infection and mortality within 30 days of the onset of infection during 2020 in Rome, with particular attention to changes in socioeconomic inequalities over time. A cohort of 1,538,231 residents in Rome on 1 January 2020, aged 35+, followed from 1 March to 31 December 2020, were considered. Cumulative incidence and mortality rates by education were estimated. Multivariable log-binomial and Cox regression models were used to investigate educational disparities in the incidence of SARS-CoV-2 infection and mortality during the entire study period and in three phases of the pandemic. During 2020, there were 47,736 incident cases and 2281 deaths.
The association between education and the incidence of infection changed over time. Till May 2020, low- and medium-educated individuals had a lower risk of infection than that of the highly educated. However, there was no evidence of an association between education and the incidence of SARS-CoV-2 infection during the summer. Lastly, low-educated adults had a 25% higher risk of infection from September to December than that of the highly educated. Similarly, there was substantial evidence of educational inequalities in mortality within 30 days of the onset of infection in the last term of 2020. In Rome, social inequalities in COVID-19 appeared in the last term of 2020, and they strengthen the need for monitoring inequalities emerging from this pandemic.
NATtrol SARS-Related Coronavirus 2 (SARS-CoV-2) Stock |
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NATSARS(COV2)-ST | Zeptometrix | Stock | 935 EUR |
SARS Coronavirus |
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MBS320182-01mg | MyBiosource | 0.1mg | 420 EUR |
SARS Coronavirus |
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MBS320182-5x01mg | MyBiosource | 5x0.1mg | 1815 EUR |
SARS Coronavirus |
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MBS320183-01mg | MyBiosource | 0.1mg | 420 EUR |
SARS Coronavirus |
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MBS320183-5x01mg | MyBiosource | 5x0.1mg | 1815 EUR |
SARS coronavirus |
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MBS320548-01mg | MyBiosource | 0.1mg | 420 EUR |
SARS coronavirus |
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MBS320548-5x01mg | MyBiosource | 5x0.1mg | 1815 EUR |
SARS coronavirus |
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MBS320549-01mg | MyBiosource | 0.1mg | 420 EUR |
SARS coronavirus |
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MBS320549-5x01mg | MyBiosource | 5x0.1mg | 1815 EUR |
SARS coronavirus |
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MBS320550-01mg | MyBiosource | 0.1mg | 420 EUR |
SARS coronavirus |
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MBS320550-5x01mg | MyBiosource | 5x0.1mg | 1815 EUR |
SARS coronavirus antigen |
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30-2000 | Fitzgerald | 200 ug | Ask for price |
SARS Coronavirus Antibody |
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10-2856 | Fitzgerald | 1 mg | 900 EUR |
SARS Coronavirus Antibody |
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10-2857 | Fitzgerald | 1 mg | 900 EUR |
SARS Coronavirus Antibody |
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10-2860 | Fitzgerald | 1 mg | 900 EUR |
SARS Coronavirus Antibody |
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10-2861 | Fitzgerald | 1 mg | 900 EUR |
SARS Coronavirus antibody |
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10C-CR9003M1 | Fitzgerald | 100 ug | 205 EUR |
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10C-CR9003M2 | Fitzgerald | 1 mg | 495 EUR |
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MBS532601-5x1mg | MyBiosource | 5x1mg | 3860 EUR |
SARS coronavirus E protein |
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30R-2290 | Fitzgerald | 200 ug | Ask for price |
SARS coronavirus M protein |
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30R-2291 | Fitzgerald | 200 ug | Ask for price |
SARS & COVID-19 coronavirus |
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3862 | Virostat | each | 330 EUR |
SARS & COVID-19 coronavirus |
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3863 | Virostat | each | 330 EUR |
SARS & COVID-19 coronavirus |
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3864 | Virostat | each | 330 EUR |
Model-Estimated Association Between Simulated US Elementary School-<em>Related</em> <em>SARS</em>-<em>CoV</em>-<em>2</em> Transmission, Mitigation Interventions, and Vaccine Coverage Across Local Incidence Levels
Importance: With recent surges in COVID-19 incidence and vaccine authorization for children aged 5 to 11 years, elementary schools face decisions about requirements for masking and other mitigation measures. These decisions require explicit determination of community objectives (eg, acceptable risk level for in-school SARS-CoV-2 transmission) and quantitative estimates of the consequences of changing mitigation measures.
Objective: To estimate the association between adding or removing in-school mitigation measures (eg, masks) and COVID-19 outcomes within an elementary school community at varying student vaccination and local incidence rates.
Design, setting, and participants: This decision analytic model used an agent-based model to simulate SARS-CoV-2 transmission within a school community, with a simulated population of students, teachers and staff, and their household members (ie, immediate school community). Transmission was evaluated for a range of observed local COVID-19 incidence (0-50 cases per 100 000 residents per day, assuming 33% of all infections detected). The population used in the model reflected the mean size of a US elementary school, including 638 students and 60 educators and staff members in 6 grades with 5 classes per grade.
Exposures: Variant infectiousness (representing wild-type virus, Alpha variant, and Delta variant), mitigation effectiveness (0%-100% reduction in the in-school secondary attack rate, representing increasingly intensive combinations of mitigations including masking and ventilation), and student vaccination levels were varied.
Main outcomes and measures: The main outcomes were (1) probability of at least 1 in-school transmission per month and (2) mean increase in total infections per month among the immediate school community associated with a reduction in mitigation; multiple decision thresholds were estimated for objectives associated with each outcome. Sensitivity analyses on adult vaccination uptake, vaccination effectiveness, and testing approaches (for selected scenarios) were conducted.
Results: With student vaccination coverage of 70% or less and moderate assumptions about mitigation effectiveness (eg, masking), mitigation could only be reduced when local case incidence was 14 or fewer cases per 100 000 residents per day to keep the mean additional cases associated with reducing mitigation to 5 or fewer cases per month. To keep the probability of any in-school transmission to less than 50% per month, the local case incidence would have to be 4 or fewer cases per 100 000 residents per day.
Conclusions and relevance: In this study, in-school mitigation measures (eg, masks) and student vaccinations were associated with substantial reductions in transmissions and infections, but the level of reduction varied across local incidence. These findings underscore the potential role for responsive plans that deploy mitigation strategies based on local COVID-19 incidence, vaccine uptake, and explicit consideration of community objectives.