Systematic review of the clinical effectiveness of Tixagevimab/Cilgavimab for prophylaxis of COVID-19 in immunocompromised patients (preprint)

Background and aims Immunocompromised patients have a reduced ability to generate antibodies after COVID-19 vaccination and are at higher risk of SARS-CoV-2 infection, complications and mortality. Tixagevimab/Cilgavimab (Evusheld) is a monoclonal antibody combination which bind to the SARS-CoV-2 spike protein, preventing the virus entering human cells. The phase III PROVENT trial reported that immunocompromised patients given Tixagevimab/Cilgavimab had a significantly reduced risk of COVID-19 infection. However, PROVENT was conducted before the SARS-CoV-2 Omicron became prevalent. This systematic review provides an updated summary of real-world clinical evidence of Tixagevimab/Cilgavimab effectiveness in immunocompromised patients. Methods Two independent reviewers conducted PubMed and medRxiv searches for the period of 01/01/2021 to 01/10/2022. Clinical studies which reported the primary outcome of breakthrough COVID-19 infections after Tixagevimab/Cilgavimab administration were included in the review. COVID-19-related hospitalisations, ITU admissions and mortality were assessed as secondary outcomes. Clinical effectiveness was determined using the case-control clinical effectiveness methodology. The GRADE tool was used to ascertain the level of certainty for the primary outcome in each study. Results 17 clinical studies were included, comprising 24,773 immunocompromised participants of whom 10,775 received Tixagevimab/Cilgavimab. Most studies reported clinical outcomes during the SARS-CoV-2 Omicron wave. Six studies compared a Tixagevimab/Cilgavimab intervention group to a control group. Overall, the clinical effectiveness of prophylactic Tixagevimab/Cilgavimab against COVID-19 breakthrough infection, hospitalisation and ITU admission were 40.47%, 69.23% and 87.89%, respectively. For prevention of all-cause and COVID-19-specifc mortality, overall clinical effectiveness was 81.29% and 86.36%, respectively. Conclusions There is a growing body of real-world evidence validating the original PROVENT phase III study regarding the clinical effectiveness of Tixagevimab/Cilgavimab as prophylaxis for immunocompromised patients, notably demonstrating effectiveness during the Omicron wave. This review demonstrates the clinical effectiveness of prophylactic Tixagevimab/Cilgavimab at reducing COVID-19 infection, hospitalisation, ITU admission and mortality for immunosuppressed individuals. It is important that ongoing larger-scale and better-controlled real world studies are initiated and evaluated to provide ongoing certainty of the clinical benefit of prophylactic antibody treatment for immunocompromised patients in the face of new variants.

SARS-CoV-2 infectivity by viral load, S gene variants and demographic factors and the utility of lateral flow devices to prevent transmission (preprint)

Background How SARS-CoV-2 infectivity varies with viral load is incompletely understood. Whether rapid point-of-care antigen lateral flow devices (LFDs) detect most potential transmission sources despite imperfect sensitivity is unknown. Methods We combined SARS-CoV-2 testing and contact tracing data from England between 01-September-2020 and 28-February-2021. We used multivariable logistic regression to investigate relationships between PCR-confirmed infection in contacts of community-diagnosed cases and index case viral load, S gene target failure (proxy for B.1.1.7 infection), demographics, SARS-CoV-2 incidence, social deprivation, and contact event type. We used LFD performance to simulate the proportion of cases with a PCR-positive contact expected to be detected using one of four LFDs. Results 231,498/2,474,066 (9%) contacts of 1,064,004 index cases tested PCR-positive. PCR-positive results in contacts independently increased with higher case viral loads (lower Ct values) e.g., 11.7%(95%CI 11.5-12.0%) at Ct=15 and 4.5%(4.4-4.6%) at Ct=30. B.1.1.7 infection increased PCR-positive results by ∼50%, (e.g. 1.55-fold, 95%CI 1.49-1.61, at Ct=20). PCR-positive results were most common in household contacts (at Ct=20.1, 8.7%[95%CI 8.6-8.9%]), followed by household visitors (7.1%[6.8-7.3%]), contacts at events/activities (5.2%[4.9-5.4%]), work/education (4.6%[4.4-4.8%]), and least common after outdoor contact (2.9%[2.3-3.8%]). Contacts of children were the least likely to test positive, particularly following contact outdoors or at work/education. The most and least sensitive LFDs would detect 89.5%(89.4-89.6%) and 83.0%(82.8-83.1%) of cases with PCR-positive contacts respectively. Conclusions SARS-CoV-2 infectivity varies by case viral load, contact event type, and age. Those with high viral loads are the most infectious. B.1.1.7 increased transmission by ∼50%. The best performing LFDs detect most infectious cases. Key points In 2,474,066 contacts of 1,064,004 SARS-CoV-2 cases, PCR-positive tests in contacts increased with higher index case viral loads, the B.1.1.7 variant and household contact. Children were less infectious. Lateral flow devices can detect 83.0-89.5% of infections leading to onward transmission.

A Systematic Review of the Sensitivity and Specificity of Lateral Flow Devices in the Detection of SARS-CoV-2 (preprint)

Background: Lateral flow devices (LFDs) are viral antigen tests for the detection of SARS-CoV-2 that produce a rapid result, are inexpensive and easy to operate. They have been advocated for use by the World Health Organisation to help control outbreaks and break the chain of transmission of COVID-19 infections. There are now several studies assessing their accuracy but as yet no systematic review. Our aims were to assess the sensitivity and specificity of LFDs in a systematic review and summarise the sensitivity and specificity of these tests. Methods: A targeted search of Pubmed and Medxriv, using PRISMA principles, was conducted identifying clinical studies assessing the sensitivity and specificity of LFDs as their primary outcome compared to reverse transcriptase polymerase chain reaction (RT-PCR) for the detection of SARS-CoV-2. Based on extracted data sensitivity and specificity was calculated for each study. Data was pooled based on manufacturer of LFD and split based on operator (self-swab or by trained professional) and sensitivity and specificity data were calculated. Results: Twenty-four papers were identified involving over 26,000 test results. Sensitivity from individual studies ranged from 37.7% (95% CI 30.6-45.5) to 99.2% (95% CI 95.5-99.9) and specificity from 92.4% (95% CI 87.5-95.5) to 100.0% (99.7-100.0). BD Veritor was the best performing manufacturer of LFD with a sensitivity of 99.2% (95% CI 95.5-99.9) and specificity of 100.0% (98.9-100.0). Operation of the test by a trained professional or by the test subject with self-swabbing produced comparable results. Conclusions: This systematic review identified that the performance of lateral flow devices is heterogeneous and dependent on the manufacturer. Some perform with high specificity with reasonable sensitivity. Test performance does appear dependent on the operator. Potentially, LFDs could support the scaling up of mass testing to aid track and trace methodology and break the chain of transmission of COVID-19 with the additional benefit of providing individuals with the results in a much shorter time frame.

Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants (preprint)

The COVID-19 pandemic has greatly affected us all, from individuals to the world economy. Whereas great advances have been achieved in record time, a lot remains to be learned about the infection mechanisms of its causative agent, the SARS-CoV-2 coronavirus. The Spike protein interacts with the human angiotensin converting enzyme 2 receptor as part of the viral entry mechanism. To do so, the receptor binding domain (RBD) of Spike needs to be in an open state conformation. Here we utilise coarse-grained normal mode analyses to model the dynamics of the SARS-CoV-2 Spike protein and the transition probabilities between open and closed conformations for the wild type, the D614G mutant as well other variants isolated experimentally. We proceed to perform several possible in silico single mutations of Spike, 17081 in total, to determine positions and specific Spike mutations that may affect the occupancy of the open and closed states. We estimate transition probabilities between the open and closed states from the calculated normal modes. Transition probabilities are employed in a Markov model to determine conformational state occupancies. Our results correctly model a shift in occupancy of the more infectious D614G strain towards higher occupancy of the open state via an increase of flexibility of the closed state and concomitant decrease of flexibility of the open state. Our results also suggest that the N501Y mutation recently observed, drastically increases the occupancy of the open state. We utilize global vibrational entropy differences to select candidate single point mutations that affect the flexibility of the open and closed states and confirm that these lead to shifts in occupancies for the most critical mutations. Among those, we observe a number of mutations on Glycine residues (404, 416, 504) and G252 in particular accepting a number of mutations. Other residues include K417, D467 and N501. This is, to our knowledge, the first use of normal mode analysis to model conformational state transitions and the effect of mutations thereon. The specific mutations of Spike identified here, while still requiring experimental validation, may guide future studies to increase our understanding of SARS-CoV-2 infection mechanisms as well as guide public health in their surveillance efforts.

Influence of clinical characteristics and anti-cancer therapy on outcomes from SARS-CoV-2 infection: a systematic review and meta-analysis of 5,678 cancer patients (preprint)

Background The COVID-19 pandemic started a healthcare crisis and heavily impacted cancer services. Methods Data from cohort studies of COVID-19 cancer patients published up until October 23rd 2020 from PubMed, PubMed Central, medRxiv and Google Scholar were reviewed. Meta-analyses using the random effects model was performed to assess the risk of death in cancer patients with COVID-19. Results Our meta-analyses including up to 5,678 patients from 13 studies showed that the following were all statistically significant risk factors for death following SARS-CoV-2 infection in cancer patients: age of 65 and above, presence of co-morbidities, cardiovascular disease, chronic lung disease, diabetes and hypertension. There was no evidence that patients who had received cancer treatment within 60 days of their COVID-19 diagnosis were at a higher risk of death, including patients who had recent chemotherapy. Conclusions Cancer patients are susceptible to severe COVID-19, especially older patients and patients with co-morbidities who will require close monitoring. Our findings support the continued administration of anti-cancer therapy during the pandemic. The analysis of chemotherapy was powered at 70% to detect an effect size of 1.2 but all other anti-cancer treatments had lower power. Further studies are required to better estimate their impact on the outcome of cancer patients.

Suppression of miR-155 attenuates lung cytokine storm induced by SARS-CoV-2 infection in human ACE2-transgenic mice (preprint)

Coronavirus disease 2019 (COVID-19) is a recent global pandemic. It is a deadly human viral disease, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a high rate of infection, morbidity and mortality. Therefore, there is a great urgency to develop new therapies to control, treat and prevent this disease. Endogenous microRNAs (miRNAs, miRs) of the viral host are key molecules in preventing viral entry and replication, and building an antiviral cellular defense. Here, we have analyzed the role of miR-155, one of the most powerful drivers of host antiviral responses including immune and inflammatory responses, in the pathogenicity of SARS-CoV-2 infection. Subsequently, we have analyzed the potency of anti-miR-155 therapy in a COVID-19 mouse model (mice transgenic for human angiotensin I- converting enzyme 2 receptor (tg-mice hACE2)). We report for the first time that miR-155 expression is elevated in COVID-19 patients. Further, our data indicate that the viral load as well as miR-155 levels are higher in male relative to female patients. Moreover, we find that the delivery of anti-miR-155 to SARS-CoV-2-infected tg-mice hACE2 effectively suppresses miR-155 expression, and leads to improved survival and clinical scores. Importantly, anti-miR-155-treated tg-mice hACE2 infected with SARS-CoV-2 not only exhibit reduced levels of pro-inflammatory cytokines, but also have increased anti-viral and anti-inflammatory cytokine responses in the lungs. Thus, our study suggests anti-miR-155 as a novel therapy for mitigating the lung cytokine storm induced by SARS-CoV-2 infection.

Molecular diversity analysis of the spike glycoprotein (S) gene from Hong Kong - China (preprint)

In this work, 37 haplotypes of spike glycoprotein of SARS-CoV-2 from Hong Kong, China, were used. All sequences were publicly available on the Platform of the National Center for Biotechnology Information (NCBI) and were analyzed for their Molecular Variance (AMOVA), haplotypic diversity, mismatch, demographic and spatial expansion, molecular diversity and time of evolutionary divergence. The results suggested that there was a low diversity among haplotypes, with very low numbers of transitions, transversions, indels-type mutations and with total absence of population expansion perceived in the neutrality tests. The estimators used in this study supported the uniformity among all the results found and confirm the evolutionary conservation of the gene, as well as its protein product, a fact that stimulates the use of therapies based on neutralizing antibodies, such as vaccines based on protein S.

Ruling the Roost: Avian Species Reclaim Urban Habitat During India's COVID Lockdown (preprint)

As we retreated to our dwellings in the "anthropause" of spring 2020, did other species return to our urban centres? We leverage an increase in balcony birdwatching, a million eBird entries, and difference-in-difference techniques to test if avian species richness rose during Indias COVID lockdown. We find that birdwatchers in Indias 20 most populous cities observed 8-17% more species during the lockdown. Most additional observations occurred after a two-week lag, signaling greater abundance instead of improved detection. More frequent appearances of at-risk, rare, and common species were recorded, implying that making our cities more wildlife friendly can protect threatened species in addition to urban specialists. Our contributions are: 1) to isolate and estimate a causal impact of reducing human activity on avian diversity, 2) to improve the external validity of this literature in rapidly urbanizing bio-diverse developing countries, and, 3) to illustrate a method separating abundance from detection in observational avian surveys.

The rapid, massive infection of the scientific literature and authors by COVID-19 (preprint)

ImportanceCOVID-19 is a major global crisis and the scientific community has been mobilized to deal with this crisis. ObjectiveTo estimate the extent to which the scientific workforce in different fields has been engaged publishing papers relative to the COVID-19 pandemic. Design, setting, and participantsWe evaluated Scopus (data cut, December 1, 2020) for all indexed published papers and preprints relevant to COVID-19. We mapped this COVID-19 literature in terms of its authors across 174 subfields of science according to the Science Metrix classification. We also evaluated the extent to which the most influential scientists across science (based on a composite citation indicator) had published COVID-19-related research. Finally, we assessed the features of authors who published the highest number of COVID-19 publications and of those with the highest impact in the COVID-19 field based on the composite citation indicator limited to COVID-19 publications. Main outcomes and measuresPublishing scientists (authors) and their published papers and citation impact. Results84,180 indexed publications were relevant to COVID-19 including 322,279 unique authors. The highest rates of COVID-19 publications were seen for authors classified in Public Health and in Clinical Medicine, where 11.3% (6,388/56,516) and 11.1% (92,570/833,060) of authors, respectively, had published on COVID-19. Almost all (173/174) subfields (except for Automobile Design & Engineering) had some authors publishing on COVID-19. Among active scientists at the top 2% of citation impact, 15,803 (13.3%) had published on COVID-19 in their publications in the first 11 months of 2020. The rates were the highest in the fields of Clinical Medicine (27.7%) and Public Health (26.8%). In 83 of the 174 subfields of science, at least one in ten active, influential authors in that field had authored something on COVID-19. 65 authors had already at least 30 (and up to 133) COVID-19 publications each. Among the 300 authors with the highest composite citation indicator for COVID-19 publications, 26 were journalists or editors publishing news stories or editorials in prestigious journals; most common countries for the remaining were China (n=77), USA (n=66), UK (n=27), and Italy (n=20). Conclusions and relevanceThe scientific literature and publishing scientists have been rapidly and massively infected by COVID-19 creating opportunities and challenges. There is evidence for hyper-prolific productivity.

Comprehensive Systematic Review to Identify putative COVID-19 Treatments: Roles for Immunomodulator and Antiviral Treatments (preprint)

Objectives: To identify putative COVID-19 treatments and identify the roles of immunomodulators and antivirals in disease management. Design: Systematic review. Data sources: PubMed, bioRxiv.org and medRxiv.org were searched for studies suggestive of effective treatments for COVID-19. Additional studies were identified via a snowballing method applied to the references of retrieved papers as well as a subsequent targeted search for drug names. Review methods: Inclusion criteria included any case series or randomised control trials in any language that were published from 18th December 2019 to 18th April 2020 and described COVID-19 treatment. Of an initial 2140 studies identified from the initial search, 29 studies were found to meet the inclusion criteria and included in this comprehensive systematic review. Results: 19 studies of antiviral treatments for COVID-19 have been reported and seven studies for immunomodulatory treatments. Six randomised controlled trials have been published with one positive trial for Hydroxychloroquine. This small study consisted of 31 patients though subsequent studies showed contradictory findings. All the remaining studies were observational studies, retrospective case reviews or non-randomised trials and these results are difficult to interpret due to methodological issues. Conclusions: To date, an impressive number of studies have been performed in a short space of time, indicative of a resilient clinical trials infrastructure. However, there is a lack of high quality evidence to support any novel treatments for COVID-19 to be incorporated into the current standard of care. The majority of the studies of treatments for COVID-19 could only be found in pre-print servers. Future clinical reviews should therefore be Comprehensive Systematic Reviews involving pre-print studies to prevent potential unnecessary replications of clinical studies.