Covid19-Sources

Literaturübersicht zur Wirksamkeit von Masken, Stand 20-11-2020

The COVID-19 pandemic is seemingly driving birthrates down – but it's not the only thing behind the global fertility decline. Here's what's behind it and why it matters.

The global race to develop a COVID-19 vaccine is on. Here are the different types of vaccines and how your body uses them to develop immunity.

But in the days following the start of the vaccination campaign, a new development became evident: Several of the recently vaccinated HCWs developed symptoms of Covid-19, and an infection with SARS-CoV-2 was confirmed by PCR. Of the 1306 HCWs who had received a first dose of the vaccine by January 18th, 2021, seven HCWs tested positive. A symptomatic infection was confirmed on day two, four, seven, eleven, sixteen, seventeen and nineteen after receiving the first dose, respectively. The recently vaccinated made up 35% of the total number of the 20 employees of the University Hospital who tested positive in that time period, meaning the recently vaccinated were overrepresented among those with a symptomatic infection. Of those who had been inoculated and later tested positive, some may have already been in the incubation period when receiving the vaccine, but others likely became infected shortly after receiving the first dose.

With the COVID-19 pandemic now ongoing for close to a year, people all over the world are still waiting for a vaccine to become available. The initial…

The authors explore how seasonal variation in transmissibility could modulate a SARS-CoV-2 pandemic. The likely aggregated effect of seasonal variation, infection control measures, and transmission rate variation is a prolonged pandemic wave with lower prevalence at any given time, thereby providing a window of opportunity for better preparation of health care systems.

Superspreading complicates the study of SARS-CoV-2 transmission. I propose a model for aggregated case data that accounts for superspreading and improves statistical inference. In a Bayesian...

While seasonal variation has a known influence on the transmission of several respiratory viral infections, its role in SARS-CoV-2 transmission remains unclear. As previous analyses have not accounted for the implementation of non-pharmaceutical interventions (NPIs) in the first year of the pandemic, they may yield biased estimates of seasonal effects. Building on two state-of-the-art observational models and datasets, we adapt a fully Bayesian method for estimating the association between seasonality and transmission in 143 temperate European regions. We find strong seasonal patterns, consistent with a reduction in the time-variable R t of 42.1% (95% CI: 24.7% – 53.4%) from the peak of winter to the peak of summer. These results imply that the seasonality of SARS-CoV-2 transmission is comparable in magnitude to the most effective individual NPIs but less than the combined effect of multiple interventions. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement J. T. Monrad acknowledges funding from the Augustinus Foundation, the Knud Hojgaard Foundation, the William Demant Foundation, the Aage and Johanne Louis-Hansen Foundation, and the Kai and Gunhild Lange Foundation. M. Sharma was supported by the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems (EP/S024050/1) and a grant from the EA Funds programme. S. Mindermann's funding for graduate studies was from Oxford University and DeepMind. G.Leech was supported by the UKRI Centre for Doctoral Training in Interactive Artificial Intelligence (EP/S022937/1). S.Bhatt acknowledges funding from the MRC Centre for Global Infectious Disease Analysis (MR/R015600/1), jointly funded by the U.K. Medical Research Council (MRC) and the U.K. Foreign, Commonwealth and Development Office (FCDO), under the MRC/FCDO Concordat agreement; is a part of the EDCTP2 program supported by the European Union; and acknowledges funding by Community Jameel. J.M. Brauner was supported by the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems (EP/S024050/1) and by Cancer Research UK. S. Bhatt acknowledges The UK Research and Innovation (MR/V038109/1), the Academy of Medical Sciences Springboard Award (SBF004/1080), The MRC (MR/R015600/1), The BMGF (OPP1197730), Imperial College Healthcare NHS Trust- BRC Funding (RDA02), The Novo Nordisk Young Investigator Award (NNF20OC0059309) and The NIHR Health Protection Research Unit in Modelling Methodology. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: No approval required for research on fully anonymised data, as per the Central University Research Ethics Committee (CUREC) of the University of Oxford. https://researchsupport.admin.ox.ac.uk/governance/ethics/apply All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Spring 2020 dataset has been published in Brauner et al.: "The effectiveness of eight nonpharmaceutical interventions against COVID-19 in 41 countries". Fall-winter 2020 dataset is currently available upon request. The entire implementation is publicly available on GitHub. [https://github.com/gavento/covid\_seasonal\_Brauner][1] [https://github.com/gavento/covid\_seasonal\_Sharma][2] [1]: https://github.com/gavento/covid_seasonal_Brauner [2]: https://github.com/gavento/covid_seasonal_Sharma

Background Understanding the global spatiotemporal pattern of seasonal influenza is essential for influenza control and prevention. Available data on the updated global spatiotemporal pattern of seasonal influenza are scarce. This study aimed to assess the spatiotemporal pattern of seasonal influenza after the 2009 influenza pandemic. Methods Weekly influenza surveillance data in 86 countries from 2010 to 2017 were obtained from FluNet. First, the proportion of influenza A in total influenza viruses (PA) was calculated. Second, weekly numbers of influenza positive virus (A and B) were divided by the total number of samples processed to get weekly positive rates of influenza A (RWA) and influenza B (RWB). Third, the average positive rates of influenza A (RA) and influenza B (RB) for each country were calculated by averaging RWA, and RWB of 52 weeks. A Kruskal-Wallis test was conducted to examine if the year-to-year change in PA in all countries were significant, and a universal kriging method with linear semivariogram model was used to extrapolate RA and RB in all countries. Results PA ranged from 0.43 in Zambia to 0.98 in Belarus, and PA in countries with higher income was greater than those countries with lower income. The spatial patterns of high RB were the highest in sub-Saharan Africa, Asia-Pacific region and South America. RWA peaked in early weeks in temperate countries, and the peak of RWB occurred a bit later. There were some temperate countries with non-distinct influenza seasonality (e.g., Mauritius and Maldives) and some tropical/subtropical countries with distinct influenza seasonality (e.g., Chile and South Africa). Conclusions Influenza seasonality is not predictable in some temperate countries, and it is distinct in Chile, Argentina and South Africa, implying that the optimal timing for influenza vaccination needs to be chosen with caution in these unpredictable countries.

Although the benefit of population-level public facial masking to protect others during the COVID-19 pandemic has received a great deal of attention, we discuss for one of the first times the hypothesis that universal masking reduces the "inoculum" or dose of the virus for the mask-wearer, leading t …

The seasonality of respiratory diseases has been linked, among other factors, to low outdoor absolute humidity and low indoor relative humidity, which increase evaporation of water in the mucosal lining of the respiratory tract. We demonstrate that normal breathing results in an absorption-desorption cycle inside facemasks, in which supersaturated air is absorbed by the mask fibers during expiration, followed by evaporation during inspiration of dry environmental air. For double-layered cotton masks, which have considerable heat capacity, the temperature of inspired air rises above room temperature, and the effective increase in relative humidity can exceed 100%.

New data from a large healthcare organization in Israel reveal a reduction in new infections in an unvaccinated population in communities with rapid vaccination rollouts, suggesting that mass vaccination strategies confer cross-protection of unvaccinated individuals.

The study, based on anonymized Israeli medical records, showed that vaccination’s benefits extend to people who have not received a shot.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve around the world, generating new variants that are of concern based on their potential for altered transmissibility, pathogenicity, and coverage by vaccines and therapeutics1–5. Here we report that 20 human sera, drawn 2 or 4 weeks after two doses of BNT162b2, neutralize engineered SARS-CoV-2 with a USA-WA1/2020 genetic background (a virus strain isolated in January 2020) and spike glycoproteins from the newly emerged B.1.617.1, B.1.617.2, B.1.618 (all first identified in India) or B.1.525 (first identified in Nigeria) lineages. Geometric mean plaque reduction neutralization titers against the variant viruses, particularly the B.1.617.1 variant, appear lower than the titer against USA-WA1/2020 virus, but all sera tested neutralize the variant viruses at titers of at least 40. The susceptibility of these newly emerged variants to BNT162b2 vaccine-elicited neutralization supports mass immunization as a central strategy to end the coronavirus disease 2019 (COVID-19) pandemic across geographies.

Moderna will take mRNA flu and HIV vaccines into Phase 1 trials this year, as well as beginning a pivotal Phase 3 study for its cytomegalovirus (CMV) vaccine candidate.

Scientists are starting to get insights into the lingering disorder that affects some people infected with SARS-CoV-2 — but many mysteries remain unsolved.

This work is concerned with the spatiotemporal dynamics of the coronavirus disease 2019 (COVID-19) in Germany. Our goal is twofold: first, we propose a novel spatial econometric model of the epidemic spread across NUTS-3 regions to identify the role played by commuting-to-work patterns for spatial disease transmission. Second, we explore if the imposed containment (lockdown) measures during the first pandemic wave in spring 2020 have affected the strength of this transmission channel. Our results from a spatial panel error correction model indicate that, without containment measures in place, commuting-to-work patterns were the first factor to significantly determine the spatial dynamics of daily COVID-19 cases in Germany. This indicates that job commuting, particularly during the initial phase of a pandemic wave, should be regarded and accordingly monitored as a relevant spatial transmission channel of COVID-19 in a system of economically interconnected regions. Our estimation results also provide evidence for the triggering role of local hot spots in disease transmission and point to the effectiveness of containment measures in mitigating the spread of the virus across German regions through reduced job commuting and other forms of mobility.

The disruptions caused by the Covid-19 pandemic might turn out to be greater than any other event since the Second World War. Governments and authorities around the world therefore have taken drastic measures since early 2020 to slow down the pandemic. Measures include the closing of schools and non-essential sales shops, mandatory face masks, travel and contact restrictions and even contact bans or curfews. It is no surprise that these measures encounter partially fierce protests by some politicians and parts of the public. It is high time to understand how effective the various measures were in reducing the spread of Covid-19 to be prepared for future epidemic and pandemic developments. This is the purpose of this paper.

Since the emerging of the "novel coronavirus" SARS-CoV-2 and the corresponding respiratory disease COVID-19, the virus has spread all over the world. Being one of the most affected countries in Europe, in March 2020, Germany established several nonpharmaceutical interventions to contain the virus spread, including the closure of schools and child day care facilities (March 16-18, 2020) as well as a full "lockdown" with forced social distancing and closures of "nonessential" services (March 23, 2020). The present study attempts to analyze whether these governmental interventions had an impact on the declared aim of "flattening the curve", referring to the epidemic curve of new infections. This analysis is conducted from a regional perspective. On the level of the 412 German counties, logistic growth models were estimated based on daily infections (estimated from reported cases), aiming at determining the regional growth rate of infections and the point of inflection where infection rates begin to decrease and the curve flattens. All German counties exceeded the peak of new infections between the beginning of March and the middle of April. In a large majority of German counties, the epidemic curve has flattened before the "lockdown" was established. In a minority of counties, the peak was already exceeded before school closures. The growth rates of infections vary spatially depending on the time the virus emerged. Counties belonging to states which established an additional curfew show no significant improvement with respect to growth rates and mortality. Furthermore, mortality varies strongly across German counties, which can be attributed to infections of people belonging to the "risk group", especially residents of retirement homes. The decline of infections in absence of the "lockdown" measures could be explained by 1) earlier governmental interventions (e.g., cancellation of mass events, domestic quarantine), 2) voluntary behavior changes (e.g., physical distancing and hygiene), 3) seasonality of the virus, and 4) a rising but undiscovered level of immunity within the population. The results raise the question whether formal contact bans and curfews really contribute to curve flattening within a pandemic.

Knowledge about the origin of SARS-CoV-2 is necessary for both a biological and epidemiological understanding of the COVID-19 pandemic. Evidence suggests that a

Emergence of SARS-CoV-2 variants, including the globally successful B.1.1.7 lineage, suggests viral adaptations to host selective pressures resulting in more efficient transmission. Although much effort has focused on Spike adaptation for viral entry and adaptive immune escape, B.1.1.7 mutations outside Spike likely contribute to enhance transmission. Here we used unbiased abundance proteomics, phosphoproteomics, mRNA sequencing and viral replication assays to show that B.1.1.7 isolates more effectively suppress host innate immune responses in airway epithelial cells. We found that B.1.1.7 isolates have dramatically increased subgenomic RNA and protein levels of Orf9b and Orf6, both known innate immune antagonists. Expression of Orf9b alone suppressed the innate immune response through interaction with TOM70, a mitochondrial protein required for RNA sensing adaptor MAVS activation, and Orf9b binding and activity was regulated via phosphorylation. We conclude that B.1.1.7 has evolved beyond the Spike coding region to more effectively antagonise host innate immune responses through upregulation of specific subgenomic RNA synthesis and increased protein expression of key innate immune antagonists. We propose that more effective innate immune antagonism increases the likelihood of successful B.1.1.7 transmission, and may increase in vivo replication and duration of infection. ### Competing Interest Statement The Krogan Laboratory has received research support from Vir Biotechnology and F. Hoffmann-La Roche. Nevan Krogan has consulting agreements with the Icahn School of Medicine at Mount Sinai, New York, Maze Therapeutics and Interline Therapeutics, is a shareholder of Tenaya Therapeutics and has received stocks from Maze Therapeutics and Interline Therapeutics. The A.G.-S. laboratory has received research support from Pfizer, Senhwa Biosciences, Kenall Manufacturing, Avimex, Johnson & Johnson, Dynavax, 7Hills Pharma, Pharmamar, ImmunityBio, Accurius, Nanocomposix and Merck. A.G.-S. has consulting agreements for the following companies involving cash and/or stock: Vivaldi Biosciences, Contrafect, 7Hills Pharma, Avimex, Vaxalto, Pagoda, Accurius, Esperovax, Farmak and Pfizer. A.G.-S. is inventor on patents and patent applications on the use of antivirals and vaccines for the treatment and prevention of virus infections, owned by the Icahn School of Medicine at Mount Sinai, New York.

SARS-CoV-2 lineage B.1.1.7 viruses are more transmissible, may lead to greater clinical severity, and result in modest reductions in antibody neutralization. subgenomic RNA (sgRNA) is produced by discontinuous transcription of the SARS-CoV-2 genome and is a crucial step in the SARS-CoV-2 life cycle. Applying our tool (periscope) to ARTIC Network Oxford Nanopore genomic sequencing data from 4400 SARS-CoV-2 positive clinical samples, we show that normalised sgRNA expression profiles are significantly increased in B.1.1.7 infections (n=879). This increase is seen over the previous dominant circulating lineage in the UK, B.1.177 (n=943), which is independent of genomic reads, E gene cycle threshold and days since symptom onset at sampling. A noncanonical sgRNA which could represent ORF9b is found in 98.4% of B.1.1.7 SARS-CoV-2 infections compared with only 13.8% of other lineages, with a 16-fold increase in median expression. We hypothesise that this is a direct consequence of a triple nucleotide mutation in nucleocapsid (28280:GAT>CAT, D3L) creating a transcription regulatory-like sequence complementary to a region 3’ of the genomic leader. These findings provide a unique insight into the biology of B.1.1.7 and support monitoring of sgRNA profiles in sequence data to evaluate emerging potential variants of concern. One Sentence Summary The recently emerged and more transmissible SARS-CoV-2 lineage B.1.1.7 shows greater subgenomic RNA expression in clinical infections and enhanced expression of a noncanonical subgenomic RNA near ORF9b. ### Competing Interest Statement The authors have declared no competing interest.

The rapid spread of the B.1.1.7 variant — also called Alpha — might be linked to its ability to dampen the body’s initial immune response.

Research and data to make progress against the world’s largest problems

Throughout 2020, the notion that the novel coronavirus leaked from a lab was off-limits. Those who dared to push for transparency say toxic politics and hidden agendas kept us in the dark.

A proportion of patients surviving acute COVID-19 infection develop post-COVID syndrome (long COVID) encompassing physical and neuropsychiatric symptoms lasting longer than 12 weeks. Here we studied a prospective cohort of individuals with long COVID (the ADAPT study) compared to age/gender matched subjects without long COVID, healthy donors and individuals infected with other non-SARS CoV2 human coronaviruses (the ADAPT-C study). We found an elevated diffuse serum inflammatory cytokine profile in symptomatic long COVID subjects that was maintained at 8 months post-infection and was not observed in asymptomatic COVID-19 survivors. This inflammatory profile consisted of 15 cytokines that positively correlated; revealing an apparent diffuse, potentially coordinated, low level up regulation of a spectrum of immune and inflammatory mediators. In addition, we found an absence of subsets of un-activated naїve T and B cells in peripheral blood of long COVID subjects, that did not reconstitute over time. In contrast, individual serum cytokines from the interferon I and III classes, T cell activation markers and plasma ACE2, while elevated in the serum of people previously infected with SARS-CoV-2 were not further elevated in subjects with long COVID symptoms. This work defines immunological parameters associated with long COVID and suggests future opportunities to prevention and treatment. ### Competing Interest Statement The authors have declared no competing interest. ### Clinical Trial ACTRN12620000554965 ### Funding Statement We appreciate grant support from the St Vincents Clinic Foundation - the Curran Foundation, the Rapid Response Research Fund (UNSW) - the Medical Research Futures Fund (Australia) - NHMRC programme grant APP 1055214 (LMB) - Medical Research Future Fund award GNT 1175865 - - Austin Medical Research Foundation Grant - the Victorian Government - MRFF Award (2005544) - NHMRC program grant (1149990) - NHMRC Fellowships 1136322 and 1123673 ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: - The ADAPT study was approved by the St Vincents Hospital Research Ethics Committee (2020/ETH00964) and is a registered trial (ACTRN12620000554965) - ADAPT-C sub study was approved by the same committee (2020/ETH01429) - All data were stored using REDCap electronic data capture tools - Unexposed healthy donors were recruited through St Vincents Hospital and was approved by St Vincents Hospital Research Ethics Committee (HREC/13/SVH/145) - The University of Melbourne unexposed donors were approved by Medicine and Dentistry HESC-Study ID 2056689. All participants gave written informed consent. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Source data files will be uploaded upon submission to intended journal

Mortality patterns of selected European countries and regions, week ending 3 January 2020 (Week 1) to week ending 1 January 2021 (Week 53).

Introduction This observational study looked at 255 COVID19 patients who required invasive mechanical ventilation (IMV) during the first two months of the US pandemic. Through comprehensive, longitudinal evaluation and new consideration of all the data, we were able to better describe and understand factors affecting outcome after intubation. Methods All vital signs, laboratory values, and medication administrations (time, date, dose, and route) were collected and organized. Further, each patient’s prior medical records, including PBM data and available ECG, were reviewed by a physician. These data were incorporated into time-series database for statistical analysis. Results By discharge or Day 90, 78.2% of the cohort expired. The most common pre-existing conditions were hypertension, (63.5%), diabetes (59.2%) and obesity (50.4%). Age correlated with death. Comorbidities and clinical status on presentation were not predictive of outcome. Admission markers of inflammation were universally elevated (>96%). The cohort’s weight range was nearly 7-fold. Causal modeling establishes that weight-adjusted HCQ and AZM therapy improves survival by over 100%. QTc prolongation did not correlate with cumulative HCQ dose or HCQ serum levels. Discussion This detailed approach gives us better understanding of risk factors, prognostic indicators, and outcomes of Covid patients needing IMV. Few variables were related to outcome. By considering more factors and using new methods, we found that when increased doses of co-administered HCQ and AZM were associated with >100% increase in survival. Comparison of absolute with weight-adjusted cumulative doses proves administration ≥80 mg/kg of HCQ with > 1 gm AZM increases survival in IMV-requiring Covid patients by over 100%. According to our data, HCQ is not associated with prolongation. Studies, which reported QTc prolongation secondary to HCQ, need to be re-evaluated more stringently and with controls. The weight ranges of Covid patient cohorts are substantially greater than those of most antibiotic RCTs. Future clinical trials need to consider the weight variance of hospitalized Covid patients and need to study therapeutics more thoughtfully. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement No external funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Saint Barnabas Medical Center is a 557-bed, teaching medical center in Livingston, New Jersey. Using the hospital's discharge coding data, we identified 255 Covid patients, who were admitted by May 1, 2020 and required invasive mechanical ventilation (IMV). Ethical approval for the study was granted by the hospital's Institutional Review Board. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Data were extracted and combined into a database. Each patient's data were combined into a dataset containing relevant time, date, result, and dosing information. In addition, each chart was reviewed to extract past medical history, prior medical attention, and outpatient medication use. These are available upon request in large format time series datasets in CSV filetype.

Most of the major life-threatening symptoms of COVID-19 disease are associated with the host's generation of an exacerbated pro-inflammatory immune response. Many studies have correlated the intensity of the immune response with the severity of disease.

Rapid growth of the SARS-CoV-2 variant B.1.617.2 has been observed in many countries. The factors driving the recent rapid growth of COVID-19 cases could be attributed to shorten generation intervals or higher transmissibility (effective reproduction number, R), or both. Establishing the reasons for the observed rapid growth is key for outbreak control. In this study, we analysed the serial interval of household transmission pairs infected with SARS-CoV-2 B.1.617.2 variant and compared with those who were infected prior to the occurrence of the major global SARS-CoV-2 variants. After controlling for confounding factors, our findings suggest no significant changes in the serial intervals for SARS-CoV-2 cases infected with the B.1.617.2 variant. This, in turn, lends support for the hypothesis of a higher R in B.1.617.2 cases. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The following funding sources are acknowledged as providing funding for the named authors. Singapore Ministry of Health (RP). This research was partly funded by the National Institute for Health Research (NIHR) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK Department of Health and Social Care (NIHR200908: AJK). Wellcome Trust (206250/Z/17/Z: AJK). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: London School of Hygiene and Tropical Medicine Ethics Committee All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All code and data to reproduce the analysis can be found at https://github.com/rachaelpung/serial\_interval\_covid_b.1.617.2 [https://github.com/rachaelpung/serial\_interval\_covid_b.1.617.2][1] [1]: https://github.com/rachaelpung/serial_interval_covid_b.1.617.2