Viral burdens are associated with age and viral variant in a population-representative study of SARS-CoV-2 that accounts for time-since-infection related sampling bias. (preprint)

In this study, we evaluated the impact of viral variant, in addition to other variables, on within-host viral burdens, by analysing cycle threshold (Ct) values derived from nose and throat swabs, collected as part of the UK COVID-19 Infection Survey. Because viral burden distributions determined from community survey data can be biased due to the impact of variant epidemiology on the time-since-infection of samples, we developed a method to explicitly adjust observed Ct value distributions to account for the expected bias. Analysing the adjusted Ct values using partial least squares regression, we found that among unvaccinated individuals with no known prior infection, the average Ct value was 0.94 lower among Alpha variant infections, compared those with the predecessor strain, B.1.177. However, among vaccinated individuals, it was 0.34 lower among Delta variant infections, compared to those with the Alpha variant. In addition, the average Ct value decreased by 0.20 for every 10 year age increment of the infected individual. In summary, within-host viral burdens are associated with age, in addition to the interplay of vaccination status and viral variant.

Enhancing global preparedness during an ongoing pandemic from partial and noisy data (preprint)

As the coronavirus disease 2019 (COVID-19) spread globally, emerging variants such as B.1.1.529 quickly became dominant worldwide. Sustained community transmission favors the proliferation of mutated sub-lineages with pandemic potential, due to cross-national mobility flows, which are responsible for consecutive cases surge worldwide. We show that, in the early stages of an emerging variant, integrating data from national genomic surveillance and global human mobility with large-scale epidemic modeling allows to quantify its pandemic potential, providing quantifiable indicators for pro-active policy interventions. We validate our framework on worldwide spreading variants and gain insights about the pandemic potential of BA.5 and BA.2.75 sub-lineages. Country-level epidemic intelligence is not enough to contrast the pandemic of respiratory pathogens such as SARS-CoV-2 and a scalable integrated approach, i.e. pandemic intelligence, is required to enhance global preparedness.

Statistical and agent-based modelling of the transmissibility of different SARS-CoV-2 variants in England and impact of different interventions (preprint)

The English SARS-CoV-2 epidemic has been affected by the emergence of new viral variants such as B.1.177, Alpha and Delta, and changing restrictions. We used statistical models and calibration of an stochastic agent-based model Covasim to estimate B.1.177 to be 20% more transmissible than the wild type, Alpha to be 50-80% more transmissible than B.1.177 and Delta to be 65-90% more transmissible than Alpha. We used these estimates in Covasim (calibrated between September 01, 2020 and June 20, 2021), in June 2021, to explore whether planned relaxation of restrictions should proceed or be delayed. We found that due to the high transmissibility of Delta, resurgence in infections driven by the Delta variant would not be prevented, but would be strongly reduced by delaying the relaxation of restrictions by one month and with continued vaccination.

A framework for reconstructing SARS-CoV-2 transmission dynamics using excess mortality data (preprint)

Detailed reconstruction of the SARS-CoV-2 transmission dynamics and assessment of its burden in several parts of the world has still remained largely unknown due to the scarcity of epidemiological analyses and limited testing capacities of different countries to identify cases and deaths attributable to COVID-19 [1-4]. Understanding the true burden of the Iranian COVID-19 epidemic is subject to similar challenges with limited clinical and epidemiological studies at the subnational level [5-9]. To address this, we develop a new quantitative framework that enables us to fully reconstruct the transmission dynamics across the country and assess the level of under-reporting in infections and deaths using province-level, age-stratified all-cause mortality data. We show that excess mortality aligns with seroprevalence estimates in each province and subsequently estimate that as of 2021-10-22, only 48% (95% confidence interval: 43-55%) of COVID-19 deaths in Iran have been reported. We find that in the most affected provinces such as East Azerbaijan, Qazvin, and Qom approximately 0.4% of the population have died of COVID-19 so far. We also find significant heterogeneity in the estimated attack rates across the country with 11 provinces reaching close to or higher than 100% attack rates. Despite a relatively young age structure in Iran, our analysis reveals that the infection fatality rate in most provinces is comparable to high-income countries with a larger percentage of older adults, suggesting that limited access to medical services, coupled with undercounting of COVID-19-related deaths, can have a significant impact on accurate estimation of COVID-19 fatalities. Our estimation of high attack rates in provinces with largely unmitigated epidemics whereby, on average, between 10% to 25% individuals have been infected with COVID-19 at least twice over the course of 20 months also suggests that, despite several waves of infection, herd immunity through natural infection has not been achieved in the population.

Modelling the effectiveness and social costs of daily lateral flow antigen tests versus quarantine in preventing onward transmission of COVID-19 from traced contacts (preprint)

Quarantining close contacts of individuals infected with SARS-CoV-2 for 10 to 14 days is a key strategy in reducing transmission. However, quarantine requirements are often unpopular, with low adherence, especially when a large fraction of the population has been vaccinated. Daily contact testing (DCT), in which contacts are required to isolate only if they test positive, is an alternative to quarantine for mitigating the risk of transmission from traced contacts. In this study, we developed an integrated model of COVID-19 transmission dynamics and compared the strategies of quarantine and DCT with regard to reduction in transmission and social/economic costs (days of quarantine/self-isolation). Specifically, we compared 10-day quarantine to 7 days of self-testing using rapid lateral flow antigen tests, starting 3 days after exposure to a case. We modelled both incomplete adherence to quarantine and incomplete adherence to DCT. We found that DCT reduces transmission from contacts with similar effectiveness, at much lower social/economic costs, especially for highly vaccinated populations. The findings were robust across a spectrum of scenarios with varying assumptions on the speed of contact tracing, sensitivity of lateral flow antigen tests, adherence to quarantine and uptake of testing. Daily tests would also allow rapid initiation of a new round of tracing from infected contacts.

Epidemiological and public health requirements for COVID-19 contact tracing apps and their evaluation (preprint)

Digital contact tracing is a public health intervention. It should be integrated with local health policy, provide rapid and accurate notifications to exposed individuals, and encourage high app uptake and adherence to quarantine. Real-time monitoring and evaluation of effectiveness of app-based contact tracing is key for improvement and public trust.

Early Analysis of a potential link between viral load and the N501Y mutation in the SARS-COV-2 spike protein (preprint)

A new variant of SARS-CoV-2 has emerged which is increasing in frequency, primarily in the South East of England (lineage B.1.1.7 (1); VUI-202012/01). One potential hypothesis is that infection with the new variant results in higher viral loads, which in turn may make the virus more transmissible. We found higher (sequence derived) viral loads in samples from individuals infected with the new variant with median inferred viral loads were three-fold higher in individuals with the new variant. Most of the new variants were sampled in Kent and Greater London. We observed higher viral loads in Kent compared to Greater London for both the new variant and other circulating lineages. Outside Greater London, the variant has higher viral loads, whereas within Greater London, the new variant does not have significantly higher viral loads compared to other circulating lineages. Higher variant viral loads outside Greater London could be due to demographic effects, such as a faster variant growth rate compared to other lineages or concentration in particular age-groups. However, our analysis does not exclude a causal link between infection with the new variant and higher viral loads. This is a preliminary analysis and further work is needed to investigate any potential causal link between infection with this new variant and higher viral loads, and whether this results in higher transmissibility, severity of infection, or affects relative rates of symptomatic and asymptomatic infection Document Description and PurposeThis is an updated report submitted to NERVTAG in December 2020 as part of urgent investigations into the new variant of SARS-COV-2 (VUI-202012/01). It makes full use of (and is restricted to) all sequence data and associated metadata available to us at the time this original report was submitted and remains provisional. Under normal circumstances more genomes and metadata would be obtained and included before making this report public. We will update this preprint when more genomes and metadata are available and before submitting for peer review.

The Timing of COVID-19 Transmission (preprint)

Background: The timing of SARS-CoV-2 transmission is a critical factor to understand the epidemic trajectory and the impact of isolation, contact tracing and other non-pharmaceutical interventions on the spread of COVID-19 epidemics. Methods: We examined the distribution of transmission event times with respect to exposure and onset of symptoms. We analysed 119 transmission pairs with known date of onset of symptoms for both index and secondary cases and partial information on their intervals of exposure. We inferred the distribution for generation time and time from onset of symptoms to transmission by maximum likelihood. We modelled different relations between time of infection, onset of symptoms and transmission, inferring the most appropriate one according to the Akaike Information Criterion. Finally, we estimated the fraction of pre-symptomatic and early symptomatic transmissions among all pairs using a Bayesian approach.Findings: For symptomatic individuals, the timing of transmission of SARS-CoV-2 was more directly linked to the onset of clinical symptoms of COVID-19 than to the time since infection. The time of transmission was approximately centered and symmetric around the onset of symptoms, with three quarters of events occurring in the window from 2-3 days before to 2-3 days after. The pre-symptomatic infectious period extended further back in time for individuals with longer incubation periods. Overall, the fraction of transmission from strictly pre-symptomatic infections was high (41%; 95%CI 31-50%), but a comparably large fraction of transmissions occurred on the same day as the onset of symptoms or the next day (35%; 95%CI 26-45%). We caution against overinterpretation of the fraction and timing of late symptomatic transmissions, due to their dependence on behavioural factors and interventions. Interpretation: Infectiousness is causally driven by the onset of symptoms. Public health authorities should reassess their policies on the contact tracing window in the light of individual variability in presymptomatic infectious period. Information about when a case was infected should be collected where possible, in order to assess how far into the past their contacts should be traced. The large fraction of transmission from strictly pre-symptomatic infections limits the efficacy of symptom-based interventions, while the large fraction of early symptomatic transmissions underlines the critical importance of individuals distancing themselves from others as soon as they notice any symptoms, even if mild. Rapid or at-home testing and contextual risk information could greatly facilitate efficient early isolation.Funding Statement: The study was funded by an award from the Li Ka Shing Foundation to CF.Declaration of Interests: None of the authors have competing financial or non-financial interests.

The timing of COVID-19 transmission (preprint)

The timing of SARS-CoV-2 transmission is a critical factor to understand the epidemic trajectory and the impact of isolation, contact tracing and other non- pharmaceutical interventions on the spread of COVID-19 epidemics. We examined the distribution of transmission events with respect to exposure and onset of symptoms. We show that for symptomatic individuals, the timing of transmission of SARS-CoV-2 is more strongly linked to the onset of clinical symptoms of COVID-19 than to the time since infection. We found that it was approximately centered and symmetric around the onset of symptoms, with three quarters of events occurring in the window from 2-3 days before to 2-3 days after. However, we caution against overinterpretation of the right tail of the distribution, due to its dependence on behavioural factors and interventions. We also found that the pre-symptomatic infectious period extended further back in time for individuals with longer incubation periods. This strongly suggests that information about when a case was infected should be collected where possible, in order to assess how far into the past their contacts should be traced. Overall, the fraction of transmission from strictly pre-symptomatic infections was high (41%; 95%CI 31-50%), which limits the efficacy of symptom-based interventions, and the large fraction of transmissions (35%; 95%CI 26-45%) that occur on the same day or the day after onset of symptoms underlines the critical importance of individuals distancing themselves from others as soon as they notice any symptoms, even if they are mild. Rapid or at-home testing and contextual risk information would greatly facilitate efficient early isolation.

COVID-19 incidence and R decreased on the Isle of Wight after the launch of the Test, Trace, Isolate programme (preprint)

In May 2020 the UK introduced a Test, Trace, Isolate programme in response to the COVID-19 pandemic. The programme was first rolled out on the Isle of Wight and included Version 1 of the NHS contact tracing app. We used COVID-19 daily case data to infer incidence of new infections and estimate the reproduction number R for each of 150 Upper Tier Local Authorities in England, and at the National level, before and after the launch of the programme on the Isle of Wight. We used Bayesian and Maximum-Likelihood methods to estimate R, and compared the Isle of Wight to other areas using a synthetic control method. We observed significant decreases in incidence and R on the Isle of Wight immediately after the launch. These results are robust across each of our approaches. Our results show that the sub-epidemic on the Isle of Wight was controlled significantly more effectively than the sub-epidemics of most other Upper Tier Local Authorities, changing from having the third highest reproduction number R (of 150) before the intervention to the tenth lowest afterwards. The data is not yet available to establish a causal link. However, the findings highlight the need for further research to determine the causes of this reduction, as these might translate into local and national non-pharmaceutical intervention strategies in the period before a treatment or vaccination becomes available.

Ongoing outbreak of COVID-19 in Iran: challenges and signs of concern with under-reporting of prevalence and deaths (preprint)

Many countries with an early outbreak of SARS-CoV-2 struggled to gauge the size and start date of the epidemic mainly due to limited testing capacities and a large proportion of undetected asymptomatic and mild infections. Iran was among the first countries with a major outbreak outside China. Using all genomic sequences collected from patients with a travel link to Iran, we estimate that the epidemic started on 21/01/2020 (95% HPD: 05/12/2019 – 14/02/2020) with a doubling time of 3 days (95% HPD: 1.68 – 16.27). We also show, using air travel data from confirmed exported cases, that from late February to early March the number of active cases across the country were more than a hundred times higher than the reported cases at the time. A detailed province-level analysis of all-cause mortality shows 20,718 (CI 95%: 18,859 – 22,576) excess deaths during winter and spring 2020 compared to previous years, almost twice the number of reported COVID-19-related deaths at the time. Correcting for under-reporting of prevalence and deaths, we use an SEIR model to reconstruct the outbreak dynamics in Iran. Our model forecasted the second epidemic peak and suggests that by 14/07/2020 a total of 9M (CI 95%: 118K – 44M) have recovered from the disease across the country. These findings have profound implications for assessing the stage of the epidemic in Iran and shed light on the dynamics of SARS-CoV-2 transmissions in Iran and central Asia despite significant levels of under-reporting. 

SARS-CoV-2 genomics beyond the consensus sequence: evidence for circulating mixed viral populations (preprint)

We gratefully acknowledge the UK COVID-19 Genomics Consortium (COG UK) for funding, and Public Health Wales / Cardiff University and MRC-University of Glasgow Centre for Virus Research for making their COG-UK sequence data publicly available. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute. The research was supported by the Wellcome Trust Core Award Grant Number 203141/Z/16/Z with funding from the NIHR Oxford BRC. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We are deeply grateful to Robert Esnouf and the BMRC Research Computing team for unfailing assistance with computational infrastructure. We also thank Benjamin Carpenter and James Docker for assistance in the laboratory, and Lorne Lonie, Maria Lopopolo, Chris Allen, John Broxholme and the WHG high-throughput genomics team for sequencing and quality control. The HIV clone p92BR025.8 was obtained through the Centre For AIDS Reagents from Drs Beatrice Hahn and Feng Gao, and the UNAIDS Virus Network (courtesy of the NIH AIDS Research and Reference Reagent Program). KAL is supported by The Wellcome Trust and The Royal Society (107652/Z/15/Z). MH, LF, MdC, GMC, NO, LAD, DB, CF and TG are supported by Li Ka Shing Foundation funding awarded to CF. PS is supported by a Wellcome Investigator Award (WT103767MA). SummarySARS-CoV-2, the causative agent of COVID-19, emerged in late 2019 causing a global pandemic, with the United Kingdom (UK) one of the hardest hit countries. Rapid sequencing and publication of consensus genomes have enabled phylogenetic analysis of the virus, demonstrating SARS-CoV-2 evolves relatively slowly1, but with multiple sites in the genome that appear inconsistent with the overall consensus phylogeny2. To understand these discrepancies, we used veSEQ3, a targeted RNA-seq approach, to quantify minor allele frequencies in 413 clinical samples from two UK locations. We show that SARS-CoV-2 infections are characterised by extensive within-host diversity, which is frequently shared among infected individuals with patterns consistent with geographical structure. These results were reproducible in data from two other sequencing locations in the UK, where we find evidence of mixed infection by major circulating lineages with patterns that cannot readily be explained by artefacts in the data. We conclude that SARS-CoV-2 diversity is transmissible, and propose that geographic patterns are generated by transient co-circulation of distinct viral populations. Co-transmission of mixed populations could open opportunities for resolving clusters of transmission and understanding pathogenesis.

Ongoing outbreak of COVID-19 in Iran: challenges and signs of concern (preprint)

Since the first outbreak in China, the Coronavirus Disease 2019 (COVID-19) has rapidly spread around the world. Iran was one of the first countries outside of China to report infections with COVID-19. With nearly 100 exported cases to various other countries, it has since been the epicentre of the outbreak in the Middle east. By examining the age-stratified COVID-19 case fatality rates across the country and 14 university hospitals in Tehran, we find that, in younger age groups, the reported cases on 13/03/2020 only capture less than 10% of symptomatic cases in the population. This indicates significant levels of under-reporting in Iran. Using the 18 full-genome sequences from cases with a travel history or link to Iran, as well as the one full genome sequence obtained from within the country, we estimate the time to the most recent common ancestor of sequences which suggests the likely start of the outbreak on 21/01/2020 (95% HPD: 05/12/2019 - 14/02/2020) with an approximate doubling time of 3.07 (95% HPD: 1.68 - 16.27). Also, based on known exported cases to Oman, Kuwait, Lebanon, and China, we estimate the outbreak size on 25 February and 6 March to be around 13,700 (95% CI: 7,600 - 33,300) and 60,500 (43,200 - 209,200), respectively. Knowing the size of the outbreak at two time points and the typical doubling times associated with the COVID-19 epidemics in countries across Europe and North America, we can independently verify that the likely start of epidemic in Iran is around 15/01/2020 (27/12/2019 - 24/01/2020). Our assessment of the fate of the epidemic based on current levels of non-pharmaceutical interventions implemented by the government suggests upward of 10 million cases (IQR: 6.7M - 18M) and 100,000 ICU beds required (IQR: 77K - 140K) during the peak of the epidemic with more than 100,000 cumulative deaths (IQR: 180K - 240K). We also predict a peak in demand for ICU beds on 21/04/2020 (IQR: 06/04/2020 - 23/05/2020). The large span of the peak of the ICU demand is a result of two separate peaks, with the first occurring at around 15/4/2020 and the second in approximately a months time. The latter is also expected to last longer and is based on the relatively relaxed social distancing measures in place. The exact magnitude and timing of the peaks strictly depends on levels of interventions and can change significantly upon new information or change of policy. We caution that a lack of, or relaxed, stringent intervention measures, during a period of highly under-reported spread, would likely lead to the healthcare system becoming overwhelmed in the next few months.

Quantifying dynamics of SARS-CoV-2 transmission suggests that epidemic control and avoidance is feasible through instantaneous digital contact tracing (preprint)

The newly emergent human virus SARS-CoV-2 is resulting in high fatality rates and incapacitated health systems. Preventing further transmission is a priority. We analysed key parameters of epidemic spread to estimate the contribution of different transmission routes and determine requirements for case isolation and contact-tracing needed to stop the epidemic. We conclude that viral spread is too fast to be contained by manual contact tracing, but could be controlled if this process was faster, more efficient and happened at scale. A contact-tracing App which builds a memory of proximity contacts and immediately notifies contacts of positive cases can achieve epidemic control if used by enough people. By targeting recommendations to only those at risk, epidemics could be contained without need for mass quarantines ('lock-downs') that are harmful to society. We discuss the ethical requirements for an intervention of this kind.