Viral emissions into the air and environment after SARS-CoV-2 human challenge: a phase 1, open label, first-in-human study.

BACKGROUND: Effectively implementing strategies to curb SARS-CoV-2 transmission requires understanding who is contagious and when. Although viral load on upper respiratory swabs has commonly been used to infer contagiousness, measuring viral emissions might be more accurate to indicate the chance of onward transmission and identify likely routes. We aimed to correlate viral emissions, viral load in the upper respiratory tract, and symptoms, longitudinally, in participants who were experimentally infected with SARS-CoV-2. METHODS: In this phase 1, open label, first-in-human SARS-CoV-2 experimental infection study at quarantine unit at the Royal Free London NHS Foundation Trust, London, UK, healthy adults aged 18-30 years who were unvaccinated for SARS-CoV-2, not previously known to have been infected with SARS-CoV-2, and seronegative at screening were recruited. Participants were inoculated with 10 50% tissue culture infectious dose of pre-alpha wild-type SARS-CoV-2 (Asp614Gly) by intranasal drops and remained in individual negative pressure rooms for a minimum of 14 days. Nose and throat swabs were collected daily. Emissions were collected daily from the air (using a Coriolis µ air sampler and directly into facemasks) and the surrounding environment (via surface and hand swabs). All samples were collected by researchers, and tested by using PCR, plaque assay, or lateral flow antigen test. Symptom scores were collected using self-reported symptom diaries three times daily. The study is registered with ClinicalTrials.gov, NCT04865237. FINDINGS: Between March 6 and July 8, 2021, 36 participants (ten female and 26 male) were recruited and 18 (53%) of 34 participants became infected, resulting in protracted high viral loads in the nose and throat following a short incubation period, with mild-to-moderate symptoms. Two participants were excluded from the per-protocol analysis owing to seroconversion between screening and inoculation, identified post hoc. Viral RNA was detected in 63 (25%) of 252 Coriolis air samples from 16 participants, 109 (43%) of 252 mask samples from 17 participants, 67 (27%) of 252 hand swabs from 16 participants, and 371 (29%) of 1260 surface swabs from 18 participants. Viable SARS-CoV-2 was collected from breath captured in 16 masks and from 13 surfaces, including four small frequently touched surfaces and nine larger surfaces where airborne virus could deposit. Viral emissions correlated more strongly with viral load in nasal swabs than throat swabs. Two individuals emitted 86% of airborne virus, and the majority of airborne virus collected was released on 3 days. Individuals who reported the highest total symptom scores were not those who emitted most virus. Very few emissions occurred before the first reported symptom (7%) and hardly any before the first positive lateral flow antigen test (2%). INTERPRETATION: After controlled experimental inoculation, the timing, extent, and routes of viral emissions was heterogeneous. We observed that a minority of participants were high airborne virus emitters, giving support to the notion of superspreading individuals or events. Our data implicates the nose as the most important source of emissions. Frequent self-testing coupled with isolation upon awareness of first symptoms could reduce onward transmissions. FUNDING: UK Vaccine Taskforce of the Department for Business, Energy and Industrial Strategy of Her Majesty's Government.

Estimating the number of undetected COVID-19 cases among travellers from mainland China [version 1, peer review: awaiting peer review]

Background: Since the start of the COVID-19 epidemic in late 2019, there have been more than 152 affected regions and countries with over 110,000 confirmed cases outside mainland China. Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries. Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that more than two thirds (70%, 95% CI: 54% - 80%, compared to Singapore;75%, 95% CI: 66% - 82%, compared to multiple countries) of cases exported from mainland China have remained undetected. Conclusions: These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.

Impact of proactive and reactive vaccination strategies for health-care workers against MERS-CoV: a mathematical modelling study.

BACKGROUND: Several vaccine candidates are in development against MERS-CoV, which remains a major public health concern. In anticipation of available MERS-CoV vaccines, we examine strategies for their optimal deployment among health-care workers. METHODS: Using data from the 2013-14 Saudi Arabia epidemic, we use a counterfactual analysis on inferred transmission trees (who-infected-whom analysis) to assess the potential impact of vaccination campaigns targeting health-care workers, as quantified by the proportion of cases or deaths averted. We investigate the conditions under which proactive campaigns (ie vaccinating in anticipation of the next outbreak) would outperform reactive campaigns (ie vaccinating in response to an unfolding outbreak), considering vaccine efficacy, duration of vaccine protection, effectiveness of animal reservoir control measures, wait (time between vaccination and next outbreak, for proactive campaigns), reaction time (for reactive campaigns), and spatial level (hospital, regional, or national, for reactive campaigns). We also examine the relative efficiency (cases averted per thousand doses) of different strategies. FINDINGS: The spatial scale of reactive campaigns is crucial. Proactive campaigns outperform campaigns that vaccinate health-care workers in response to outbreaks at their hospital, unless vaccine efficacy has waned significantly. However, reactive campaigns at the regional or national levels consistently outperform proactive campaigns, regardless of vaccine efficacy. When considering the number of cases averted per vaccine dose administered, the rank order is reversed: hospital-level reactive campaigns are most efficient, followed by regional-level reactive campaigns, with national-level and proactive campaigns being least efficient. If the number of cases required to trigger reactive vaccination increases, the performance of hospital-level campaigns is greatly reduced; the impact of regional-level campaigns is variable, but that of national-level campaigns is preserved unless triggers have high thresholds. INTERPRETATION: Substantial reduction of MERS-CoV morbidity and mortality is possible when vaccinating only health-care workers, underlining the need for countries at risk of outbreaks to stockpile vaccines when available. FUNDING: UK Medical Research Council, UK National Institute for Health Research, UK Research and Innovation, UK Academy of Medical Sciences, The Novo Nordisk Foundation, The Schmidt Foundation, and Investissement d'Avenir France.

Risk factors and vectors for SARS-CoV-2 household transmission: a prospective, longitudinal cohort study.

BACKGROUND: Despite circumstantial evidence for aerosol and fomite spread of SARS-CoV-2, empirical data linking either pathway with transmission are scarce. Here we aimed to assess whether the presence of SARS-CoV-2 on frequently-touched surfaces and residents' hands was a predictor of SARS-CoV-2 household transmission. METHODS: In this longitudinal cohort study, during the pre-alpha (September to December, 2020) and alpha (B.1.1.7; December, 2020, to April, 2021) SARS-CoV-2 variant waves, we prospectively recruited contacts from households exposed to newly diagnosed COVID-19 primary cases, in London, UK. To maximally capture transmission events, contacts were recruited regardless of symptom status and serially tested for SARS-CoV-2 infection by RT-PCR on upper respiratory tract (URT) samples and, in a subcohort, by serial serology. Contacts' hands, primary cases' hands, and frequently-touched surface-samples from communal areas were tested for SARS-CoV-2 RNA. SARS-CoV-2 URT isolates from 25 primary case-contact pairs underwent whole-genome sequencing (WGS). FINDINGS: From Aug 1, 2020, until March 31, 2021, 620 contacts of PCR-confirmed SARS-CoV-2-infected primary cases were recruited. 414 household contacts (from 279 households) with available serial URT PCR results were analysed in the full household contacts' cohort, and of those, 134 contacts with available longitudinal serology data and not vaccinated pre-enrolment were analysed in the serology subcohort. Household infection rate was 28·4% (95% CI 20·8-37·5) for pre-alpha-exposed contacts and 51·8% (42·5-61·0) for alpha-exposed contacts (p=0·0047). Primary cases' URT RNA viral load did not correlate with transmission, but was associated with detection of SARS-CoV-2 RNA on their hands (p=0·031). SARS-CoV-2 detected on primary cases' hands, in turn, predicted contacts' risk of infection (adjusted relative risk [aRR]=1·70 [95% CI 1·24-2·31]), as did SARS-CoV-2 RNA presence on household surfaces (aRR=1·66 [1·09-2·55]) and contacts' hands (aRR=2·06 [1·57-2·69]). In six contacts with an initial negative URT PCR result, hand-swab (n=3) and household surface-swab (n=3) PCR positivity preceded URT PCR positivity. WGS corroborated household transmission. INTERPRETATION: Presence of SARS-CoV-2 RNA on primary cases' and contacts' hands and on frequently-touched household surfaces associates with transmission, identifying these as potential vectors for spread in households. FUNDING: National Institute for Health Research Health Protection Research Unit in Respiratory Infections, Medical Research Council.

Data pipelines in a public health emergency: The human in the machine.

In an emergency epidemic response, data providers supply data on a best-faith effort to modellers and analysts who are typically the end user of data collected for other primary purposes such as to inform patient care. Thus, modellers who analyse secondary data have limited ability to influence what is captured. During an emergency response, models themselves are often under constant development and require both stability in their data inputs and flexibility to incorporate new inputs as novel data sources become available. This dynamic landscape is challenging to work with. Here we outline a data pipeline used in the ongoing COVID-19 response in the UK that aims to address these issues. A data pipeline is a sequence of steps to carry the raw data through to a processed and useable model input, along with the appropriate metadata and context. In ours, each data type had an individual processing report, designed to produce outputs that could be easily combined and used downstream. Automated checks were in-built and added as new pathologies emerged. These cleaned outputs were collated at different geographic levels to provide standardised datasets. Finally, a human validation step was an essential component of the analysis pathway and permitted more nuanced issues to be captured. This framework allowed the pipeline to grow in complexity and volume and facilitated the diverse range of modelling approaches employed by researchers. Additionally, every report or modelling output could be traced back to the specific data version that informed it ensuring reproducibility of results. Our approach has been used to facilitate fast-paced analysis and has evolved over time. Our framework and its aspirations are applicable to many settings beyond COVID-19 data, for example for other outbreaks such as Ebola, or where routine and regular analyses are required.

Effectiveness assessment of non-pharmaceutical interventions: lessons learned from the COVID-19 pandemic.

Effectiveness of non-pharmaceutical interventions (NPIs), such as school closures and stay-at-home orders, during the COVID-19 pandemic has been assessed in many studies. Such assessments can inform public health policies and contribute to evidence-based choices of NPIs during subsequent waves or future epidemics. However, methodological issues and no standardised assessment practices have restricted the practical value of the existing evidence. Here, we present and discuss lessons learned from the COVID-19 pandemic and make recommendations for standardising and improving assessment, data collection, and modelling. These recommendations could contribute to reliable and policy-relevant assessments of the effectiveness of NPIs during future epidemics.

The societal value of SARS-CoV-2 booster vaccination in Indonesia.

OBJECTIVES: To estimate the expected socio-economic value of booster vaccination in terms of averted deaths and averted closures of businesses and schools using simulation modelling. METHODS: The value of booster vaccination in Indonesia is estimated by comparing simulated societal costs under a twelve-month, 187-million-dose Moderna booster vaccination campaign to costs without boosters. The costs of an epidemic and its mitigation consist of lost lives, economic closures and lost education; cost-minimising non-pharmaceutical mitigation is chosen for each scenario. RESULTS: The cost-minimising non-pharmaceutical mitigation depends on the availability of vaccines: the differences between the two scenarios are 14 to 19 million years of in-person education and $153 to $204 billion in economic activity. The value of the booster campaign ranges from $2,500 ($1,400-$4,100) to $2,800 ($1,700-$4,600) per dose in the first year, depending on life-year valuations. CONCLUSIONS: The societal benefits of booster vaccination are substantial. Much of the value of vaccination resides in the reduced need for costly non-pharmaceutical mitigation. We propose cost minimisation as a tool for policy decision-making and valuation of vaccination, taking into account all socio-economic costs, and not averted deaths alone.

Quantifying the effect of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study.

BACKGROUND: The UK was the first country to start national COVID-19 vaccination programmes, initially administering doses 3 weeks apart. However, early evidence of high vaccine effectiveness after the first dose and the emergence of the SARS-CoV-2 alpha variant prompted the UK to extend the interval between doses to 12 weeks. In this study, we aimed to quantify the effect of delaying the second vaccine dose in England. METHODS: We used a previously described model of SARS-CoV-2 transmission, calibrated to COVID-19 surveillance data from England, including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data, using a Bayesian evidence-synthesis framework. We modelled and compared the epidemic trajectory in the counterfactual scenario in which vaccine doses were administered 3 weeks apart against the real reported vaccine roll-out schedule of 12 weeks. We estimated and compared the resulting numbers of daily infections, hospital admissions, and deaths. In sensitivity analyses, we investigated scenarios spanning a range of vaccine effectiveness and waning assumptions. FINDINGS: In the period from Dec 8, 2020, to Sept 13, 2021, the number of individuals who received a first vaccine dose was higher under the 12-week strategy than the 3-week strategy. For this period, we estimated that delaying the interval between the first and second COVID-19 vaccine doses from 3 to 12 weeks averted a median (calculated as the median of the posterior sample) of 58 000 COVID-19 hospital admissions (291 000 cumulative hospitalisations [95% credible interval 275 000-319 000] under the 3-week strategy vs 233 000 [229 000-238 000] under the 12-week strategy) and 10 100 deaths (64 800 deaths [60 200-68 900] vs 54 700 [52 800-55 600]). Similarly, we estimated that the 3-week strategy would have resulted in more infections compared with the 12-week strategy. Across all sensitivity analyses the 3-week strategy resulted in a greater number of hospital admissions. In results by age group, the 12-week strategy led to more hospitalisations and deaths in older people in spring 2021, but fewer following the emergence of the delta variant during summer 2021. INTERPRETATION: England's delayed-second-dose vaccination strategy was informed by early real-world data on vaccine effectiveness in the context of limited vaccine supplies in a growing epidemic. Our study shows that rapidly providing partial (single-dose) vaccine-induced protection to a larger proportion of the population was successful in reducing the burden of COVID-19 hospitalisations and deaths overall. FUNDING: UK National Institute for Health Research; UK Medical Research Council; Community Jameel; Wellcome Trust; UK Foreign, Commonwealth and Development Office; Australian National Health and Medical Research Council; and EU.

A COVID‐19 model for local authorities of the United Kingdom

We propose a new framework to model the COVID-19 epidemic of the United Kingdom at the local authority level. The model fits within a general framework for semi-mechanistic Bayesian models of the epidemic based on renewal equations, with some important innovations, including a random walk modelling the reproduction number, incorporating information from different sources, including surveys to estimate the time-varying proportion of infections that lead to reported cases or deaths, and modelling the underlying infections as latent random variables. The model is designed to be updated daily using publicly available data. We envisage the model to be useful for now-casting and short-term projections of the epidemic as well as estimating historical trends. The model fits are available on a public website: . The model is currently being used by the Scottish government to inform their interventions.

Vaccine equity in low and middle income countries: a systematic review and meta-analysis.

BACKGROUND: Evidence to date has shown that inequality in health, and vaccination coverage in particular, can have ramifications to wider society. However, whilst individual studies have sought to characterise these heterogeneities in immunisation coverage at national level, few have taken a broad and quantitative view of the contributing factors to heterogeneity in immunisation coverage and impact, i.e. the number of cases, deaths, and disability-adjusted life years averted. This systematic review aims to highlight these geographic, demographic, and sociodemographic characteristics through a qualitative and quantitative approach, vital to prioritise and optimise vaccination policies. METHODS: A systematic review of two databases (PubMed and Web of Science) was undertaken using search terms and keywords to identify studies examining factors on immunisation inequality and heterogeneity in vaccination coverage. Inclusion criteria were applied independently by two researchers. Studies including data on key characteristics of interest were further analysed through a meta-analysis to produce a pooled estimate of the risk ratio using a random effects model for that characteristic. RESULTS: One hundred and eight studies were included in this review. We found that inequalities in wealth, education, and geographic access can affect vaccine impact and vaccination dropout. We estimated those living in rural areas were not significantly different in terms of full vaccination status compared to urban areas but noted considerable heterogeneity between countries. We found that females were 3% (95%CI[1%, 5%]) less likely to be fully vaccinated than males. Additionally, we estimated that children whose mothers had no formal education were 28% (95%CI[18%,47%]) less likely to be fully vaccinated than those whose mother had primary level, or above, education. Finally, we found that individuals in the poorest wealth quintile were 27% (95%CI [16%,37%]) less likely to be fully vaccinated than those in the richest. CONCLUSIONS: We found a nuanced picture of inequality in vaccination coverage and access with wealth disparity dominating, and likely driving, other disparities. This review highlights the complex landscape of inequity and further need to design vaccination strategies targeting missed subgroups to improve and recover vaccination coverage following the COVID-19 pandemic. TRIAL REGISTRATION: Prospero, CRD42021261927.

Onset and window of SARS-CoV-2 infectiousness and temporal correlation with symptom onset: a prospective, longitudinal, community cohort study.

BACKGROUND: Knowledge of the window of SARS-CoV-2 infectiousness is crucial in developing policies to curb transmission. Mathematical modelling based on scarce empirical evidence and key assumptions has driven isolation and testing policy, but real-world data are needed. We aimed to characterise infectiousness across the full course of infection in a real-world community setting. METHODS: The Assessment of Transmission and Contagiousness of COVID-19 in Contacts (ATACCC) study was a UK prospective, longitudinal, community cohort of contacts of newly diagnosed, PCR-confirmed SARS-CoV-2 index cases. Household and non-household exposed contacts aged 5 years or older were eligible for recruitment if they could provide informed consent and agree to self-swabbing of the upper respiratory tract. The primary objective was to define the window of SARS-CoV-2 infectiousness and its temporal correlation with symptom onset. We quantified viral RNA load by RT-PCR and infectious viral shedding by enumerating cultivable virus daily across the course of infection. Participants completed a daily diary to track the emergence of symptoms. Outcomes were assessed with empirical data and a phenomenological Bayesian hierarchical model. FINDINGS: Between Sept 13, 2020, and March 31, 2021, we enrolled 393 contacts from 327 households (the SARS-CoV-2 pre-alpha and alpha variant waves); and between May 24, 2021, and Oct 28, 2021, we enrolled 345 contacts from 215 households (the delta variant wave). 173 of these 738 contacts were PCR positive for more than one timepoint, 57 of which were at the start of infection and comprised the final study population. The onset and end of infectious viral shedding were captured in 42 cases and the median duration of infectiousness was 5 (IQR 3-7) days. Although 24 (63%) of 38 cases had PCR-detectable virus before symptom onset, only seven (20%) of 35 shed infectious virus presymptomatically. Symptom onset was a median of 3 days before both peak viral RNA and peak infectious viral load (viral RNA IQR 3-5 days, n=38; plaque-forming units IQR 3-6 days, n=35). Notably, 22 (65%) of 34 cases and eight (24%) of 34 cases continued to shed infectious virus 5 days and 7 days post-symptom onset, respectively (survival probabilities 67% and 35%). Correlation of lateral flow device (LFD) results with infectious viral shedding was poor during the viral growth phase (sensitivity 67% [95% CI 59-75]), but high during the decline phase (92% [86-96]). Infectious virus kinetic modelling suggested that the initial rate of viral replication determines the course of infection and infectiousness. INTERPRETATION: Less than a quarter of COVID-19 cases shed infectious virus before symptom onset; under a crude 5-day self-isolation period from symptom onset, two-thirds of cases released into the community would still be infectious, but with reduced infectious viral shedding. Our findings support a role for LFDs to safely accelerate deisolation but not for early diagnosis, unless used daily. These high-resolution, community-based data provide evidence to inform infection control guidance. FUNDING: National Institute for Health and Care Research.

Using next generation matrices to estimate the proportion of infections that are not detected in an outbreak.

Contact tracing, where exposed individuals are followed up to break ongoing transmission chains, is a key pillar of outbreak response for infectious disease outbreaks. Unfortunately, these systems are not fully effective, and infections can still go undetected as people may not remember all their contacts or contacts may not be traced successfully. A large proportion of undetected infections suggests poor contact tracing and surveillance systems, which could be a potential area of improvement for a disease response. In this paper, we present a method for estimating the proportion of infections that are not detected during an outbreak. Our method uses next generation matrices that are parameterized by linked contact tracing data and case line-lists. We validate the method using simulated data from an individual-based model and then investigate two case studies: the proportion of undetected infections in the SARS-CoV-2 outbreak in New Zealand during 2020 and the Ebola epidemic in Guinea during 2014. We estimate that only 5.26% of SARS-CoV-2 infections were not detected in New Zealand during 2020 (95% credible interval: 0.243 - 16.0%) if 80% of contacts were under active surveillance but depending on assumptions about the ratio of contacts not under active surveillance versus contacts under active surveillance 39.0% or 37.7% of Ebola infections were not detected in Guinea (95% credible intervals: 1.69 - 87.0% or 1.70 - 80.9%).

Measuring Vaccine Efficacy Against Infection and Disease in Clinical Trials: Sources and Magnitude of Bias in Coronavirus Disease 2019 (COVID-19) Vaccine Efficacy Estimates.

BACKGROUND: Phase III trials have estimated coronavirus disease 2019 (COVID-19) vaccine efficacy (VE) against symptomatic and asymptomatic infection. We explore the direction and magnitude of potential biases in these estimates and their implications for vaccine protection against infection and against disease in breakthrough infections. METHODS: We developed a mathematical model that accounts for natural and vaccine-induced immunity, changes in serostatus, and imperfect sensitivity and specificity of tests for infection and antibodies. We estimated expected biases in VE against symptomatic, asymptomatic, and any severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and against disease following infection for a range of vaccine characteristics and measurement approaches, and the likely overall biases for published trial results that included asymptomatic infections. RESULTS: VE against asymptomatic infection measured by polymerase chain reaction (PCR) or serology is expected to be low or negative for vaccines that prevent disease but not infection. VE against any infection is overestimated when asymptomatic infections are less likely to be detected than symptomatic infections and the vaccine protects against symptom development. A competing bias toward underestimation arises for estimates based on tests with imperfect specificity, especially when testing is performed frequently. Our model indicates considerable uncertainty in Oxford-AstraZeneca ChAdOx1 and Janssen Ad26.COV2.S VE against any infection, with slightly higher than published, bias-adjusted values of 59.0% (95% uncertainty interval [UI] 38.4-77.1) and 70.9% (95% UI 49.8-80.7), respectively. CONCLUSIONS: Multiple biases are likely to influence COVID-19 VE estimates, potentially explaining the observed difference between ChAdOx1 and Ad26.COV2.S vaccines. These biases should be considered when interpreting both efficacy and effectiveness study results.

The Life with Corona survey.

The COVID-19 pandemic is a global crisis affecting everyone. Yet, its challenges and countermeasures vary significantly over time and space. Individual experiences of the pandemic are highly heterogeneous and its impacts span and interlink multiple dimensions, such as health, economic, social and political impacts. Therefore, there is a need to disaggregate "the pandemic": analysing experiences, behaviours and impacts at the micro level and from multiple disciplinary perspectives. Such analyses require multi-topic pan-national survey data that are collected continuously and can be matched with other datasets, such as disease statistics or information on countermeasures. To this end, we introduce a new dataset that matches these desirable properties - the Life with Corona (LwC) survey - and perform illustrative analyses to show the importance of such micro data to understand how the pandemic and its countermeasures shape lives and societies over time.

Estimating the COVID-19 infection fatality ratio accounting for seroreversion using statistical modelling.

Background: The infection fatality ratio (IFR) is a key statistic for estimating the burden of coronavirus disease 2019 (COVID-19) and has been continuously debated throughout the COVID-19 pandemic. The age-specific IFR can be quantified using antibody surveys to estimate total infections, but requires consideration of delay-distributions from time from infection to seroconversion, time to death, and time to seroreversion (i.e. antibody waning) alongside serologic test sensitivity and specificity. Previous IFR estimates have not fully propagated uncertainty or accounted for these potential biases, particularly seroreversion. Methods: We built a Bayesian statistical model that incorporates these factors and applied this model to simulated data and 10 serologic studies from different countries. Results: We demonstrate that seroreversion becomes a crucial factor as time accrues but is less important during first-wave, short-term dynamics. We additionally show that disaggregating surveys by regions with higher versus lower disease burden can inform serologic test specificity estimates. The overall IFR in each setting was estimated at 0.49-2.53%. Conclusion: We developed a robust statistical framework to account for full uncertainties in the parameters determining IFR. We provide code for others to apply these methods to further datasets and future epidemics.

COVID-19 impact on routine immunisations for vaccine-preventable diseases: Projecting the effect of different routes to recovery.

Over the past two decades, vaccination programmes for vaccine-preventable diseases (VPDs) have expanded across low- and middle-income countries (LMICs). However, the rise of COVID-19 resulted in global disruption to routine immunisation activities. Such disruptions could have a detrimental effect on public health, leading to more deaths from VPDs, particularly without mitigation efforts. Hence, as routine immunisation activities resume, it is important to estimate the effectiveness of different approaches for recovery. We apply an impact extrapolation method developed by the Vaccine Impact Modelling Consortium to estimate the impact of COVID-19-related disruptions with different recovery scenarios for ten VPDs across 112 LMICs. We focus on deaths averted due to routine immunisations occurring in the years 2020-2030 and investigate two recovery scenarios relative to a no-COVID-19 scenario. In the recovery scenarios, we assume a 10% COVID-19-related drop in routine immunisation coverage in the year 2020. We then linearly interpolate coverage to the year 2030 to investigate two routes to recovery, whereby the immunization agenda (IA2030) targets are reached by 2030 or fall short by 10%. We estimate that falling short of the IA2030 targets by 10% leads to 11.26% fewer fully vaccinated persons (FVPs) and 11.34% more deaths over the years 2020-2030 relative to the no-COVID-19 scenario, whereas, reaching the IA2030 targets reduces these proportions to 5% fewer FVPs and 5.22% more deaths. The impact of the disruption varies across the VPDs with diseases where coverage expands drastically in future years facing a smaller detrimental effect. Overall, our results show that drops in routine immunisation coverage could result in more deaths due to VPDs. As the impact of COVID-19-related disruptions is dependent on the vaccination coverage that is achieved over the coming years, the continued efforts of building up coverage and addressing gaps in immunity are vital in the road to recovery.

COVID-19 in Japan, January-March 2020: insights from the first three months of the epidemic.

BACKGROUND: Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data. METHODS: We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, Rt, correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs. RESULTS: The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ± 2 days). Early transmission was driven primarily by returning travellers with Rt peaking at 2.4 (95% CrI: 1.6, 3.3) nationally. In the final week of the trusted period (16-23 March 2020), Rt accounting for importations diverged from overall Rt at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6), respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age with individuals more likely to infect, and be infected by, contacts in a similar age group to them. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients < 20 years old developing pneumonia or severe respiratory symptoms. CONCLUSIONS: Information collected in the early phases of an outbreak are important in characterising any novel pathogen. The availability of timely and detailed data and appropriate analyses is critical to estimate and understand a pathogen's transmissibility, high-risk settings for transmission, and key symptoms. These insights can help to inform urgent response strategies.

Assessment of mortality and hospital admissions associated with confirmed infection with SARS-CoV-2 Alpha variant: a matched cohort and time-to-event analysis, England, October to December 2020.

BackgroundThe emergence of the SARS-CoV-2 Alpha variant in England coincided with a rapid increase in the number of PCR-confirmed COVID-19 cases in areas where the variant was concentrated.AimOur aim was to assess whether infection with Alpha was associated with more severe clinical outcomes than the wild type.MethodsLaboratory-confirmed infections with genomically sequenced SARS-CoV-2 Alpha and wild type between October and December 2020 were linked to routine healthcare and surveillance datasets. We conducted two statistical analyses to compare the risk of hospital admission and death within 28 days of testing between Alpha and wild-type infections: a matched cohort study and an adjusted Cox proportional hazards model. We assessed differences in disease severity by comparing hospital admission and mortality, including length of hospitalisation and time to death.ResultsOf 63,609 COVID-19 cases sequenced in England between October and December 2020, 6,038 had the Alpha variant. In the matched cohort analysis, we matched 2,821 cases with Alpha to 2,821 to cases with wild type. In the time-to-event analysis, we observed a 34% increased risk in hospitalisation associated with Alpha compared with wild type, but no significant difference in the risk of mortality.ConclusionWe found evidence of increased risk of hospitalisation after adjusting for key confounders, suggesting increased infection severity associated with the Alpha variant. Rapid assessments of the relative morbidity in terms of clinical outcomes and mortality associated with emerging SARS-CoV-2 variants compared with dominant variants are required to assess overall impact of SARS-CoV-2 mutations.

Safety, tolerability and viral kinetics during SARS-CoV-2 human challenge in young adults.

Since its emergence in 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused hundreds of millions of cases and continues to circulate globally. To establish a novel SARS-CoV-2 human challenge model that enables controlled investigation of pathogenesis, correlates of protection and efficacy testing of forthcoming interventions, 36 volunteers aged 18-29 years without evidence of previous infection or vaccination were inoculated with 10 TCID50 of a wild-type virus (SARS-CoV-2/human/GBR/484861/2020) intranasally in an open-label, non-randomized study (ClinicalTrials.gov identifier NCT04865237 ; funder, UK Vaccine Taskforce). After inoculation, participants were housed in a high-containment quarantine unit, with 24-hour close medical monitoring and full access to higher-level clinical care. The study's primary objective was to identify an inoculum dose that induced well-tolerated infection in more than 50% of participants, with secondary objectives to assess virus and symptom kinetics during infection. All pre-specified primary and secondary objectives were met. Two participants were excluded from the per-protocol analysis owing to seroconversion between screening and inoculation, identified post hoc. Eighteen (~53%) participants became infected, with viral load (VL) rising steeply and peaking at ~5 days after inoculation. Virus was first detected in the throat but rose to significantly higher levels in the nose, peaking at ~8.87 log10 copies per milliliter (median, 95% confidence interval (8.41, 9.53)). Viable virus was recoverable from the nose up to ~10 days after inoculation, on average. There were no serious adverse events. Mild-to-moderate symptoms were reported by 16 (89%) infected participants, beginning 2-4 days after inoculation, whereas two (11%) participants remained asymptomatic (no reportable symptoms). Anosmia or dysosmia developed more slowly in 15 (83%) participants. No quantitative correlation was noted between VL and symptoms, with high VLs present even in asymptomatic infection. All infected individuals developed serum spike-specific IgG and neutralizing antibodies. Results from lateral flow tests were strongly associated with viable virus, and modeling showed that twice-weekly rapid antigen tests could diagnose infection before 70-80% of viable virus had been generated. Thus, with detailed characterization and safety analysis of this first SARS-CoV-2 human challenge study in young adults, viral kinetics over the course of primary infection with SARS-CoV-2 were established, with implications for public health recommendations and strategies to affect SARS-CoV-2 transmission. Future studies will identify the immune factors associated with protection in those participants who did not develop infection or symptoms and define the effect of prior immunity and viral variation on clinical outcome.