The changing impact of vaccines in the COVID-19 pandemic

The Omicron wave has left a global imprinting of immunity which changes the COVID landscape. In this study, we simulate six hypothetical variants emerging over the next year and evaluate the impact of existing and improved vaccines. We base our study on South Africas infection- and vaccination-derived immunity. Our findings illustrate that variant-chasing vaccines will only add value above existing vaccines in the setting where a variant emerges if we can shorten the window between variant introduction and vaccine deployment to under three weeks, an impossible time-frame without significant NPI use. This strategy may have global utility, depending on the rate of spread from setting to setting. Broadly neutralizing and durable next-generation vaccines could avert over three-times as many deaths from an immune-evading variant compared to existing vaccines. Our results suggest it is crucial to develop next-generation vaccines and redress inequities in vaccine distribution to tackle future emerging variants.

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

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.

Transmission of SARS-CoV-2 by children and young people in households and schools: a meta-analysis of population-based and contact-tracing studies

BackgroundThe role of children and young people (CYP) in transmission of SARS-CoV-2 in household and educational settings remains unclear. We undertook a systematic review and meta-analysis of contact-tracing and population-based studies at low risk of bias. MethodsWe searched 4 electronic databases on 28 July 2021 for contact-tracing studies and population-based studies informative about transmission of SARS-CoV-2 from 0-19 year olds in household or educational settings. We excluded studies at high risk of bias, including from under-ascertainment of asymptomatic infections. We undertook multilevel random effects meta-analyses of secondary attack rates (SAR: contact-tracing studies) and school infection prevalence, and used meta-regression to examine the impact of community SARS-CoV-2 incidence on school infection prevalence. Findings4529 abstracts were reviewed, resulting in 37 included studies (16 contact-tracing; 19 population studies; 2 mixed studies). The pooled relative transmissibility of CYP compared with adults was 0.92 (0.68, 1.26) in adjusted household studies. The pooled SAR from CYP was lower (p=0.002) in school studies 0.7% (0.2, 2.7) than household studies (7.6% (3.6, 15.9). There was no difference in SAR from CYP to child or adult contacts. School population studies showed some evidence of clustering in classes within schools. School infection prevalence was associated with contemporary community 14-day incidence (OR 1.003 (1.001, 1.004), p<0.001). InterpretationWe found no difference in transmission of SARS-CoV-2 from CYP compared with adults within household settings. SAR were markedly lower in school compared with household settings, suggesting that household transmission is more important than school transmission in this pandemic. School infection prevalence was associated with community infection incidence, supporting hypotheses that school infections broadly reflect community infections. These findings are important for guiding policy decisions on shielding, vaccination school and operations during the pandemic. FundingNo funding obtained.

Genomic reconstruction of the SARS-CoV-2 epidemic across England from September 2020 to May 2021

The evolution of the SARS-CoV-2 pandemic continuously produces new variants, which warrant timely epidemiological characterisation. Here we use the dense genomic surveillance generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of sub-epidemics that peaked in the early autumn of 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. Alpha grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed Alpha and eliminated nearly all other lineages in early 2021. However, a series of variants (mostly containing the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. Accounting for sustained introductions, however, indicates that their transmissibility is unlikely to have exceeded that of Alpha. Finally, B.1.617.2/Delta was repeatedly introduced to England and grew rapidly in the early summer of 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on June 26.

Modelling the impact of reopening schools in early 2021 in the presence of the new SARS-CoV-2 variant and with roll-out of vaccination against COVID-19

BackgroundFollowing the resurgence of the COVID-19 epidemic in the UK in late 2020 and the emergence of the alpha (also known as B117) variant of the SARS-CoV-2 virus, a third national lockdown was imposed from January 4, 2021. Following the decline of COVID-19 cases over the remainder of January 2021, the question of when and how to reopen schools became an increasingly pressing one in early 2021. This study models the impact of a partial national lockdown with social distancing measures enacted in communities and workplaces under different strategies of reopening schools from March 8, 2021 and compares it to the impact of continual full national lockdown remaining until April 19, 2021. MethodsWe used our previously published agent-based model, Covasim, to model the emergence of the alpha variant over September 1, 2020 to January 31, 2021 in presence of Test, Trace and Isolate (TTI) strategies. We extended the model to incorporate the impacts of the roll-out of a two-dose vaccine against COVID-19, with 200,000 daily vaccine doses prioritised by age starting with people 75 years or older, assuming vaccination offers a 95% reduction in disease acquisition risk and a 30% reduction in transmission risk. We used the model, calibrated until January 25, 2021, to simulate the impact of a full national lockdown (FNL) with schools closed until April 19, 2021 versus four different partial national lockdown (PNL) scenarios with different elements of schooling open: 1) staggered PNL with primary schools and exam-entry years (years 11 and 13) returning on March 8, 2021 and the rest of the schools years on March 15, 2020; 2) full-return PNL with both primary and secondary schools returning on March 8, 2021; 3) primary-only PNL with primary schools and exam critical years (years 11 and 13) going back only on March 8, 2021 with the rest of the secondary schools back on April 19, 2021 and 4) part-rota PNL with both primary and secondary schools returning on March 8, 2021 with primary schools remaining open continuously but secondary schools on a two-weekly rota-system with years alternating between a fortnight of face-to-face and remote learning until April 19, 2021. Across all scenarios, we projected the number of new daily cases, cumulative deaths and effective reproduction number R until April 30, 2021. ResultsOur calibration across different scenarios is consistent with alpha variant being around 60% more transmissible than the wild type. We find that strict social distancing measures, i.e. national lockdowns, were essential in containing the spread of the virus and controlling hospitalisations and deaths during January and February 2021. We estimated that a national lockdown over January and February 2021 would reduce the number of cases by early March to levels similar to those seen in October 2020, with R also falling and remaining below 1 over this period. We estimated that infections would start to increase when schools reopened, but found that if other parts of society remain closed, this resurgence would not be sufficient to bring R above 1. Reopening primary schools and exam critical years only or having primary schools open continuously with secondary schools on rotas was estimated to lead to lower increases in cases and R than if all schools opened. Without an increase in vaccination above the levels seen in January and February, we estimate that R could have increased above 1 following the reopening of society, simulated here from April 19, 2021. FindingsOur findings suggest that stringent measures were integral in mitigating the increase in cases and bringing R below 1 over January and February 2021. We found that it was plausible that a PNL with schools partially open from March 8, 2021 and the rest of the society remaining closed until April 19, 2021 would keep R below 1, with some increase evident in infections compared to continual FNL until April 19, 2021. Reopening society in mid-April, without an increase in vaccination levels, could push R above 1 and induce a surge in infections, but the effect of vaccination may be able to control this in future depending on the transmission blocking properties of the vaccines.

Factors associated with COVID-19 related hospitalisation, critical care admission and mortality using linked primary and secondary care data

BackgroundTo identify risk factors associated with increased risk of hospitalisation, intensive care unit (ICU) admission and mortality in inner North East London (NEL) during the first UK COVID-19 wave. MethodsMultivariate logistic regression analysis on linked primary and secondary care data from people aged 16 or older with confirmed COVID-19 infection between 01/02/2020-30/06/2020 determined odds ratios (OR), 95% confidence intervals (CI) and p-values for the association between demographic, deprivation and clinical factors with COVID-19 hospitalisation, ICU admission and mortality. ResultsOver the study period 1,781 people were diagnosed with COVID-19, of whom 1,195 (67%) were hospitalised, 152 (9%) admitted to ICU and 400 (23%) died. Results confirm previously identified risk factors: being male, or of Black or Asian ethnicity, or aged over 50. Obesity, type 2 diabetes and chronic kidney disease (CKD) increased the risk of hospitalisation. Obesity increased the risk of being admitted to ICU. Underlying CKD, stroke and dementia in-creased the risk of death. Having learning disabilities was strongly associated with increased risk of death (OR=4.75, 95%CI=(1.91,11.84), p=0.001). Having three or four co-morbidities increased the risk of hospitalisation (OR=2.34,95%CI=(1.55,3.54),p<0.001;OR=2.40, 95%CI=(1.55,3.73), p<0.001 respectively) and death (OR=2.61, 95%CI=(1.59,4.28), p<0.001;OR=4.07, 95% CI= (2.48,6.69), p<0.001 respectively). ConclusionsWe confirm that age, sex, ethnicity, obesity, CKD and diabetes are important determinants of risk of COVID-19 hospitalisation or death. For the first time, we also identify people with learning disabilities and multi-morbidity as additional patient cohorts that need to be actively protected during COVID-19 waves.

Exploring overcrowding trends in an inner city emergence department in the UK before and during COVID-19 epidemic

BackgroundWe compared impact of three pre-COVID-19 interventions and of the COVID-19 UK-epidemic and the first UK national lockdown on overcrowding within University College London Hospital Emergency Department (UCLH ED). The three interventions: target the influx of patients at ED (A), reduce the pressure on in-patients beds (B) and improve ED processes to improve the flow of patents out from ED (C). MethodsWe analysed the change in overcrowding metrics (daily attendances, the proportion of people leaving within four hours of arrival (four-hours target) and the reduction in overall waiting time) across three analysis. The first analysis used data 01/04/2017-31/12-2019 to calculate changes over a period of six months before and after the start of interventions A-C. The second and third analyses focused on evaluating the impact of the COVID-19 epidemic, comparing the first 10 months in 2020 and 2019, and of the first national lockdown (23/03/2020-31/05/2020). ResultsPre-COVID-19 all interventions led to small reductions in waiting time (17%, p<0.001 for A and C;9%, p=0.322 for B) but also to a small decrease in the number of patients leaving within four hours of arrival (6.6%,7.4%,6.2% respectively A-C,p<0.001). In presence of the COVID-19 pandemic, attendance and waiting time were reduced (40% and 8%;p<0.001), and the number of people leaving within four hours of arrival was increased (6%,p<0.001). During the first lockdown, there was 65% reduction in attendance, 22% reduction in waiting time and 8% increase in number of people leaving within 4 hours of arrival (p<0.001). Crucially, when the lockdown was lifted, there was an increase (6.5%,p<0.001) in the percentage of people leaving within four hours, together with a larger (12.5%,p<0.001) decrease in waiting time. This occurred despite the increase of 49.6%(p<0.001) in attendance after lockdown ended. ConclusionsThe mixed results pre-COVID-19 (significant improvements in waiting time with some interventions but not improvement in the four-hours target), may be due to a spill-over effect where clogging up one part of the ED system affects other parts. Hence multifaceted interventions and a system-wide approach to improve the pathway of flow through the ED system is necessary. During 2020 and in presence of the COVID-19 epidemic, a shift in public behaviour with anxiety over attending hospitals and higher use of virtual consultations, led to notable drop in UCLH ED attendance and consequential curbing of overcrowding. Importantly, once the lockdown was lifted, although there was an increase in arrivals at UCLH ED, overcrowding metrics were reduced. Thus, the combination of shifted public behaviour and the restructuring changes during COVID-19 epidemic, maybe be able to curb future ED overcrowding, but longer timeframe analysis is required to confirm this.

The potential contribution of face coverings to the control of SARS-CoV-2 transmission in schools and broader society in the UK: a modelling study

Recent findings suggest that an adequate test-trace-isolate (TTI) strategy is needed to prevent a secondary COVID-19 wave with the reopening of society in the UK. Here we assess the potential importance of mandatory masks in the parts of community and in secondary schools. We show that, assuming current TTI levels, adoption of masks in secondary schools in addition to community settings can reduce the size of a second wave, but will not prevent it; more testing of symptomatic people, tracing and isolating of their contacts is also needed. To avoid a second wave, with masks mandatory in secondary schools and in certain community settings, under current tracing levels, 68% or 46% of those with symptomatic infection would need to be tested if masks effective coverage were 15% or 30% respectively, compared to 76% and 57% if masks are mandated in community settings but not secondary schools.

Controlling COVID-19 via test-trace-quarantine

Initial COVID-19 containment in the United States focused on limiting mobility, including school and workplace closures. However, these interventions have had enormous societal and economic costs. Here we demonstrate the feasibility of an alternative control strategy, test-trace-quarantine: routine testing of primarily symptomatic individuals, tracing and testing their known contacts, and placing their contacts in quarantine. We performed this analysis using Covasim, an open-source agent-based model, which was calibrated to detailed demographic, mobility, and epidemiological data for the Seattle region from January through June 2020. With current levels of mask use and schools remaining closed, we found that high but achievable levels of testing and tracing are sufficient to maintain epidemic control even under a return to full workplace and community mobility and with low vaccine coverage. The easing of mobility restrictions in June 2020 and subsequent scale-up of testing and tracing programs through September provided real-world validation of our predictions. Although we show that test-trace-quarantine can control the epidemic in both theory and practice, its success is contingent on high testing and tracing rates, high quarantine compliance, relatively short testing and tracing delays, and moderate to high mask use. Thus, in order for test-trace-quarantine to control transmission with a return to high mobility, strong performance in all aspects of the program is required.

RT-PCR testing to detect a COVID-19 outbreak in Austria: rapid, accurate and early diagnosis in primary care (The REAP study)

BackgroundDelay in COVID-19 detection has led to a major pandemic. We report rapid early detection of SARS-CoV-2 by reverse transcriptase-polymerase chain reaction (RT-PCR), comparing it to the serostatus of convalescent infection, at an Austrian National Sentinel Surveillance Practice in an isolated ski-resort serving a population of 22,829 people. MethodsRetrospective dataset of all 73 patients presenting with mild to moderate flu-like symptoms to a sentinel practice in the ski-resort of Schladming-Dachstein, Austria, between 24 February and 03 April, 2020. We split the outbreak in two halves, by dividing the period from the first to the last case by two, to characterise the following three cohorts of patients with confirmed infection: people with reactive RT-PCR presenting during the first half (early acute infection) vs. those presenting in the second half (late acute), and people with non-reactive RT-PCR (late convalescent). For each cohort we report the number of cases detected, the accuracy of RT-PCR and the duration of symptoms. We also report multivariate regression of 15 clinical symptoms as covariates, comparing all people with convalescent infection to those with acute infection. FindingsAll 73 patients had SARS-CoV-2 RT-PCR testing. 22 patients were diagnosed with COVID-19, comprising: 8 patients presenting early acute, and 7 presenting late acute and 7 late convalescent respectively; 44 patients tested SARS-COV-2 negative, and 7 were excluded. RT-PCR sensitivity was high (100%) among acute presenters, but dropped to 50% in the second half of the outbreak; specificity was 100%. The mean duration of symptoms was 2 days (range 1-4) among early acute presenters, and 4.4 days (1-7) among late acute and 8 days (2-12) among late convalescent presenters respectively. Convalescent infection was only associated with loss of taste (ORs=6.02;p=0.047). Acute infection was associated with loss of taste (OR=571.72;p=0.029), nausea and vomiting (OR=370.11;p=0.018), breathlessness (OR=134.46;p=0.049), and myalgia (OR=121.82;p=0.032); but not loss of smell, fever or cough. InterpretationRT-PCR rapidly and reliably detects early COVID-19 among people presenting with viral illness and multiple symptoms in primary care, particularly during the early phase of an outbreak. RT-PCR testing in primary care should be prioritised for effective COVID-19 prevention and control. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSA comprehensive and effective test-trace-isolate (TTI) strategy is necessary to keep track of current and future COVID-19 infection in the UK and avoid a secondary wave later this year, as society reopens. As part of a wider TTI strategy, it is important to assess the feasibility of COVID-19 testing in primary care. We searched PubMed for implementation of SARS-CoV-2 testing in primary care using the following search terms: ("SARS-CoV-2" OR "COVID-19") AND "testing" AND ("primary care" OR "general practice"). We did not find any studies that met these criteria. Added value of this studyTo our knowledge, our study provides first evidence that extension of a National Influenza Surveillance Programme to include SARS-CoV-2 RT-PCR testing in primary care leads to viral detection among patients presenting with mild to moderate flu-like illness during a local outbreak of COVID-19. We show that the sensitivity of reverse transcriptase-polymerase chain reaction (RT-PCR), the technique to detect viral RNA, is high (100%) in the initial phase of the outbreak and among patients who were acutely unwell. Acute infection was associated with multiply symptoms: loss of taste, nausea and vomiting, breathlessness, myalgia and sore throat; but not loss of smell, fever or cough. We also show high correlation between reactive RT-PCR and seropositivity. Implications of all available evidenceOur findings suggest that RT-PCR can rapidly and reliably detect early COVID-19 among people presenting with viral illness and multiple symptoms in primary care, particularly during the early phase of an outbreak. Furthermore RT-PCR testing in primary care can effectively detect new COVID-19 clusters in the community and should be included in any strategy for prevention and control of the disease.

Determining the optimal strategy for reopening schools, work and society in the UK: balancing earlier opening and the impact of test and trace strategies with the risk of occurrence of a secondary COVID-19 pandemic wave

BackgroundIn order to slow down the spread of SARS-CoV-2, the virus causing the COVID-19 pandemic, the UK government has imposed strict physical distancing ( lockdown) measures including school dismissals since 23 March 2020. As evidence is emerging that these measures may have slowed the spread of the pandemic, it is important to assess the impact of any changes in strategy, including scenarios for school reopening and broader relaxation of social distancing. This work uses an individual-based model to predict the impact of a suite of possible strategies to reopen schools in the UK, including that currently proposed by the UK government. MethodsWe use Covasim, a stochastic agent-based model for transmission of COVID-19, calibrated to the UK epidemic. The model describes individuals contact networks stratified as household, school, work and community layers, and uses demographic and epidemiological data from the UK. We simulate a range of different school reopening strategies with a society-wide relaxation of lockdown measures and in the presence of different non-pharmaceutical interventions, to estimate the number of new infections, cumulative cases and deaths, as well as the effective reproduction number with different strategies. To account for uncertainties within the stochastic simulation, we also simulated different levels of infectiousness of children and young adults under 20 years old compared to older ages. FindingsWe found that with increased levels of testing of people (between 25% and 72% of symptomatic people tested at some point during an active COVID-19 infection depending on scenarios) and effective contact-tracing and isolation for infected individuals, an epidemic rebound may be prevented across all reopening scenarios, with the effective reproduction number (R) remaining below one and the cumulative number of new infections and deaths significantly lower than they would be if testing did not increase. If UK schools reopen in phases from June 2020, prevention of a second wave would require testing 51% of symptomatic infections, tracing of 40% of their contacts, and isolation of symptomatic and diagnosed cases. However, without such measures, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a secondary pandemic wave, as are other scenarios for reopening. When infectiousness of <20 year olds was varied from 100% to 50% of that of older ages, our findings remained unchanged. InterpretationTo prevent a secondary COVID-19 wave, relaxation of social distancing including reopening schools in the UK must be implemented alongside an active large-scale population-wide testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of symptomatic and diagnosed individuals. Such combined measures have a greater likelihood of controlling the transmission of SARS-CoV-2 and preventing a large number of COVID-19 deaths than reopening schools and society with the current level of implementation of testing and isolation of infected individuals. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSSince the onset of COVID-19 pandemic, mathematical modelling has been at the heart of informing decision-making, including the imposing of the lockdown in the UK. As countries are now starting to plan modification of these measures, it is important to assess the impact of different lockdown exit strategies including whether and how to reopen schools and relax other social distancing measures. Added value of this studyUsing mathematical modelling, we explored the impact of strategies to reopen schools and society in the UK, including that currently proposed by the UK government. We assessed the impact of opening all schools fully or in a phased way with only some school years going back, with a society-wide relaxation of lockdown measures and in the presence of a different levels of implementation of test-trace-isolate strategies. We projected the number of new COVID-19 infections, cumulative cases and deaths, as well as the temporal distribution in the effective reproduction number (R) across different strategies. Our study is the first to provide quantification of the amount of testing and tracing that would be needed to prevent a second wave of COVID-19 in the UK under different reopening scenarios. To account for uncertainties within the stochastic simulation, we also simulated different levels of infectiousness of children and young adults under 20 years old compared to older ages. Implications of all the available evidenceEvidence to date points to the need for additional testing, contact tracing, and isolation of individuals who have either been diagnosed with COVID-19, or who are considered to be at high risk of carrying infection due to their contact history or symptoms. Our study supports these conclusions and provides additional quantification of the amount of testing and tracing that would be needed to prevent a second wave of COVID-19 in the UK under different lockdown exit strategies. Reopening schools and society alongside active testing of the symptomatic population (between 25% and 72% of people with symptomatic COVID-19 infection depending on scenarios) and with an effective contact-tracing and rapid isolation of symptomatic and diagnosed individuals, will not only prevent a secondary pandemic wave, but is also likely to be able to control the transmission of SARS-CoV-2, via keeping the R value below 1, thus preventing a large number of COVID-19 cases and deaths. However, in the absence of fully implemented large-scale testing, contact-tracing and isolation strategy, plans for reopening schools, including those currently proposed by the UK government, and the associated increase in work and community contacts, are likely to induce a secondary pandemic wave of COVID-19.

Susceptibility to and transmission of COVID-19 amongst children and adolescents compared with adults: a systematic review and meta-analysis

ImportanceThe degree to which children and young people are infected by and transmit the SARS-CoV-2 virus is unclear. The role of children and young people in transmission of SARS-CoV-2 is dependent on susceptibility, symptoms, viral load, social contact patterns and behaviour. ObjectiveWe undertook a rapid systematic review to address the question "What is the susceptibility to and transmission of SARS-CoV-2 by children and adolescents compared with adults?" Data sourcesWe searched PubMed and medRxiv up to 28 July 2020 and identified 13,926 studies, with additional studies identified through handsearching of cited references and professional contacts. Study SelectionWe included studies which provided data on the prevalence of SARS-CoV-2 in children and young people (<20 years) compared with adults derived from contact-tracing or population-screening. We excluded single household studies. Data extraction and SynthesisWe followed PRISMA guidelines for abstracting data, independently by 2 reviewers. Quality was assessed using a critical appraisal checklist for prevalence studies. Random effects meta-analysis was undertaken. Main OutcomesSecondary infection rate (contact-tracing studies) or prevalence or seroprevalence (population-screening studies) amongst children and young people compared with adults. Results32 studies met inclusion criteria; 18 contact-tracing and 14 population-screening. The pooled odds ratio of being an infected contact in children compared with adults was 0.56 (0.37, 0.85) with substantial heterogeneity (95%). Three school contact tracing studies found minimal transmission by child or teacher index cases. Findings from population-screening studies were heterogenous and were not suitable for meta-analysis. The majority of studies were consistent with lower seroprevalence in children compared with adults, although seroprevalence in adolescents appeared similar to adults. ConclusionsThere is preliminary evidence that children and young people have lower susceptibility to SARS-CoV-2, with a 43% lower odds of being an infected contact. There is weak evidence that children and young people play a lesser role in transmission of SARS-CoV-2 at a population level. Our study provides no information on the infectivity of children. Key pointsO_ST_ABSQuestionC_ST_ABSWhat is the evidence on the susceptibility and transmission of children and young people to SARS-CoV-2 in comparison with adults? FindingsIn this systematic review and meta-analysis, children and young people under 18-20 years had an 435 lower odds of secondary infection of with SARS-CoV-2 compared to adults 20 years plus, a significant difference. This finding was most marked in children under 12-14 years. Data were insufficient to conclude whether transmission of SARS-CoV-2 by children is lower than by adults. MeaningWe found preliminary evidence that children have a lower susceptibility for SARS-CoV-2 infection compared with adults, although data for adolescents is less clear. The role that children and young people play in transmission of this pandemic remains unclear.

Testing, tracing and isolation in compartmental models

Existing compartmental mathematical modelling methods for epidemics, such as SEIR models, cannot accurately represent effects of contact tracing. This makes them inappropriate for evaluating testing and contact tracing strategies to contain an outbreak. An alternative used in practice is the application of agent- or individual-based models (ABM). However ABMs are complex, less well-understood and much more computationally expensive. This paper presents a new method for accurately including the effects of Testing, contact-Tracing and Isolation (TTI) strategies in standard compartmental models. We derive our method using a careful probabilistic argument to show how contact tracing at the individual level is reflected in aggregate on the population level. We show that the resultant SEIR-TTI model accurately approximates the behaviour of a mechanistic agent-based model at far less computational cost. The computationally efficiency is such that it be easily and cheaply used for exploratory modelling to quantify the required levels of testing and tracing, alone and with other interventions, to assist adaptive planning for managing disease outbreaks.

Covasim: an agent-based model of COVID-19 dynamics and interventions

The COVID-19 pandemic has created an urgent need for models that can project epidemic trends, explore intervention scenarios, and estimate resource needs. Here we describe the methodology of Covasim (COVID-19 Agent-based Simulator), an open-source model developed to help address these questions. Covasim includes country-specific demographic information on age structure and population size; realistic transmission networks in different social layers, including households, schools, workplaces, long-term care facilities, and communities; age-specific disease outcomes; and intrahost viral dynamics, including viral-load-based transmissibility. Covasim also supports an extensive set of interventions, including non-pharmaceutical interventions, such as physical distancing and protective equipment; pharmaceutical interventions, including vaccination; and testing interventions, such as symptomatic and asymptomatic testing, isolation, contact tracing, and quarantine. These interventions can incorporate the effects of delays, loss-to-follow-up, micro-targeting, and other factors. Implemented in pure Python, Covasim has been designed with equal emphasis on performance, ease of use, and flexibility: realistic and highly customized scenarios can be run on a standard laptop in under a minute. In collaboration with local health agencies and policymakers, Covasim has already been applied to examine epidemic dynamics and inform policy decisions in more than a dozen countries in Africa, Asia-Pacific, Europe, and North America.