"Predictions of COVID-19 dynamics in the UK: short-term forecasting, analysis of potential exit strategies and impact of reopening schools"
Efforts to suppress transmission of SARS-CoV-2 in the UK saw non-pharmaceutical interventions being invoked throughout March 2020, culminating in the application of lockdown measures. From mid-April, COVID-19 cases were declining and there was good evidence to suggest that the effective reproduction number had dropped below 1. A multi-phase relaxation plan to emerge from lockdown was put in place, including primary schools being scheduled to partially reopen in England on 1st June. Regarding the future course of the COVID-19 outbreak in the UK, mathematical models have provided, and continue to provide, short and long term forecasts to support evidence-based policymaking. We present a deterministic, age-structured transmission model for SARS-CoV-2 that uses real-time data on confirmed cases requiring hospital care and mortality to provide predictions on epidemic spread in ten regions of the UK. The model captures a range of age-dependent heterogeneities, reduced transmission from asymptomatic infections and produces a good fit to the key epidemic features over time. We illustrate how the model has been used to generate short-term predictions, assess potential lockdown exit strategies, and the impact of children returning to school. We found that significant relaxation of social distancing measures from 7th May could lead to a rapid resurgence of COVID-19 disease and the health system being quickly overwhelmed by a second epidemic wave. On reopening schools, whilst children returning to educational establishments results in more mixing between children and an increase in transmission of the disease, the magnitude of that increase can be low dependent upon the age-groups that return to school and the behaviour of the remaining population. Our work confirmed the effectiveness of stringent non-pharmaceutical measures in March 2020 to suppress the epidemic. It also provided support for the need for a cautious, measured approach to relaxation of lockdown measures, to support the health service through subduing demand on hospital beds. Finally, it indicated that any reopening of schools would result in increased mixing and infection amongst children and the wider population, although the opening of schools alone at that time was unlikely to push the value of R above one.
Los Alamos National Lab
"Estimating the epidemic growth rate and the reproductive number R0 of SARS-CoV-2 and implications for vaccination"
SARS-CoV-2 is a novel pathogen causes the COVID-19 pandemic. Some of the basic epidemiological parameters, such as the exponential epidemic growth rate and R0 are debated. We collected and analyzed data from China, eight European countries and the US using a variety of inference approaches. In all countries, the early epidemic grew exponentially at rates between 0.19-0.29/day (epidemic doubling times between 2.4-3.7 days). I will discuss the appropriate serial intervals to estimate the basic reproductive number R0 and argue that existing evidence suggests a highly infectious virus with an R0 likely between 4.0 and 7.1. Further, we found that similar levels of intervention efforts are needed, no matter the goal is mitigation or containment. We further show that regular repeated vaccinations will be required to maintain herd immunity if the duration of protective immunity is consistent with other known coronaviruses and that individual-level heterogeneity in protective immunity can significantly affect vaccination policy.
Thi Mui Pham
"Impact of self-imposed prevention measures and short-term government intervention on mitigating and delaying a COVID-19 epidemic"
Background: With new cases of COVID-19 surging around the world, many countries have to prepare for moving beyond the containment phase. Prediction of the effectiveness of non-case-based interventions for mitigating, delaying or preventing the epidemic is urgent, especially for countries affected by the ongoing seasonal influenza activity. Methods: We developed a deterministic transmission model to evaluate the impact of self-imposed pre- vention measures (handwashing, mask-wearing, and social distancing) due to the spread of COVID-19 awareness and of short-term government-imposed social distancing on the peak number of diagnoses, attack rate and time until the peak number of diagnoses. Findings: For fast awareness spread in the population, self-imposed measures can significantly reduce the attack rate, diminish and postpone the peak number of diagnoses. A large epidemic can be prevented if the efficacy of these measures exceeds 50%. For slow awareness spread, self-imposed measures reduce the peak number of diagnoses and attack rate but do not affect the timing of the peak. Short-term government policies on social distancing (e.g. community-wide quarantine) that are initiated early can only postpone the epidemic peak whereas later implementation can lead to a reduction of the attack rate and a flatter peak. Interpretation: Handwashing, mask-wearing and social distancing as a reaction to information dissem- ination about COVID-19 can be effective strategies to mitigate and delay the epidemic. We stress the importance of rapidly spreading awareness on the use of these self-imposed prevention measures in the population. Early-initiated short-term government-imposed social distancing can buy time for healthcare systems to prepare for an increasing COVID-19 burden.
University College London
"Determining the optimal strategy for reopening schools, workplaces and society in the UK: modelling patterns of reopening, the impact of test and trace strategies and risk of occurrence of a secondary COVID-19 pandemic wave"
Background: As evidence is emerging that the UK lockdown has slowed the spread of the pandemic, it is important to assess the impact of any changes in strategy, including school reopening and broader relaxation of physical distancing measures moving forward. This work uses an individual-based model to predict the impact of two possible strategies for reopening schools to all students (full-time versus part-time rotas) in the UK from September 2020, in combination with different assumptions about the scale-up of testing. Methods: We use Covasim, a stochastic agent-based model for transmission of COVID-19, calibrated to the UK epidemic. The model describes individuals’ contact networks stratified into household, school, workplace and community layers, and uses demographic and epidemiological data from the UK. We simulate six different scenarios, representing the combination of two school reopening strategies and three testing scenarios, and estimate the number of new infections, cases and deaths, as well as the effective reproduction number (R) under 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. Findings: We found that with increased levels of testing (between 59% and 87% of symptomatic people tested at some point during an active COVID-19 infection, depending on the scenario), and effective contact tracing and isolation, an epidemic rebound may be prevented. Assuming 68% of contacts could be traced, we estimate that 75% of those with symptomatic infection would need to be diagnosed and isolated if schools return full-time in September, or 65% if a part-time rota system were used. If only 40% of contacts could be traced, these figures would increase to 87% and 75%, respectively.However, without such measures, reopening of schools together with gradual relaxing of the lockdown measures are likely to induce a secondary wave that would peak in December 2020 if schools open full-time in September, and in February 2021 if a part-time rota system were adopted. In either case, the secondary wave would result in R rising above 1 and a resulting secondary wave of infections 2-2.3 times the size of the original COVID-19 wave. When infectiousness of <20 year olds was varied from 100% to 50% of that of older ages, we still find that comprehensive and effective TTI would be required to avoid a secondary COVID-19 wave. Interpretation: To prevent a secondary COVID-19 wave, relaxation of physical distancing including reopening schools in the UK must be accompanied by large-scale testing of symptomatic individuals and effective tracing of their contacts, followed by isolation of diagnosed individuals.