RESUMEN
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.
RESUMEN
During the current COVID-19 pandemic, testing kit and RNA extraction kit availability has become a major limiting factor in the ability to determine patient disease status and accurately quantify prevalence. Current testing strategies rely on individual tests of cases matching restrictive diagnostic criteria to detect SARS-CoV-2 RNA, limiting testing of asymptomatic and mild cases. Testing these individuals is one effective way to understand and reduce the spread of COVID-19. Here, we develop a pooled testing strategy to identify these low-risk individuals. Drawing on the well-studied group testing literature, modeling suggests practical changes to testing protocols which can reduce test costs and stretch a limited test kit supply. When most tests are negative, pooling reduces the total number of tests up to four-fold at 2% prevalence and eight-fold at 0.5% prevalence. At current SARS-CoV-2 prevalence, randomized group testing optimized per country could double the number of tested individuals from 1.85M to 3.7M using only 671k more tests. This strategy is well-suited to supplement testing for asymptomatic and mild cases who would otherwise go untested, and enable them to adopt behavioral changes to slow the spread of COVID-19.