A novel SARS-CoV-2 variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England in November 2020 and is rapidly spreading toward fixation. Using a variety of statistical and dynamic modelling approaches, we estimate that this variant has a 43–90% (range of 95% credible intervals 38–130%) higher reproduction number than preexisting variants. A fitted two-strain dynamic transmission model shows that VOC 202012/01 will lead to large resurgences of COVID-19 cases. Without stringent control measures, including limited closure of educational institutions and a greatly accelerated vaccine roll-out, COVID-19 hospitalisations and deaths across England in 2021 will exceed those in 2020. Concerningly, VOC 202012/01 has spread globally and exhibits a similar transmission increase (59–74%) in Denmark, Switzerland, and the United States.

Background: Interventions are now in place worldwide to reduce transmission of the novel coronavirus. Assessing temporal variations in transmission in different countries is essential for evaluating the effectiveness of public health interventions and the impact of changes in policy. Methods: We use case notification data to generate daily estimates of the time-dependent reproduction number in different regions and countries. Our modelling framework, based on open source tooling, accounts for reporting delays, so that temporal variations in reproduction number estimates can be compared directly with the times at which interventions are implemented. Results: We provide three example uses of our framework. First, we demonstrate how the toolset displays temporal changes in the reproduction number. Second, we show how the framework can be used to reconstruct case counts by date of infection from case counts by date of notification, as well as to estimate the reproduction number. Third, we show how maps can be generated to clearly show if case numbers are likely to decrease or increase in different regions. Results are shown for regions and countries worldwide on our website (https://epiforecasts.io/covid/) and are updated daily. Our tooling is provided as an open-source R package to allow replication by others. Conclusions: This decision-support tool can be used to assess changes in virus transmission in different regions and countries worldwide. This allows policymakers to assess the effectiveness of current interventions, and will be useful for inferring whether or not transmission will increase when interventions are lifted. As well as providing daily updates on our website, we also provide adaptable computing code so that our approach can be used directly by researchers and policymakers on confidential datasets. We hope that our tool will be used to support decisions in countries worldwide throughout the ongoing COVID-19 pandemic.

Adjusting for delay from confirmation-to-death, we estimated case and infection fatality ratios (CFR, IFR) for COVID-19 on the Diamond Princess ship as 2.3% (0.75%-5.3%) and 1.2% (0.38-2.7%). Comparing deaths onboard with expected deaths based on naive CFR estimates using China data, we estimate IFR and CFR in China to be 0.5% (95% CI: 0.2-1.2%) and 1.1% (95% CI: 0.3-2.4%) respectively.

A novel SARS-CoV-2 variant, VOC 202012/01, emerged in southeast England in November 2020 and is rapidly spreading towards fixation. Using a variety of statistical and dynamic modelling approaches, we assessed the relative transmissibility of this novel variant. Depending on the analysis, we estimate that VOC 202012/01 is 43–82% (range of 95% credible intervals 38–106%) more transmissible than preexisting variants of SARS-CoV-2. We did not find clear evidence that VOC 202012/01 results in greater or lesser severity of disease than preexisting variants. Nevertheless, the increase in transmissibility is likely to lead to a large increase in incidence. To assess the potential impact of VOC 202012/01, we fitted a two-strain mathematical model of SARS-CoV-2 transmission to observed COVID-19 hospital admissions, hospital and ICU bed occupancy, and deaths; SARS-CoV-2 PCR prevalence and seroprevalence; and the relative frequency of VOC 202012/01. We find that without stringent control measures, COVID-19 hospitalisations and deaths are projected to reach higher levels in 2021 than were observed in 2020. Control measures of a similar stringency to the national lockdown implemented in England in November 2020 are unlikely to reduce the effective reproduction number Rt to less than 1, unless primary schools, secondary schools, and universities are also closed. We project that large resurgences of the virus are likely to occur following easing of control measures. It may be necessary to greatly accelerate vaccine roll-out to have an appreciable impact in suppressing the resulting disease burden.

Background: Assessing temporal variations in transmission in different countries is essential for monitoring the epidemic, evaluating the effectiveness of public health interventions and estimating the impact of changes in policy. Methods: We use case and death notification data to generate daily estimates of the time-varying reproduction number globally, regionally, nationally, and subnationally over a 12-week rolling window. Our modelling framework, based on open source tooling, accounts for uncertainty in reporting delays, so that the reproduction number is estimated based on underlying latent infections. Results: Estimates of the reproduction number, trajectories of infections, and forecasts are displayed on a dedicated website as both maps and time series, and made available to download in tabular form. Conclusions:  This decision-support tool can be used to assess changes in virus transmission both globally, regionally, nationally, and subnationally. This allows public health officials and policymakers to track the progress of the outbreak in near real-time using an epidemiologically valid measure. As well as providing regular updates on our website, we also provide an open source tool-set so that our approach can be used directly by researchers and policymakers on confidential data-sets. We hope that our tool will be used to support decisions in countries worldwide throughout the ongoing COVID-19 pandemic.