The Timing of COVID-19 Transmission

Ferretti, Luca; Ledda, Alice; Wymant, Chris; Zhao, Lele; Ledda, Virginia; Dörner, Lucie Abeler-; Kendall, Michaela; Nurtay, Anel; Cheng, Hao-Yuan; Ng, Ta-Chou; Lin, Hsien-Ho; Hinch, Rob; Masel, Joanna; Kilpatrick, A. Marm; Fraser, Christophe

doi:10.2139/ssrn.3716879

Cited by 51 publications

(57 citation statements)

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“…We estimate that the Omicron variant is growing in England at an exponential growth rate of r = 0.29 per day. This corresponds to a 2.4-day doubling time and a reproduction number R t = 4.0, assuming a generation interval of 5.5 days with standard deviation 1.8 days (25,26). If the generation interval of Omicron is shorter than 5.5 days, then R t would be correspondingly lower.…”

Section: Resultsmentioning

confidence: 99%

Projected epidemiological consequences of the Omicron SARS-CoV-2 variant in England, December 2021 to April 2022

Barnard

Davies

Pearson

et al. 2021

Preprint

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The Omicron B.1.1.529 SARS-CoV-2 variant was first detected in late November 2021 and has since spread to multiple countries worldwide. We model the potential consequences of the Omicron variant on SARS-CoV-2 transmission and health outcomes in England between December 2021 and April 2022, using a deterministic compartmental model fitted to epidemiological data from March 2020 onwards. Because of uncertainty around the characteristics of Omicron, we explore scenarios varying the extent of Omicron’s immune escape and the effectiveness of COVID-19 booster vaccinations against Omicron, assuming the level of Omicron’s transmissibility relative to Delta to match the growth in observed S gene target failure data in England. We consider strategies for the re-introduction of control measures in response to projected surges in transmission, as well as scenarios varying the uptake and speed of COVID-19 booster vaccinations and the rate of Omicron’s introduction into the population. These results suggest that Omicron has the potential to cause substantial surges in cases, hospital admissions and deaths in populations with high levels of immunity, including England. The reintroduction of additional non-pharmaceutical interventions may be required to prevent hospital admissions exceeding the levels seen in England during the previous peak in winter 2020–2021.

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Section: Resultsmentioning

confidence: 99%

Projected epidemiological consequences of the Omicron SARS-CoV-2 variant in England, December 2021 to April 2022

Barnard

Davies

Pearson

et al. 2021

Preprint

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“…Within the model, an infected pupil's relative probability of transmission to other pupils since day of infection was based upon a previously derived infectivity profile for COVID-19 41 , based on data from known sourcerecipient pairs 42 , with an assumed incubation period distribution under the assumption that the generation time and incubation period are independent. Symptomatic pupils developed symptoms on a day drawn from a Gamma distribution with shape 5.807 and scale 0.948 43 , corresponding to a mean time to symptom onset of 5.5 days.…”

Section: Transmissionmentioning

confidence: 99%

“…those not isolating and it being a school day) transmitted infection to other pupils within their year group with a probability dependent on the time elapsed since their infection. Specifically, we assumed that the relative probability of transmission since the day of infection is given by a Gamma distribution (Γ I (d)) with shape 5.62 and scale 0.98 41 , derived from data from known source-recipient pairs 42 , with an assumed incubation period distribution (Gamma distributed with shape 5.807 and scale 0.948 43 ) under the assumption that the generation time and incubation period are independent. After 14 days, infected individuals recover with immunity that persists over the course of the simulation.…”

Section: S21 Within-school Transmissionmentioning

confidence: 99%

Quantifying within-school SARS-CoV-2 transmission and the impact of lateral flow testing in secondary schools in England

Leng

Hill

Holmes

et al. 2021

Preprint

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Background To control within-school SARS-CoV-2 transmission in England, secondary school pupils have been encouraged to participate in twice weekly mass testing via lateral flow device tests (LFTs) from 8th March 2021, to complement an isolation of close contacts policy in place since 31st August 2020. Strategies involving the isolation of close contacts can lead to high levels of absences, negatively impacting pupils. Methods We fit a stochastic individual-based model of secondary schools to both community swab testing data and secondary school absences data. By simulating epidemics in secondary schools from 31st August 2020 until 21st May 2021, we quantify within-school transmission of SARS-CoV-2 in secondary schools in England, the impact of twice weekly mass testing on within-school transmission, and the potential impact of alternative strategies to the isolation of close contacts in reducing pupil absences. Findings The within-school reproduction number, R school , has remained below 1 from 31st August 2020 until 21st May 2021. Twice weekly mass testing using LFTs have helped to control within-school transmission in secondary schools in England. A strategy of serial contact testing alongside mass testing substantially reduces absences compared to strategies involving isolating close contacts, with only a marginal increase in within-school transmission. Interpretation Secondary school control strategies involving mass testing have the potential to control within-school transmission while substantially reducing absences compared to an isolation of close contacts policy.

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“…The resulting distribution is shown in Fig. 1(d) using estimates from the literature of p(τ i ) ∼ Ŵ(5.0 ± 0.75, 10 ± 1.5) and p(τ d ) ∼ Ŵ(4.5 ± 0.75, 5.0 ± 1.0) 19,20 . With these distributions in place it is straightforward to simulate an epidemic if R(t) and k are known.…”

Section: Openmentioning

confidence: 99%

Superspreading quantified from bursty epidemic trajectories

Kirkegaard

Sneppen

2021

Sci Rep

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The quantification of spreading heterogeneity in the COVID-19 epidemic is crucial as it affects the choice of efficient mitigating strategies irrespective of whether its origin is biological or social. We present a method to deduce temporal and individual variations in the basic reproduction number directly from epidemic trajectories at a community level. Using epidemic data from the 98 districts in Denmark we estimate an overdispersion factor k for COVID-19 to be about 0.11 (95% confidence interval 0.08–0.18), implying that 10 % of the infected cause between 70 % and 87 % of all infections.

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The Timing of COVID-19 Transmission

Cited by 51 publications

References 0 publications

Projected epidemiological consequences of the Omicron SARS-CoV-2 variant in England, December 2021 to April 2022

Projected epidemiological consequences of the Omicron SARS-CoV-2 variant in England, December 2021 to April 2022

Quantifying within-school SARS-CoV-2 transmission and the impact of lateral flow testing in secondary schools in England

Superspreading quantified from bursty epidemic trajectories

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