Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1126/science.abb6936 |
Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing | |
Luca Ferretti; Chris Wymant; Michelle Kendall; Lele Zhao; Anel Nurtay; Lucie Abeler-Dörner; Michael Parker; David Bonsall; Christophe Fraser | |
2020-05-08 | |
发表期刊 | Science |
出版年 | 2020 |
英文摘要 | New analyses indicate that severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2) is more infectious and less virulent than the earlier SARS-CoV-1, which emerged in China in 2002. Unfortunately, the current virus has greater epidemic potential because it is difficult to trace mild or presymptomatic infections. As no treatment is currently available, the only tools that we can currently deploy to stop the epidemic are contact tracing, social distancing, and quarantine, all of which are slow to implement. However imperfect the data, the current global emergency requires more timely interventions. Ferretti et al. explored the feasibility of protecting the population (that is, achieving transmission below the basic reproduction number) using isolation coupled with classical contact tracing by questionnaires versus algorithmic instantaneous contact tracing assisted by a mobile phone application. For prevention, the crucial information is understanding the relative contributions of different routes of transmission. A phone app could show how finite resources must be divided between different intervention strategies for the most effective control.
Science , this issue p. [eabb6936][1]
### INTRODUCTION
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome–coronavirus 2 (SARS-CoV-2), has clear potential for a long-lasting global pandemic, high fatality rates, and incapacitated health systems. Until vaccines are widely available, the only available infection prevention approaches are case isolation, contact tracing and quarantine, physical distancing, decontamination, and hygiene measures. To implement the right measures at the right time, it is of crucial importance to understand the routes and timings of transmission.
### RATIONALE
We used key parameters of epidemic spread to estimate the contribution of different transmission routes with a renewal equation formulation, and analytically determined the speed and scale for effective identification and contact tracing required to stop the epidemic.
### RESULTS
We developed a mathematical model for infectiousness to estimate the basic reproductive number R and to quantify the contribution of different transmission routes. To parameterize the model, we analyzed 40 well-characterized source-recipient pairs and estimated the distribution of generation times (time from infection to onward transmission). The distribution had a median of 5.0 days and standard deviation of 1.9 days. We used published parameters for the incubation time distribution (median 5.2 days) and the epidemic doubling time (5.0 days) from the early epidemic data in China.
The model estimated R = 2.0 in the early stages of the epidemic in China. The contributions to R included 46% from presymptomatic individuals (before showing symptoms), 38% from symptomatic individuals, 10% from asymptomatic individuals (who never show symptoms), and 6% from environmentally mediated transmission via contamination. Results on the last two routes are speculative. According to these estimates, presymptomatic transmissions alone are almost sufficient to sustain epidemic growth.
To estimate the requirements for successful contact tracing, we determined the combination of two key parameters needed to reduce R to less than 1: the proportion of cases who need to be isolated, and the proportion of their contacts who need to be quarantined. For a 3-day delay in notification assumed for manual contact tracing, no parameter combination leads to epidemic control. Immediate notification through a contact-tracing mobile phone app could, however, be sufficient to stop the epidemic if used by a sufficiently high proportion of the population.
We propose an app, based on existing technology, that allows instant contact tracing. Proximity events between two phones running the app are recorded. Upon an individual’s COVID-19 diagnosis, contacts are instantly, automatically, and anonymously notified of their risk and asked to self-isolate. Practical and logistical factors (e.g., uptake, coverage, R in a given population) will determine whether an app is sufficient to control viral spread on its own, or whether additional measures to reduce R (e.g., physical distancing) are required. The performance of the app in scenarios with higher values of R can be explored at |
领域 | 气候变化 ; 资源环境 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/249804 |
专题 | 气候变化 资源环境科学 |
推荐引用方式 GB/T 7714 | Luca Ferretti,Chris Wymant,Michelle Kendall,et al. Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing[J]. Science,2020. |
APA | Luca Ferretti.,Chris Wymant.,Michelle Kendall.,Lele Zhao.,Anel Nurtay.,...&Christophe Fraser.(2020).Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing.Science. |
MLA | Luca Ferretti,et al."Quantifying SARS-CoV-2 transmission suggests epidemic control with digital contact tracing".Science (2020). |
条目包含的文件 | 条目无相关文件。 |
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