A New Framework and Software to Estimate Time-Varying Reproduction Numbers During Epidemics
By Anne Cori, Neil M. Ferguson, Christophe Fraser, Simon Cauchemez. American Journal of Epidemiology, 2013
1,535 citations recorded by the source corpus.
The quantification of transmissibility during epidemics is essential to designing and adjusting public health responses. Transmissibility can be measured by the reproduction number R, the average number of secondary cases caused by an infected individual. Several methods have been proposed to estimate R over the course of an epidemic; however, they are usually difficult to implement for people without a strong background in statistical modeling. Here, we present a ready-to-use tool for estimating R from incidence time series, which is implemented in popular software including Microsoft Excel (Microsoft Corporation, Redmond, Washington). This tool produces novel, statistically robust analytical estimates of R and incorporates uncertainty in the distribution of the serial interval (the time between the onset of symptoms in a primary case and the onset of symptoms in secondary cases). We applied the method to 5 historical outbreaks; the resulting estimates of R are consistent with those presented in the literature. This tool should help epidemiologists quantify temporal changes in the transmission intensity of future epidemics by using surveillance data.
Subfields: Epidemiology, Modeling and Simulation, Public Health, Environmental and Occupational Health
View Paper: https://www.semanticscholar.org/paper/a6f1b64f5e8d7d26b695dc08f66147da3d51483e
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Citations in the corpus
- Mathematical perspective of Covid-19 pandemic: Disease extinction criteria in deterministic and stochastic models (2020, neutral): “Real-time reproduction number (RTRN) is a data-driven analysis, which describes the epidemic status at every instant of time [46].”
- Improved inference of time-varying reproduction numbers during infectious disease outbreaks (2019, methodology): “The latter therefore characterises the “instantaneous” transmissibility at time t, and is more straightforward to estimate in real-time than the case reproduction number because it does not require assumptions about future transmissibility (Cori et al., 2013).”