Abstract
The epidemiological curve (epicurve) is one of the simplest yet most useful tools used by field epidemiologists, modellers, and decision makers for assessing the dynamics of infectious disease epidemics. Here, we present the free, open-source package incidence for the R programming language, which allows users to easily compute, handle, and visualise epicurves from unaggregated linelist data. This package was built in accordance with the development guidelines of the R Epidemics Consortium (RECON), which aim to ensure robustness and reliability through extensive automated testing, documentation, and good coding practices. As such, it fills an important gap in the toolbox for outbreak analytics using the R software, and provides a solid building block for further developments in infectious disease modelling. incidence is available from https://www.repidemicsconsortium.org/incidence.
Highlights
Responses to infectious disease epidemics use a growing body of data sources to inform decision making (Cori et al, 2017; Fraser et al, 2009; WHO Ebola Response Team et al, 2014; WHO Ebola Response Team et al, 2015)
We introduce incidence, an R package developed as part of the toolbox for epidemics analysis of the R Epidemics Consortium (RECON) which aims to fill this gap
We have shown that an incidence object can flexibly be defined at different datetime intervals with any number of stratifications and be subset by groups or dates
Summary
2. Quirine ten Bosch , Wageningen University and Research Centre, Wageningen, The Netherlands. 3. Bertrand Sudre, European Centre for Disease Prevention and Control (ECDC), Solna, Sweden. This article is included in the RPackage gateway. Any reports and responses or comments on the article can be found at the end of the article
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