Sensitivity analysis

The perfromance of EVI depends on the specified case definition (i.e.,  \(r\)) and the desired accuracy. Ideally, in the presence of historical data, various case defintions should be explored to identify which one provides the optimal index for monitoring an epidemic.

Example Data

The current most serious threat to global health and economy\cite{Fauci_2020} is the COVID-19 pandemic that was reported to the WHO China Country Office on December 31, 2019\cite{world2020pneumonia}. Data on the confrimed cases of COVID-19 were retrieved by the COVID-19 Data Repository, which is maintained by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University\cite{Dong2020}. The number of daily confirmed new cases of COVID-19, for each country, from January 22, 2020 until April 13, 2021 were analyzed. Because of the variability due to different reporting rates between working days and weekends the 7-day moving average rather than the axctuall observed daily cases were analyzed.
For the primary analysis the case definition was an increase in the mean of expected cases equal or higher than twenty percent, that is: \(r=\frac{1}{1.2}\). For sensitivity analysis the detection of an increase in the mean of expected cases equal or higher than 50 percent(\(r=\frac{1}{1.5}\)) was also considered. Data were analyzed separately for each country and for each of the United States of America that had, until April 13, 2021, experienced a total number of cases higher than 20,000.
Results for Italy, one of the most severely affected EU countries\cite{livingston2020coronavirus}, and New York, which was in the epicentre of the pandemic in the U.S.\cite{thompson2020covid}, are presented in the main manuscipt. Results from a list of selected countries (Argentina, Australia, Belgium, Brazil, California, Canada, Czechia, Florida, France, Germany, Greece, India, Italy, Netherlands, New York, Poland, Portugal, Romania, Russia, Saudi Arabia, South Africa, Spain, Sweden, Texas Ukraine and the United Kingdom) are provided as a supplementary material along with results from all countires in the world (S1 and S2, respectively).

Statistical software

All models were run in R\cite{team2020r} and the packages readxl\cite{wickham2019package}, ggplot2\cite{wickham2011ggplot2}, cowplot\cite{wilke2019package} and readr\cite{wickham2015package} were used.