Overall Accuracy and Predictive Values
It is possible, at each time point t, to calculate the positive and negative predictive values, defined as the probability of observing a rise or drop in the future number of cases, given that an early warning was issued or not, respectively. Finally, once the entire time series data has been observed the overall SeEVI and SpEVI can be estimated.
Sensitivity analysis
The accuracy of EVI depends on the specified case definition. Ideally, in the presence of historical data, various case definitions should be explored to identify which are suitable for the optimal monitoring of an epidemic.
Example application
The current most serious threat to global health and economy
\cite{Fauci_2020} is the COVID-19 pandemic that begun in China and was first reported to the WHO China Country Office on December 31, 2019
\cite{world2020pneumonia}. Data on the confirmed cases of COVID-19 were retrieved from 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. Due to unnatural variability in the reported cases between working days and weekends, the 7-day moving average rather than the actual observed cases were analyzed. For the analysis,
\(m_{max}\) was restricted to 30 days in order to avoid the effect of potentially higher volatility from previous epidemic waves on the volatility estimates of the most recent data and the predictive ability of EVI for upcoming and perhaps milder epidemic waves.