Background. This paper presents, for the first time, the Epidemic Volatility Index (EVI), a conceptually simple, early warning tool for emerging epidemic waves. Methods. EVI is based on the volatility of the newly reported cases per unit of time, ideally per day, and issues an early warning when the rate of the volatility change exceeds a threshold.Results. Results from the COVID-19 epidemic in Italy and New York are presented here, while daily updated predictions for all world countries and each of the United States are available online.Interpretation. EVI's application to data from the current COVID-19 pandemic revealed a consistent and stable performance in terms of detecting oncoming waves. The application of EVI to other epidemics and syndromic surveillance tasks in combination with existing early warning systems will enhance our ability to act fast and optimize containment of outbreaks.
The aim of the present study were to describe for first time the prevalence of porcine r porcine circovirus type-2 (PCV2) among pig farms. PIn conclusion, our results could be the basis of the development of surveillance protocols for a national monitoring system for PRRSV and PCV2, which could prevent future infection of Greek farms.