Occurrence and Associated Risk Factors of Porcine Reproductive and Respiratory Syndrome Virus and Porcine Circovirus Type 2 Infections in Greece.

The objective of the present study was to identify factors associated with the probability of being polymerase chain reaction (PCR) positive and the level of porcine reproductive and respiratory syndrome virus (PRRSV), porcine circovirus type 2 (PCV2) occurrence in Greek farms. The study included 56 pig farms, with a total population of 22.500 sows, which represent about 40% of the entire capacity of the Greek swine production. A total of 896 blood samples (224 pools*4 samples/pool = 896 samples) from breeding stock, weaners, growers, and finishers were collected from each farm and organized in pools of 4 samples size. Further, data regarding herd health management protocols were collected. The sera were tested for PRRSV and PCV2, using real-time PCR (RT-PCR). The results indicated that both viruses remain a major challenge for the Greek swine industry. Main risk factors involved in the infection process by these viruses were identified. In particular, vaccination programs such as the mass PRRSV vaccination with modified-live virus (MLV) in breeding stock during the last stages of gestation or with killed-virus (KV) during the middle of gestation are more likely to be associated with PRRSV PCR-positivity. Farms with low biosecurity level are associated with higher PRRSV circulation. It has also been revealed that breeding stock is more likely to be associated with PCV2 circulation compared to weaners and growers. In 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.

The epidemic volatility index, a novel early warning tool for identifying new waves in an epidemic.

Early warning tools are crucial for the timely application of intervention strategies and the mitigation of the adverse health, social and economic effects associated with outbreaks of epidemic potential such as COVID-19. This paper introduces, the Epidemic Volatility Index (EVI), a new, conceptually simple, early warning tool for oncoming epidemic waves. EVI is based on the volatility of newly reported cases per unit of time, ideally per day, and issues an early warning when the volatility change rate exceeds a threshold. Data on the daily confirmed cases of COVID-19 are used to demonstrate the use of EVI. Results from the COVID-19 epidemic in Italy and New York State are presented here, based on the number of confirmed cases of COVID-19, from January 22, 2020, until April 13, 2021. Live daily updated predictions for all world countries and each of the United States of America are publicly available online. For Italy, the overall sensitivity for EVI was 0.82 (95% Confidence Intervals: 0.75; 0.89) and the specificity was 0.91 (0.88; 0.94). For New York, the corresponding values were 0.55 (0.47; 0.64) and 0.88 (0.84; 0.91). Consecutive issuance of early warnings is a strong indicator of main epidemic waves in any country or state. EVI's application to data from the current COVID-19 pandemic revealed a consistent and stable performance in terms of detecting new 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 swiftly and thereby enhance containment of outbreaks.