Dr Giovanni Franzo

DVM, PhD. Msc

EBVS® European Specialist in Veterinary Microbiology

Born in Latisana (Italy) on December 09, 1987. September 2011, Degree in Veterinary Medicine with the final grade of 110/110 magna cum laude. March 2015, Defense of the PhD thesis entitled “Further insight into the molecular epidemiology and evolutionary dynamics of rapidly evolving RNA and ssDNA viruses”. November 2017: Achievement of a second-level master in “Biostatistics and Clinical Epidemiology”, at University of Pavia, defending a thesis entitled “Comparison and validation of different machine learning methods for the prediction of survival to Canine Parvovirus 2 infection”.Fellow researcher (January 2015-November 2017 ) and Researcher (since November 2017) at Dept. Animal Medicine, Production and Health (MAPS), University of Padua, Italy.
Visiting Scientist at MRC University of Glasgow. Centre for Virus Research; Institute of Infection, Immunity and Inflammation; College of Medical, Veterinary and Life Sciences(2014), INRA, UMR Interactions Hotes-Agents Pathogenes, Ecole Nationale Veterinaire, Tolulouse (2016) and RTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA- UAB), Campus de la Universitat Autònoma de Barcelona , 08193 Bellaterra, Barcelona, Spain (2017).
Member of the Italian Society of Avian Pathology (SIPA), Italian Society of Swine Pathology and Farming (SIPAS) and National Association of Veterinary Infectivologists (ANIV)
Associate Editor of Large Animal Review and Frontiers in Veterinary Sciences, guest editor of Pathogens and Veterinary sciences.
The research activities focus mainly on the study of viral evolution and molecular epidemiology using different bioinformatic, phylogenetic-based and biostatistics approaches. To date, my studies have focused mostly on rapidly evolving RNA and single-stranded DNA viruses affecting swine (PCV-2, PCV-3, PCV-4, PPV and PRRSV), poultry (aMPV, IBDV and IBV), companion (FPV, CPV-2) and wild animals (mainly AMV, CanineCV and PCVs) . I have also investigated the effect of these viruses remarkable heterogeneity on the control strategies (i.e. vaccination) efficacy and on the performances of molecular biology based diagnostic assays. Recently, I worked on the development of Machine Learning based models aimed to predict the disease outcome based on genetic data or clinical parameter analysis.
Author/co-author of more than 100 scientific manuscripts on peer-reviewed international journals