authorea Authorea 10.22541/au.161918947.77588494/v2 The Epidemic Volatility Index: an early warning tool for epidemics 0000-0001-7051-1541 Kostoulas Polychronis
Faculty of Public Health, University of Thessaly, Greece.
0000-0003-2862-7182 Meletis Eletherios
Faculty of Public Health, University of Thessaly, Greece.
0000-0002-6005-9798 Pateras Konstantinos
Faculty of Public Health, University of Thessaly, Greece.
0000-0002-0715-6396 Eusebi Paolo
Department of Medicine and Surgery, University of Perugia.
0000-0003-2201-6938 Kostoulas Theodoros
Department of Information and Communication Systems Engineering, University of the Aegean, Greece
0000-0003-3322-3502 Speybroeck Niko
Research Institute of Health and Society (IRSS), Université Catholique de Louvain, 1200, Brussels, Belgium.
0000-0001-5212-4273 Denwood Matthew
Department of Veterinary and Animal Sciences, University of Copenhagen, Denmark
Doi Suhail A.R.
Department of Population Medicine, College of Medicine, QU Health, Qatar University, Doha, Qatar.
0000-0002-5230-6760 Althaus Christian L.
Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
Kirkeby Carsten
Department of Veterinary and Animal Sciences, University of Copenhagen, Denmark
Rohani Pejman
Center for the Ecology of Infectious Diseases, University of Georgia, Athens, GA 30602, USA.
0000-0002-4362-3596 Dhand Navneet K.
Sydney School of Veterinary Science, The University of Sydney, Camden, NSW, Australia.
Peñalvo José L.
Unit of Noncommunicable Diseases, Department of Public Health, Institute of Tropical Medicine, Antwerp, Belgium.
Furuya-Kanamori Luis
UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Herston, Australia.
Thabane Lehana
Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton ON, Canada.
BenMiled Slimane
Pasteur Institute, University of Tunis el Manar, Tunis, Tunisia.
0000-0002-9008-7618 Sharifi Hamid
HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Walter Stephen
Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton ON, Canada.
29 5 2021 This preprint is available at https://doi.org/10.22541/au.161918947.77588494/v2

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.

 covid-19 early warning epidemic