ArticleScientific reports2021
The epidemic volatility index, a novel early warning tool for identifying new waves in an epidemic.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Implementation of AESOP early-warning system for respiratory disease: a pilot and validation study using routinely collected data in Amazonas, Brazil.Lancet regional health. Americas · 2026Article
- One health investigation following a cluster of Crimean-Congo haemorrhagic fever, North Macedonia, July to November 2023.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025Article
- Animal Health Discourse during Ecological Crises in the Media-Lessons Learnt from the Flood in Thessaly from the One Health Perspective.Veterinary sciences · 2024Article
- Early warning system using primary health care data in the post-COVID-19 pandemic era: Brazil nationwide case-study.Cadernos de saude publica · 2024Article
- Evaluation of Bayesian spatiotemporal infectious disease models for prospective surveillance analysis.BMC medical research methodology · 2023Article
- The convergence epidemic volatility index (cEVI) as an alternative early warning tool for identifying waves in an epidemic.Infectious Disease Modelling · 2023Article
- Simple methods for early warnings of COVID-19 surges: Lessons learned from 21 months of wastewater and clinical data collection in Detroit, Michigan, United States.The Science of the total environment · 2023Article
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18 authors.
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Abstract
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.
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