Pandemetrics: systematically assessing, monitoring, and controlling the evolution of a pandemic

Abstract

The still ongoing pandemic of SARS-CoV-2 virus and COVID-19 disease, affecting the population worldwide, has demonstrated the need of more accurate methodologies for assessing, monitoring, and controlling an outbreak of such devastating proportions. Authoritative attempts have been made in traditional fields of medicine (epidemiology, virology, infectiology) to address these shortcomings, mainly by relying on mathematical and statistical modeling. However, here, we propose approaching the methodological work from a different, and to some extent alternative, standpoint. Applied systematically, the concepts and tools of statistical engineering and quality management, developed not only in healthcare settings, but also in other scientific contexts, can be very useful in assessing, monitoring, and controlling pandemic events. We propose a methodology based on a set of tools and techniques, formulas, graphs, and tables to support the decision-making concerning the management of a pandemic like COVID-19. This methodological body is hereby named Pandemetrics. This name intends to emphasize the peculiarity of our approach to measuring, and graphically presenting the unique context of the COVID-19 pandemic.

Sequential monitoring of high‐dimensional time series

“…Statistical sequential procedures, especially control charts, are widely spread to detect changes in several fields of science. Applications in economics and finance can be found in Theodossiou (1993), Golosnoy and Schmid (2007), Bodnar (2009), Bodnar et al (2014), Bersimis et al (2018), while applications in medicine can be found in Shmueli and Burkom (2010), Schiöler and Frisén (2012), Meyer et al (2017), Barone and Chakhunashvili (2022). Anderson and Thompson (2004) applied multivariate control charts to detect changes in environmental processes, while Ye and Chen (2001) dealt with applications in network monitoring.…”