First Quarter Chronicle of COVID-19: An Attempt to Measure Governments’ Responses

Şule Şahin, María del Carmen Boado-Penas, Corina Constantinescu, Julia Eisenberg, Kira Henshaw, Maoqi Hu, Jing Wang and Wei Zhu
Additional contact information
Şule Şahin: Institute for Financial and Actuarial Mathematics, Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK
María del Carmen Boado-Penas: Institute for Financial and Actuarial Mathematics, Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK
Corina Constantinescu: Institute for Financial and Actuarial Mathematics, Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK
Julia Eisenberg: Financial & Actuarial Mathematics, TU Wien, Wiedner Hauptstr. 8/E105-1, 1040 Vienna, Austria
Maoqi Hu: Institute for Financial and Actuarial Mathematics, Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK
Jing Wang: Institute for Financial and Actuarial Mathematics, Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK
Wei Zhu: Institute for Financial and Actuarial Mathematics, Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK

Risks, 2020, vol. 8, issue 4, 1-26

Abstract: The crisis caused by the outbreak of COVID-19 revealed the global unpreparedness for handling the impact of a pandemic. In this paper, we present a first quarter chronicle of COVID-19 in Hubei China, Italy and Spain, particularly focusing on infection speed, death and fatality rates. By analysing the parameters of the best fitting distributions of the available data for the three rates in each of the three regions, we illustrate the pandemic’s evolution in relation to government measures. We compared the effectiveness of lockdown measures by observing the true situation in each dataset, without proposing a mathematical model. The feasibility of obtaining a firm conclusion in regard to the best solution for containing COVID-19 is limited, with a universal solution failing to exist due to globally varying culture, mentality and behaviours. Our method provides valid insights into the individual and national actions implemented and adhered to in order to slow the effect of the pandemic during the first-wave of COVID-19.

Keywords: epidemic; risk; distribution fitting (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-9091/8/4/115/pdf (application/pdf)
https://www.mdpi.com/2227-9091/8/4/115/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:8:y:2020:i:4:p:115-:d:439377

Access Statistics for this article

Risks is currently edited by Mr. Claude Zhang

More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().