Abstract
The crisis caused by 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, specifically their infection speed, death and fatality rates. By fitting distributions to these rates, we look for the effectiveness of government measures during the pandemic through a number of statistical approaches.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
M.C. Boado-Penas is grateful for the financial assistance received from the Spanish Ministry of the Economy and Competitiveness [project ECO2015-65826-P]. The research of J. Eisenberg was funded by the Austrian Science Fund (FWF), Project number V 603-N35.
Author Declarations
I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.
Yes
The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
Not relevant, as we have worked with public available data.
All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.
Yes
I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).
Yes
I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.
Yes
Data Availability
The R package, nCov2019, developed by Yu (202), provides direct access to real-time epidemiological data on the outbreak. Yu, G. (2020). nCov2019: An R package with real-time data, historical data and Shiny app.