PreprintShort NoteVersion 1Preserved in Portico This version is not peer-reviewed
The Ongoing COVID-19 Epidemic Curves Indicate Initial Point Spread in China with Log-Normal Distribution of New Cases Per Day with a Predictable Last Date of the Outbreak
Version 1
: Received: 4 March 2020 / Approved: 5 March 2020 / Online: 5 March 2020 (02:58:51 CET)
Version 2
: Received: 11 March 2020 / Approved: 12 March 2020 / Online: 12 March 2020 (05:04:52 CET)
Version 3
: Received: 25 March 2020 / Approved: 27 March 2020 / Online: 27 March 2020 (02:22:11 CET)
Version 4
: Received: 16 April 2020 / Approved: 19 April 2020 / Online: 19 April 2020 (08:15:10 CEST)
How to cite:
Olsson, S. The Ongoing COVID-19 Epidemic Curves Indicate Initial Point Spread in China with Log-Normal Distribution of New Cases Per Day with a Predictable Last Date of the Outbreak. Preprints2020, 2020030077. https://doi.org/10.20944/preprints202003.0077.v1
Olsson, S. The Ongoing COVID-19 Epidemic Curves Indicate Initial Point Spread in China with Log-Normal Distribution of New Cases Per Day with a Predictable Last Date of the Outbreak. Preprints 2020, 2020030077. https://doi.org/10.20944/preprints202003.0077.v1
Olsson, S. The Ongoing COVID-19 Epidemic Curves Indicate Initial Point Spread in China with Log-Normal Distribution of New Cases Per Day with a Predictable Last Date of the Outbreak. Preprints2020, 2020030077. https://doi.org/10.20944/preprints202003.0077.v1
APA Style
Olsson, S. (2020). The Ongoing COVID-19 Epidemic Curves Indicate Initial Point Spread in China with Log-Normal Distribution of New Cases Per Day with a Predictable Last Date of the Outbreak. Preprints. https://doi.org/10.20944/preprints202003.0077.v1
Chicago/Turabian Style
Olsson, S. 2020 "The Ongoing COVID-19 Epidemic Curves Indicate Initial Point Spread in China with Log-Normal Distribution of New Cases Per Day with a Predictable Last Date of the Outbreak" Preprints. https://doi.org/10.20944/preprints202003.0077.v1
Abstract
During an epidemic outbreak it is useful for planners and responsible authorities to be able to plan ahead to estimate when an outbreak of an epidemic is likely to ease and when the last case can be predicted in their area of responsibility. Theoretically this could be done for a point source epidemic using epidemic curve forecasting. The extensive data now coming out of China makes it possible to test if this can be done using MS Excel a standard spreadsheet program available to most offices. The available data is divided up for whole China and the different provinces. This and the high number of cases makes the analysis possible. Data for new confirmed infections for Hubei, Hubei outside Wuhan, China excluding Hubei as well as Zhejiang and Fujian provinces all follow a log-normal distribution that can be used to make a rough estimate for the date of the last new confirmed cases in respective areas.
Keywords
epidemiology; COVID-19
Subject
Biology and Life Sciences, Virology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received:
23 April 2020
Commenter:
Pier Franco Nali
The commenter has declared there is no conflict of interests.
Comment:
I made a very similar model of the new cases per day and the accumulated cases on Italy data. If you are interested you may take a look on https://github.com/pfnali/Covid-19. I noticed that your model uses the base 10 logarithm (Excel LOG function) while the lognomal distribution is defined using the natural logarithm (Excel LOGNORM.DIST standard function). Even if this does not affect the correctness of your model, it gives rise to a difference if one uses the standard Excel distribution on your data. I suggest you should put a notice on this particular point in your paper or you can directly use in the spreadsheet the LN function in place of LOG.
Best regards,
Pier Franco Nali
former Executive at Regione Sardegna, Italy
pfnali@alice.it
Received:
22 May 2020
Commenter:
Kerry Litvin
The commenter has declared there is no conflict of interests.
Comment:
I have been modeling the daily positive case data for New York City, and Philadelphia. I have also found that the COVID19 epidemic in both cities are following log-normal statistics as well. I am not very familiar with epidemiology so I would like to know the theoretical foundations which would dictate that the disease spread should follow log-normal statistics. New York City, in particular, is very closely following a log-normal PDF for the daily new case rate and a log normal CDF for the accumulated total number of positive cases. I currently have the asymptotic total number of cases for NYC at about 203000. Thank you. I'm looking forward to your comments.
Commenter: Pier Franco Nali
The commenter has declared there is no conflict of interests.
Best regards,
Pier Franco Nali
former Executive at Regione Sardegna, Italy
pfnali@alice.it
Commenter: Kerry Litvin
The commenter has declared there is no conflict of interests.