COVID-19 epidemic outside China: 34 founders and exponential growth.
J Investig Med
; 69(1): 52-55, 2021 01.
Article
in English
| MEDLINE | ID: covidwho-835516
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
COVID-19 raised tension both within China and internationally. Here, we used mathematical modeling to predict the trend of patient diagnosis outside China in future, with the aim of easing anxiety regarding the emergent situation. According to all diagnosis number from WHO website and combining with the transmission mode of infectious diseases, the mathematical model was fitted to predict future trend of outbreak. Daily diagnosis numbers from countries outside China were downloaded from WHO situation reports. The data used for this analysis were collected from January 21, 2020 and currently end at February 28, 2020. A simple regression model was developed based on these numbers, as follows [Formula see text], where [Formula see text] is the total diagnosed patient till the i-th day and t=1 at February 1, 2020. Based on this model, we estimate that there were approximately 34 undetected founder patients at the beginning of the spread of COVID-19 outside China. The global trend was approximately exponential, with an increase rate of 10-fold every 19 days. Through establishment of this model, we call for worldwide strong public health actions, with reference to the experiences learned from China and Singapore.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Global Health
/
Epidemics
/
COVID-19
Type of study:
Diagnostic study
/
Observational study
/
Prognostic study
/
Qualitative research
Limits:
Humans
Language:
English
Journal:
J Investig Med
Journal subject:
Medicine
Year:
2021
Document Type:
Article
Affiliation country:
Jim-2020-001491
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