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Cluster analysis of epidemiological characteristic features of confirmed cases with the novel coronavirus (COVID-19) outside China: a descriptive study
Preprint
in English
| medRxiv
| ID: ppmedrxiv-20142000
ABSTRACT
BackgroundNovel coronavirus COVID-19 has caused significant global outbreaks outside China. Many countries have closed their borders with China and performed obligate protective procedures, however, this disease was still rising worldwide. In this report, we aim to identify transmission patterns from China to other countries, along with describing the disease control situation of countries. MethodsWe retrospectively collected information about infected cases with COVID-19 from WHO situation reports, official notification websites of health ministries and reliable local newspapers from each country. Descriptive and cluster analysis was performed to describe the transmission characteristics while the logistic regression test was used to estimate the risk factors for the occurrence of an infected individual with an unknown source. ResultsA total of 446 infected cases were recorded from 24 countries outside China until 12 February 2020, with the number of reported infected cases were doubled every 3.08 {+/-} 0.35 days (range from 2.6 to 3.9). Besides the spread from China, the transmission was originated from sub-endemic countries (Japan, Thailand, Singapore, Malaysia, France, German). Out of 6 countries got occurrence of an infected individual with unknown source and possible potential factors contributed to this occurrence was a time of epidemic circulating, number of patients and number of clusters when the occurrence still has not happened, and notably, the unreported situation of Chinese tourists information. ConclusionsThe situational reports of each country about COVID-19 should be more detailed mentioning the transmissions routes with keeping contact tracing of the unknown cases to increase the control of this disease.
cc_by_nc_nd
Full text:
Available
Collection:
Preprints
Database:
medRxiv
Type of study:
Observational study
/
Prognostic study
Language:
English
Year:
2020
Document type:
Preprint