Literature DB >> 33023916

COVID-19 epidemic outside China: 34 founders and exponential growth.

Yi Li1,2, Meng Liang1, Xianhong Yin1, Xiaoyu Liu1, Meng Hao1, Zixin Hu1, Yi Wang3, Li Jin3,2,4.   

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. © American Federation for Medical Research 2021. Re-use permitted under CC BY-NC. No commercial re-use. Published by BMJ.

Entities:  

Keywords:  disease management

Year:  2020        PMID: 33023916     DOI: 10.1136/jim-2020-001491

Source DB:  PubMed          Journal:  J Investig Med        ISSN: 1081-5589            Impact factor:   2.895


  5 in total

1.  The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges.

Authors:  Amir Ahmad; Sunita Garhwal; Santosh Kumar Ray; Gagan Kumar; Sharaf Jameel Malebary; Omar Mohammed Barukab
Journal:  Arch Comput Methods Eng       Date:  2020-08-04       Impact factor: 7.302

2.  Mathematical modeling of coronavirus disease COVID-19 dynamics using CF and ABC non-singular fractional derivatives.

Authors:  Virender Singh Panwar; P S Sheik Uduman; J F Gómez-Aguilar
Journal:  Chaos Solitons Fractals       Date:  2021-02-04       Impact factor: 5.944

3.  A sustainable advanced artificial intelligence-based framework for analysis of COVID-19 spread.

Authors:  Misbah Ahmad; Imran Ahmed; Gwanggil Jeon
Journal:  Environ Dev Sustain       Date:  2022-08-16       Impact factor: 4.080

4.  Impact of COVID-19 on older adults and role of long-term care facilities during early stages of epidemic in Italy.

Authors:  Stefano Amore; Emanuela Puppo; Josué Melara; Elisa Terracciano; Susanna Gentili; Giuseppe Liotta
Journal:  Sci Rep       Date:  2021-06-15       Impact factor: 4.379

5.  Enabling Artificial Intelligence for Genome Sequence Analysis of COVID-19 and Alike Viruses.

Authors:  Imran Ahmed; Gwanggil Jeon
Journal:  Interdiscip Sci       Date:  2021-08-06       Impact factor: 3.492

  5 in total

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