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: , where 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.
- disease management
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YL and ML contributed equally.
Contributors YW conceived the idea and wrote the source code. YW, YL, ML, and LJ contributed to the data analysis, generating of tables and figures, and manuscript writing. YL, ML, XY, XL, MH, ZH, YW, and LJ contributed to the theoretical analysis and manuscript revision. All authors contributed to the final revision of the manuscript.
Funding Data in this study are publicly available and were downloaded from the WHO Website. Our research was supported by the Postdoctoral Science Foundation of China (2018M640333) and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01).
Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement All data relevant to the study are included in the article or uploaded as supplementary information. The source code of the model is available at https://github.com/wangyi-fudan/COVID-19_Global_Model.
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