Forecasting the Worldwide Spread of COVID-19 based on Logistic Model and SEIR Model
Zhou, X., Hong, N., Ma, Y., He, J., Jiang, H., Liu, C., ... & Long, Y. (preprint), medRxiv.
Background: As the outbreak of coronavirus disease 2019 (COVID-19), a sudden case increase in late February 2020 in global attracted deep concern. Italy, South Korea, Iran, France, Germany, Spain, the U.S. and Japan are probable the most severe countries. Collecting epidemiological data and predicting epidemic trends are important to develop and measure public intervention strategies. Epidemic predictions results yield by different mathematical models are out of line, therefore, we sought to compare different models and their prediction results, so as to generate objective conclusions.
Methods: We used the number of cases reported from January 23 to March 20, 2020 to estimate possible spread size and peak time of COVID-19, especially in 8 high risk countries. Logistic growth model, basic SEIR model and adjusted SEIR model were adopted for predicting. Considering different model inputs may infer different model outputs, we implemented three model predictions with three scenarios of epidemic development.
Results: When contrasting all 8 countries short-term prediction results and peak predictions, the difference between the models was relatively large. The logistic growth model estimated a smaller epidemic size than the basic SERI model, however, once we added parameters which considered the effects of public health interventions and control measures, the adjusted SERI model results demonstrated a considerably rapid decelerate of the epidemic development. Our results demonstrated contact rate, quarantine scale, quarantine initiate time and length are important factors to control the epidemic size and length.
Conclusions: We demonstrated a comparative assessment of the predictions of COVID-19 outbreak of 8 high risk countries using multiple methods. By forecasting epidemic size and peak time as well as simulating the effects of public health interventions, the intent of this paper is to help understand the transmission dynamics of COVID-19 and recommend operation suggestions to slow down the epidemic. It is suggested that quickly detecting cases, enough quarantine implementation and public self-protection behaviors are critical to slow down the epidemic.
**Disclaimer: this paper is so new it has not been peer-reviewed yet**