Forecasting the Worldwide Spread of COVID-19 based on Logistic Model and SEIR Model

Xiang Zhou; Na Hong; Yingying Ma; Jie He; Huizhen Jiang; Chun Liu; Guangliang Shan; Longxiang Su; Weiguo Zhu; Yun Long

The study has some limitations. The mathematical models allow for the quick incorporation of multiple inputs to yield prediction results. However, this process involves making assumptions about uncertain factors; for example, it is difficult to determine the exact extent to which people follow the local government's quarantine policies or measures and engage in behaviors such as washing hands, using masks, and social distancing. This may affect the actual contact rate and the subsequent development of the epidemic. The models also lack enough data to estimate the quarantine proportions of a certain population. In fact, the evolution of the epidemic is quite . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity.