A new method for spatio-temporal transmission prediction of COVID-19.

ABSTRACT: COVID-19 is the most serious public health event of the 21st century and has had a huge impact across the world. The spatio-temporal pattern analysis and simulation of epidemic spread have become the focus of current research. LSTM model has made a lot of achievements in the prediction of infectious diseases by virtue of its advantages in time prediction, but lacks the spatial expression. CA model plays an important role in epidemic spatial propagation modeling due to its unique evolution characteristics from local to global. However, no existing studies of CA have considered long-term dependence due to the impact of time changes on the evolution of the epidemic, and few have modeled using location data from actual diagnosed patients. Therefore, we proposed a LSTM-CA model to solve above m

SUBMITTER: Wang P 

PROVIDER: S-EPMC9792945 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature