Artificial Intelligence-Based Model for Predicting the Effect of Governments’ Measures on Community Mobility

Abstract

Mobility is considered one of the main reasons for the COVID-19 spread. Predicting the effect of control measures on mobility is essential to apply effective decisions. This work proposes an AI-based model for mobility changes prediction. The proposed CNN-LSTM with Autoregression has achieved the best results compared to other investigated models. Results show that the proposed model can predict the effect of precaution control measures on future community mobility with minimum loss. The mean absolute error over all countries in the study is 5.3. For Egypt and Saudi Arabia, the model achieved an MAE loss of 4.6 and 3.7 consecutively.

Keywords

• COVID-19
• Community mobility
• Time series prediction
• Autoregression
• Convolution neural network
• Long short-term memory network