Prediction of infectious diseases based on an improved SEIR model: Taking COVID-19 as an example
Infectious diseases are not new to our daily lives, and humans have a long history of fighting infectious diseases. On December 31, 2019, the outbreak of the new coronavirus pneumonia (COVID-19) on a global scale, from the beginning of the outbreak to the end of the outbreak of the epidemic has caused irreparable losses to the safety of people's lives and property all over the world, although now the new crown virus has quietly disappeared from people's lives, but we do not know when other similar infectious viruses will appear, when we face other unknown infectious viruses, how we should predict their development trend is particularly important work at this stage. Therefore, this paper takes the outbreak of the new coronavirus in Indiana, USA from March 6 to April 7, 2022 as an example, and proposes an improved SSqEEqIQRD model on the basis of the traditional SEIR model, and the prediction results show that the improved SSqEEqIQRD model is better than the traditional SEIR model, this also provides important reference value for predicting similar infectious viruses that may occur in the future.
Authors
- Lujie Li
Publication Details
- Published
- 2025-03-21
- DOI
- https://doi.org/10.1145/3745533.3745591
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00