A swarm-optimizer-assisted simulation and prediction model for emerging infectious diseases based on SEIR.
Complex Intell Systems
; : 1-16, 2022 Nov 16.
Article
in English
| MEDLINE | ID: covidwho-2122101
ABSTRACT
Mechanism-driven models based on transmission dynamics and statistic models driven by public health data are two main methods for simulating and predicting emerging infectious diseases. In this paper, we intend to combine these two methods to develop a more comprehensive model for the simulation and prediction of emerging infectious diseases. First, we combine a standard epidemic dynamic, the susceptible-exposed-infected-recovered (SEIR) model with population migration. This model can provide a biological spread process for emerging infectious diseases. Second, to determine suitable parameters for the model, we propose a data-driven approach, in which the public health data and population migration data are assembled. Moreover, an objective function is defined to minimize the error based on these data. Third, based on the proposed model, we further develop a swarm-optimizer-assisted simulation and prediction method, which contains two modules. In the first module, we use a level-based learning swarm optimizer to optimize the parameters required in the epidemic mechanism. In the second module, the optimized parameters are used to predicate the spread of emerging infectious diseases. Finally, various experiments are conducted to validate the effectiveness of the proposed model and method.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Type of study:
Prognostic study
Language:
English
Journal:
Complex Intell Systems
Year:
2022
Document Type:
Article
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