Informed Random Forest to Model Associations of Epidemiological Priors, Government Policies, and Public Mobility
Tsaone Swaabow Thapelo,
Dimane Mpoeleng,
Gregory Hillhouse
Abstract:Background. Infectious diseases constitute a significant concern worldwide due to their increasing prevalence, associated health risks, and the socioeconomic costs. Machine learning (ML) models and epidemic models formulated using deterministic differential equations are the most dominant tools for analyzing and modeling the transmission of infectious diseases. However, ML models can be inconsistent in extracting the dynamics of a disease in the presence of data drifts. Likewise, the capability of epidemic mod… Show more
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