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Does the introduction explain the objective of the research presented in the preprint?

Yes

The authors raise an important question in the field of public health. They further identify limitations in existing infectious disease models. They then propose addressing these gaps through real-world data analysis.

Are the methods well-suited for this research?

Highly appropriate

The authors combined three different modeling approaches to better capture real-world infectious disease outbreaks. Each approach presents a well-defined predictive framework that is supported by examples and code.

Are the conclusions supported by the data?

Highly supported

The article used recent data on COVID-19 cases, hospitalizations, and deaths to build the model. The authors also demonstrated the limitations of the approach. They also conducted analyses under different scenarios and quantified the uncertainty of the model.

Are the data presentations, including visualizations, well-suited to represent the data?

Highly appropriate and clear

How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research?

Very clearly

The article clearly described each stage of the model. In the discussion section, the authors emphasized collaboration with public health departments to refine the model and adapt it to evolving conditions.

Is the preprint likely to advance academic knowledge?

Highly likely

Would it benefit from language editing?

No

Would you recommend this preprint to others?

Yes, it’s of high quality

Is it ready for attention from an editor, publisher or broader audience?

Yes, as it is

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.