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An Integrated Economic Epidemiology Model Minimizing COVID-19 Burden of Disease and Economic Growth Trade-off

Abstract

We propose an integrated economic-epidemiological model that optimizes lockdown policies by balancing disease control and economic growth. Our model, calibrated using both epidemiological data and economic indicators, offers a more comprehensive approach to pandemic management for policymakers. Our study highlights the importance of interdisciplinary research in addressing complex global challenges like COVID-19 and sets the stage for future work in economic epidemiology.

Read the full paper at https://lequ02.github.io/cv_frbus/Research_Paper_cv_frbus.pdf

Quick manual

  1. Run cv_frbus.py to find the best policy. Save the best policy to a .csv file
  2. Run custom_cv_plot.py to get the COVID-19 Comparison plot
  3. Run ./pyfrbus/demos/sm_frbus.py to get the Economic Comparision plot

Acknowledgements:

The FRB/US package is downloaded from the Federal Reserve Board of the United States (https://www.federalreserve.gov/econres/us-models-python.htm)

The SIR-MACRO code is downloaded from https://github.com/bbardoczy/sir-macro.

Future developments can implement Fu et al. (https://doi.org/10.1016/j.frl.2021.102123) by modifying the code framework of the sir-macro package above to include how SAH orders will affect Aggregate Consumption and integrate that into the FRBUS model.

Additional files and Changes in these packages were made by the repository owner.

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