Data and Code for: Optimal Targeted Lockdownsin a Multi-Group SIR Model

This is the code repository for "Optimal Targeted Lockdowns in a Multi-Group SIR Model", (AER Insights: Revision). <br><br>DATA <br><br>The fatality parameters used in computation are based on Ferguson, NM, D. Laydon, G. Nedjati-Gilani, N. Imai, K Ainslie, M. Baguelin, S. Bhatia, A. Boonyasiri, Z. Cucunubá, G. Cuomo-Dannenburg, and A. Dighe, “Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand,” March 2020. Imperial College COVID-19 Response Team. As commented in the paper, these parameters are in line with those from South Korea and the Diamond Princess cruise (see<b> </b>Acemoglu D., V. Chernozhukov, I. Werning, and M. D. Whinston, “A multi-risk SIR model with optimally targeted lockdown,” Technical Report, National Bureau of Eco- nomic Research 2020, for details and discussion). The latter data is not used in the paper.<br><br><br>COMPUTATIONAL CODE FILES. <br><br>The code files are the Python Notebooks: <br><br>Optimal3GPolicy-v6.ipynb produces Figures 3, 4, 5, A1, A3, A4, A5.2. <br>Optimal3G-SEIR-v6.ipynb produces Figures A6 an A8.3. <br>Optimal4GPolicy-OldWorking-v6.ipynb produces Figure A2.4. <br>Optimal3G-CustomContactMatrix.ipynb produces Figure A7. <br><br>The code is available under a Creative Commons Non-commercial license. <br><br>EXECUTION <br><br>We executed the files as follow: We have uploaded these notebooks to Google Colab Cloud https://colab.research.google.com/ and executed them online in the cloud.<br><br>To execute the code, the user can follow a similar approach. The user will need to modify the notebook cell that mounts the Google drive and supply her our own default paths for where to store computational output, figures: The path "/content/drive/My Drive/Covid/Lockdown/" has to be modified to user’s working folder. In that folder, the user must create the following subfolders: models/, figs/, summaryres/, results/. This is needed to make sure that the code executes properly. Alternatively, the code can be executed on a local machine with a local Python installation. <pre>REQUIREMENTS We used Google Colab Cloud https://colab.research.google.com/ with default runtime hardware setting to execute the notebooks. Execution via local installation will require Python 3.6.1 or higher and Gekko Optimization suite (ver 1.1.0; see https://gekko.readthedocs.io/en/latest/ ). </pre> <br>ALTERNATIVE SUGGESTED EXECUTION <br><br>The Python notebooks can be accessible online directly at: <br><br>https://colab.research.google.com/drive/16zhsso-NzNbxn9C_MMP4lqzdVA2N-xxt?usp=sharing https://colab.research.google.com/drive/1Ogi15qeU0vVm1eUq66c3B7M1nPiL-ZtE?usp=sharinghttps://colab.research.google.com/drive/15RYgCU6esEdOfOSA6LK7kRV5BZmQmVD3?usp=sharing https://colab.research.google.com/drive/1AvOOsR_3w-r0eciToP758dLkQRdSVm6H?usp=sharing <br><br>They can be cloned and executed directly in Google Colab Cloud.