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Challenge2020-Covid-19-Vaccination-Optimization

This notebook is related to a project participating in the IBM-Challenge 2020. See below for what problem this project is intended for.

Problem description:

When a vaccine for COVID-19 is ready, possibly it will not be available immediately in enough quantity to immunize everyone in every region.

Objective:

In a prescriptive analytic approach, this work proposes a linear programming model aimed to optimize a city vaccination campaign in a way to minimize the number of possible deaths in a scenario where just part of the vaccines arrives in certain regions. Here we are simulating such a scenario using São Paulo city hall data.

Outcome:

A dashboard was created (link below) using the results generated here. https://dataplatform.cloud.ibm.com/dashboards/7e0a7415-0514-4a82-838a-2f9e8949ff05/view/0768fc2738a832ff6dd7e6e4079d2a547937775bb2bb870280d07b490f317997f36d1a92c87a4f088c150d61faba475a9f

References:

https://www.prefeitura.sp.gov.br/cidade/secretarias/upload/saude/COVID19_Relatorio_SItuacional_SMS_20200529.pdf

https://www.prefeitura.sp.gov.br/cidade/secretarias/subprefeituras/subprefeituras/dados_demograficos/index.php?p=12758

https://www.cdc.gov/mmwr/volumes/69/wr/mm6912e2.htm?s_cid=mm6912e2_w#F1_down

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