Mathematical model of COVID-19 intervention scenarios for Sao Paulo- Brazil

TL;DR

This study uses a mathematical epidemiological model combined with genetic algorithms to identify effective COVID-19 intervention strategies in Sao Paulo, emphasizing sustained social distancing and increased personal protection over two years.

Contribution

It introduces an integrated modeling and optimization approach to determine optimal social distancing and protective behavior strategies for COVID-19 containment.

Findings

Maintaining or increasing social distancing for 60+ days is optimal.

Increasing personal protection by at least 10% is recommended.

A long-term oscillatory social distancing strategy is effective over two years.

Abstract

An epidemiological compartmental model was used to simulate social distancing strategies to contain the COVID-19 pandemic and prevent a second wave in Sao Paulo, Brazil. Optimization using genetic algorithm was used to determine the optimal solutions. Our results suggest the best-case strategy for Sao Paulo is to maintain or increase the current magnitude of social distancing for at least 60 more days and increase the current levels of personal protection behaviors by a minimum of 10% (e.g., wearing facemasks, proper hand hygiene and avoid agglomeration). Followed by a long-term oscillatory level of social distancing with a stepping-down approach every 80 days over a period of two years with continued protective behavior.