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Mathematical model describing CoViD-19 in São Paulo, Brazil - evaluating isolation as control mechanism and

H M Yang1, L P Lombardi Junior1, F F M Castro2

  • 1Department of Applied Mathematics, State University of Campinas, General Hospital of the Medicine School of University of São Paulo, Campinas, Brazil.

Epidemiology and Infection
|July 21, 2020
PubMed

Insights

Mathematical modeling of COVID-19 in São Paulo suggests that delaying the release of isolated individuals, particularly the elderly, is crucial. Higher isolation rates could have prevented healthcare system collapse.

Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health

Background:

  • The first COVID-19 case in São Paulo was confirmed on February 26, 2020, with the first death on March 16.
  • São Paulo implemented non-essential activity isolation on March 24, 2020.
  • Understanding the dynamics of coronavirus disease 2019 (CoViD-19) spread is critical for public health interventions.

Purpose of the Study:

  • To develop a mathematical model simulating COVID-19 spread in São Paulo, considering age-stratified subpopulations.
  • To estimate the basic reproduction number (R0) and assess the effectiveness of implemented isolation measures.
  • To evaluate different release strategies for isolated populations and their impact on healthcare system burden.

Main Methods:

  • Formulation of a deterministic mathematical model using non-linear ordinary differential equations.
  • Inclusion of two subpopulations: young (≤60 years) and elder (>60 years).
  • Parameter estimation using São Paulo's epidemiological data to simulate COVID-19 dissemination.

Main Results:

  • The estimated basic reproduction number (R0) was 6.8.
  • The model estimated that 50% of São Paulo's population was in isolation.
  • Achieving 80% isolation could have prevented healthcare system collapse; however, all release strategies studied did not substantially reduce severe COVID-19 hospitalizations.

Conclusions:

  • The initial isolation strategy in São Paulo was only partially successful in controlling the epidemic.
  • Releasing young individuals while keeping the elderly isolated longer showed better outcomes among release strategies.
  • Postponing the start of releasing isolated individuals is the recommended strategy to mitigate severe COVID-19 hospitalizations.

Keywords:
Epidemiological scenariosnew coronavirusnumerical simulationspulses of releaseunique pulse of isolation/quarantine

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