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Forecasting the rate of cumulative cases of COVID-19 infection in Northeast Brazil: a Boltzmann function-based

Géssyca Cavalcante de Melo1,2, Renato Américo de Araújo Neto3, Karina Conceição Gomes Machado de Araújo2

  • 1Universidade Estadual de Ciências da Saúde de Alagoas, Maceió, Brasil.

Cadernos De Saude Publica
|July 2, 2020
PubMed

Insights

Northeast Brazil faces a high COVID-19 death rate. This study forecasts a substantial increase in cumulative cases by July 31, especially in Ceará, Sergipe, and Paraíba, necessitating urgent public health planning.

Area of Science:

  • Epidemiology
  • Public Health
  • Mathematical Modeling

Background:

  • Northeast Brazil exhibits a significantly higher COVID-19 death rate than the national average.
  • This necessitates regional prognosis for effective control measures and healthcare system preservation.

Purpose of the Study:

  • To estimate the potential cumulative cases of COVID-19 in Northeast Brazil over the subsequent three months.
  • To inform public health strategies and prevent healthcare system collapse.

Main Methods:

  • Utilized confirmed COVID-19 case data from March 8 to April 28, 2020, sourced from Brazil's official reporting website.
  • Applied the Boltzmann function for data simulation and forecasting across different states.
  • Achieved high model fit with R² values near 0.999.

Main Results:

  • As of April 28, 20,665 COVID-19 cases were confirmed in the region.
  • Ceará reported the highest accumulated cases per 100,000 inhabitants (75.75), followed by Pernambuco.
  • Forecasts indicate a dramatic increase in cumulative cases by July 31 for Ceará, Sergipe, and Paraíba.

Conclusions:

  • A substantial rise in COVID-19 cases per 100,000 inhabitants is projected for Northeast Brazil within three months.
  • The Boltzmann function is an effective tool for epidemiological forecasting to guide public health interventions.
  • Proactive planning is crucial to manage the escalating COVID-19 situation in the region.

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