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Predictive models on COVID 19: What Africans should do?

Habte Tadesse Likassa1, Wen Xain2, Xuan Tang2

  • 1Departement of Statistics, College of Natural and Computational Sciences, Addis Ababa University, Ethiopia.

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A cubic model accurately predicts COVID-19 cases and deaths in Africa, revealing varying spatial and temporal patterns. Strict self-isolation and public health interventions are crucial for mitigation and managing the pandemic's growth.

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Area of Science:

  • Epidemiology
  • Mathematical Modeling
  • Public Health

Background:

  • The Corona virus 2019 (COVID-19) pandemic has presented significant challenges in Africa.
  • Understanding the spatial and temporal dynamics of COVID-19 is crucial for effective response.

Purpose of the Study:

  • To develop and evaluate predictive models for estimating COVID-19 confirmed cases and deaths in Africa.
  • To analyze the spatial and temporal patterns of the COVID-19 pandemic across the African continent.

Main Methods:

  • Proposed predictive models to estimate COVID-19 confirmed cases and deaths.
  • Evaluated model performance against six families of exponential functions.
  • Identified the cubic model as the best performing algorithm.

Main Results:

  • The spatial and temporal patterns of the COVID-19 pandemic vary significantly across Africa.
  • The cubic model demonstrated superior performance in predicting COVID-19 cases and deaths compared to other models.
  • The cubic algorithm proved more robust than existing state-of-the-art methods using World Health Organization data.

Conclusions:

  • The cubic model offers a robust tool for predicting COVID-19 trends in Africa.
  • Effective mitigation strategies include persistent, strict self-isolation and practical public health interventions.
  • Addressing the pandemic requires moving beyond theoretical planning to hands-on implementation of public health measures.