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Predicting the Spread of COVID-19 in Africa Using Facebook Prophet and Polynomial Regression

In: Decision Sciences for COVID-19

Author

Listed:
  • Cecilia Ajowho Adenusi

    (Linux Professional Institute, Nigeria Master Affiliate, UI)

  • Olufunke Rebecca Vincent

    (Federal University of Agriculture)

  • Abiodun Folurera Ajayi

    (Federal University of Agriculture)

  • Bukola Taibat Adebiyi

    (Federal University of Agriculture)

Abstract

The COVID-19 pandemic is a noisy disease and a deadly one that has got the whole world’s attention. This deadly disease led to the whole world’s total lockdown for months before necessary measures were put in place for those who could not go out. Measures like regular hand washing, sanitizer, nose or face covering, social distances, and the like. This pandemic was first discovered in China and later in other parts of the world too. This study looked into the spread of COVID-19 in Africa using the US COVID-19 dataset, where data was extracted for analysis and prediction using Polynomial Regression. The results were further compared using a Facebook prophet. But at the end of the prediction, polynomial regression has the lowest Relative Mean Absolute Error (RMSE), which is now the model used for predicting the spread of COVID-19 in Africa.

Suggested Citation

  • Cecilia Ajowho Adenusi & Olufunke Rebecca Vincent & Abiodun Folurera Ajayi & Bukola Taibat Adebiyi, 2022. "Predicting the Spread of COVID-19 in Africa Using Facebook Prophet and Polynomial Regression," International Series in Operations Research & Management Science, in: Said Ali Hassan & Ali Wagdy Mohamed & Khalid Abdulaziz Alnowibet (ed.), Decision Sciences for COVID-19, chapter 0, pages 151-163, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-87019-5_9
    DOI: 10.1007/978-3-030-87019-5_9
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