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

Cecilia Ajowho Adenusi (), Olufunke Rebecca Vincent (), Abiodun Folurera Ajayi () and Bukola Taibat Adebiyi ()
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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

Chapter Chapter 9 in Decision Sciences for COVID-19, 2022, pp 151-163 from Springer

Abstract: 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.

Keywords: COVID-19; Africa; WHO; Facebook Prophet; Polynomial Regression; SIR; Prediction; Diseases (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-030-87019-5_9

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DOI: 10.1007/978-3-030-87019-5_9

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