A Machine Learning Evaluation of the Effects of South Africa’s COVID-19 Lockdown Measures on Population Mobility

Following the declaration by the World Health Organisation (WHO) on 11 March 2020, that the global COVID-19 outbreak had become a pandemic, South Africa implemented a full lockdown from 27 March 2020 for 21 days. The full lockdown was implemented after the publication of the National Disaster Regula...

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Main Authors: Albert Whata, Charles Chimedza
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Machine Learning and Knowledge Extraction
Subjects:
Online Access:https://www.mdpi.com/2504-4990/3/2/25
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author Albert Whata
Charles Chimedza
author_facet Albert Whata
Charles Chimedza
author_sort Albert Whata
collection DOAJ
description Following the declaration by the World Health Organisation (WHO) on 11 March 2020, that the global COVID-19 outbreak had become a pandemic, South Africa implemented a full lockdown from 27 March 2020 for 21 days. The full lockdown was implemented after the publication of the National Disaster Regulations (NDR) gazette on 18 March 2020. The regulations included lockdowns, public health measures, movement restrictions, social distancing measures, and social and economic measures. We developed a hybrid model that consists of a long-short term memory auto-encoder (LSTMAE) and the kernel quantile estimator (KQE) algorithm to detect change-points. Thereafter, we utilised the Bayesian structural times series models (BSTSMs) to estimate the causal effect of the lockdown measures. The LSTMAE and KQE, successfully detected the changepoint that resulted from the full lockdown that was imposed on 27 March 2020. Additionally, we quantified the causal effect of the full lockdown measure on population mobility in residential places, workplaces, transit stations, parks, grocery and pharmacy, and retail and recreation. In relative terms, population mobility at grocery and pharmacy places decreased significantly by −17,137.04% (<i>p</i>-value = 0.001 < 0.05). In relative terms, population mobility at transit stations, retail and recreation, workplaces, parks, and residential places decreased significantly by −998.59% (<i>p</i>-value = 0.001 < 0.05), −1277.36% (<i>p</i>-value = 0.001 < 0.05), −2175.86% (<i>p</i>-value = 0.001 < 0.05), −370.00% (<i>p</i>-value = 0.001< 0.05), and −22.73% (<i>p</i>-value = 0.001 < 0.05), respectively. Therefore, the full lockdown Level 5 imposed on March 27, 2020 had a causal effect on population mobility in these categories of places.
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spelling doaj.art-8836922a7b934f72a282b31219c84cdf2023-11-21T22:21:54ZengMDPI AGMachine Learning and Knowledge Extraction2504-49902021-06-013248150610.3390/make3020025A Machine Learning Evaluation of the Effects of South Africa’s COVID-19 Lockdown Measures on Population MobilityAlbert Whata0Charles Chimedza1School of Natural and Applied Sciences, Sol Plaatje University, Kimberley 8301, South AfricaSchool of Statistics and Actuarial Science, University of the Witwatersrand, Johannesburg 2050, South AfricaFollowing the declaration by the World Health Organisation (WHO) on 11 March 2020, that the global COVID-19 outbreak had become a pandemic, South Africa implemented a full lockdown from 27 March 2020 for 21 days. The full lockdown was implemented after the publication of the National Disaster Regulations (NDR) gazette on 18 March 2020. The regulations included lockdowns, public health measures, movement restrictions, social distancing measures, and social and economic measures. We developed a hybrid model that consists of a long-short term memory auto-encoder (LSTMAE) and the kernel quantile estimator (KQE) algorithm to detect change-points. Thereafter, we utilised the Bayesian structural times series models (BSTSMs) to estimate the causal effect of the lockdown measures. The LSTMAE and KQE, successfully detected the changepoint that resulted from the full lockdown that was imposed on 27 March 2020. Additionally, we quantified the causal effect of the full lockdown measure on population mobility in residential places, workplaces, transit stations, parks, grocery and pharmacy, and retail and recreation. In relative terms, population mobility at grocery and pharmacy places decreased significantly by −17,137.04% (<i>p</i>-value = 0.001 < 0.05). In relative terms, population mobility at transit stations, retail and recreation, workplaces, parks, and residential places decreased significantly by −998.59% (<i>p</i>-value = 0.001 < 0.05), −1277.36% (<i>p</i>-value = 0.001 < 0.05), −2175.86% (<i>p</i>-value = 0.001 < 0.05), −370.00% (<i>p</i>-value = 0.001< 0.05), and −22.73% (<i>p</i>-value = 0.001 < 0.05), respectively. Therefore, the full lockdown Level 5 imposed on March 27, 2020 had a causal effect on population mobility in these categories of places.https://www.mdpi.com/2504-4990/3/2/25causal effectencoder–decoderkernel quantile estimatorlong-short term memorypopulation mobilityreconstruction error
spellingShingle Albert Whata
Charles Chimedza
A Machine Learning Evaluation of the Effects of South Africa’s COVID-19 Lockdown Measures on Population Mobility
Machine Learning and Knowledge Extraction
causal effect
encoder–decoder
kernel quantile estimator
long-short term memory
population mobility
reconstruction error
title A Machine Learning Evaluation of the Effects of South Africa’s COVID-19 Lockdown Measures on Population Mobility
title_full A Machine Learning Evaluation of the Effects of South Africa’s COVID-19 Lockdown Measures on Population Mobility
title_fullStr A Machine Learning Evaluation of the Effects of South Africa’s COVID-19 Lockdown Measures on Population Mobility
title_full_unstemmed A Machine Learning Evaluation of the Effects of South Africa’s COVID-19 Lockdown Measures on Population Mobility
title_short A Machine Learning Evaluation of the Effects of South Africa’s COVID-19 Lockdown Measures on Population Mobility
title_sort machine learning evaluation of the effects of south africa s covid 19 lockdown measures on population mobility
topic causal effect
encoder–decoder
kernel quantile estimator
long-short term memory
population mobility
reconstruction error
url https://www.mdpi.com/2504-4990/3/2/25
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