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Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia

COVID-19 has struck the world with multiple waves. Each wave was caused by a variant and presented different peaks and baselines. This made the identification of waves with the time series of the cases a difficult task. Human activity intensities may affect the occurrence of an outbreak. We demonstr...

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Autores principales: Chin, Wei Chien Benny, Chan, Chun-Hsiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967257/
https://www.ncbi.nlm.nih.gov/pubmed/36828488
http://dx.doi.org/10.3390/tropicalmed8020072
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author Chin, Wei Chien Benny
Chan, Chun-Hsiang
author_facet Chin, Wei Chien Benny
Chan, Chun-Hsiang
author_sort Chin, Wei Chien Benny
collection PubMed
description COVID-19 has struck the world with multiple waves. Each wave was caused by a variant and presented different peaks and baselines. This made the identification of waves with the time series of the cases a difficult task. Human activity intensities may affect the occurrence of an outbreak. We demonstrated a metric of time series, namely log-moving-average-ratio (LMAR), to identify the waves and directions of the changes in the disease cases and check-ins (MySejahtera). Based on the detected waves and changes, we explore the relationship between the two. Using the stimulus-organism-response model with our results, we presented a four-stage model: (1) government-imposed movement restrictions, (2) revenge travel, (3) self-imposed movement reduction, and (4) the new normal. The inverse patterns between check-ins and pandemic waves suggested that the self-imposed movement reduction would naturally happen and would be sufficient for a smaller epidemic wave. People may spontaneously be aware of the severity of epidemic situations and take appropriate disease prevention measures to reduce the risks of exposure and infection. In summary, LMAR is more sensitive to the waves and could be adopted to characterize the association between travel willingness and confirmed disease cases.
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spelling pubmed-99672572023-02-26 Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia Chin, Wei Chien Benny Chan, Chun-Hsiang Trop Med Infect Dis Article COVID-19 has struck the world with multiple waves. Each wave was caused by a variant and presented different peaks and baselines. This made the identification of waves with the time series of the cases a difficult task. Human activity intensities may affect the occurrence of an outbreak. We demonstrated a metric of time series, namely log-moving-average-ratio (LMAR), to identify the waves and directions of the changes in the disease cases and check-ins (MySejahtera). Based on the detected waves and changes, we explore the relationship between the two. Using the stimulus-organism-response model with our results, we presented a four-stage model: (1) government-imposed movement restrictions, (2) revenge travel, (3) self-imposed movement reduction, and (4) the new normal. The inverse patterns between check-ins and pandemic waves suggested that the self-imposed movement reduction would naturally happen and would be sufficient for a smaller epidemic wave. People may spontaneously be aware of the severity of epidemic situations and take appropriate disease prevention measures to reduce the risks of exposure and infection. In summary, LMAR is more sensitive to the waves and could be adopted to characterize the association between travel willingness and confirmed disease cases. MDPI 2023-01-19 /pmc/articles/PMC9967257/ /pubmed/36828488 http://dx.doi.org/10.3390/tropicalmed8020072 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chin, Wei Chien Benny
Chan, Chun-Hsiang
Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia
title Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia
title_full Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia
title_fullStr Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia
title_full_unstemmed Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia
title_short Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia
title_sort analyzing the trends of covid-19 and human activity intensity in malaysia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967257/
https://www.ncbi.nlm.nih.gov/pubmed/36828488
http://dx.doi.org/10.3390/tropicalmed8020072
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