The Trend Distribution and Temporal Pattern Analysis of COVID-19 Pandemic using GIS framework in Malaysia

Yahya, Mohd Yamani; Safian, Edie Ezwan Mohd; Burhan, Burhaida

doi:10.21467/preprints.174

Cited by 4 publications

(4 citation statements)

References 10 publications

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“…First, the spread of COVID-19 occurs in a cluster shape in the Kermanshah metropolis [29,44]. The cluster formation indicates the unexpected occurrence of disease and the possibility of disease growth in the new centres that form in the future.…”

Section: Discussionmentioning

confidence: 97%

The Spatiality of COVID-19 in Kermanshah Metropolis, Iran

et al. 2022

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The COVID-19 pandemic is a severe ongoing health crisisworldwide. Studying the socio-economic impacts of COVID-19 can help policymakers develop successful pandemic management plans. This paper focuses on the spatial epidemiology of COVID-19 among different social classes in the Kermanshah metropolis, Iran. This cross-sectional study uses the data of people infected with COVID-19 in the Kermanshah metropolis in 2020, acquired from the official COVID-19 Registry of Kermanshah. The results show that 2013 people were infected with COVID-19 (male = 1164 and female = 849). The mean age of the patients was 45 ± 18.69. The Moran’s I show that COVID-19 in different social classes was clustered across the neighbourhoods in the Kermanshah metropolis. The mean ages of men and women were 44.51 ± 18.62 and 45.69 ± 18.76, respectively. Importantly, COVID-19 was highly prevalent in the middle-class groups. Age group comparisons indicate that older people were the most infected in poorer neighbourhoods. In the middle-classtheage group of 0–14 years and in the rich neighbourhoods the age group of 15–64 years were the most exposed to the disease. The findings of this study suggest that older people and lower socioeconomic classes should be prioritised while developing and implementing preventative programs for COVID-19 and similar pandemics.

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Section: Discussionmentioning

confidence: 97%

The Spatiality of COVID-19 in Kermanshah Metropolis, Iran

et al. 2022

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“…Furthermore, individuals whose ages range between (30-79) years are more exposed to the virus, especially when they have underlying health problems, such as cardiorespiratory diseases, diabetes, blood pressure, and cancer (Liu et al, 2020). Meanwhile, the age categories over 50 years are more exposed to death due to coronavirus as compared to the other categories (Yahya et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, the national geographic information system for combating the SARS pandemic as well as the early warning developed by the Chinese national center for combating and preventing diseases (China CDC) played an important role in managing, analyzing, and controlling severe acute respiratory syndrome (SARS). They were also used in drawing a spatial map for the areas affected by coronavirus in Malaysia in an attempt to detect the spatial patterns and temporal directions for the prevalence of the virus (Yahya et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The Temporal and Spatial Analysis of Corona Pandemic in Jordan using the Geographic Information System: An Applied Geographical Study

Taran

AlFanatseh

Rawashdeh

et al. 2023

IJG

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The coronavirus disease which results from severe acute respiratory syndrome (SARS-COV-2), is considered a global challenge affecting millions of people and leading to a global increase in mortality, including in Jordan. Therefore, this study aims to analyze the temporal and spatial patterns of the prevalence and outbreak of coronavirus in Jordan during six periods, from 1, October 2020 until 31, March 2021 by applying geographical information systems. The Moran coefficient was applied in addition to the G* test and location quotient (LQ). The results showed the overall pattern for the distribution of cases affected by the virus was random since most governorates' experience increased the focus and prevalence of the pandemic. Furthermore, four hot spots were revealed, namely Amman, Irbid, Zarqa, and Balqa'. This study introduced new insights into the statistical analysis of the distribution and prevalence of coronavirus in Jordan using geographical information systems. This will help planners and decision-makers to predict the dynamics of the temporal and spatial transfer of the virus in the future. It will also explain the current situation to set the appropriate policies or measures to face the pandemic, as well as reduce its prevalence. Therefore, monitoring, evaluating, and planning the usage of geospatial analysis are essential for controlling the spread of COVID-19 in the country.

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“…ESDA has also been conducted in Malaysia to analyse the spatial cluster of crime cases in Peninsular Malaysia [14]. Another study [20] provided a general view of COVID-19 based on trend distribution and temporal pattern analysis. However, no spatial statistical analysis was done.…”

Section: Introductionmentioning

confidence: 99%

Exploratory Spatial Data Analysis (Esda) on Covid-19 Cases in Malaysia

et al. 2021

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The Malaysian government implemented The Movement Control Order (MCO) on 18 March 2020 to control the spread of the COVID-19 outbreak. However, the third wave that started in September 2020 during the Recovery Movement Control Order (RMCO) phase saw a continuous increase in the number of cases. In this study, the exploratory spatial data analysis (ESDA) was used to analyse the existence of COVID-19 spatial clusters. Moran's index was used to map the spatial autocorrelation (cluster) to showcase the spreading patterns of the COVID-19 pandemic in Malaysia. The study results indicated significant changes in the COVID-19 hotspots over time. At the beginning of 2020, the state of Selangor and Sarawak were the first locality to become a significant COVID-19 hotspot. Furthermore, this research showed all affected areas during the study period. Overall, a non-random distribution of COVID-19 occurrences was detected, thus suggesting a positive spatial autocorrelation. Many parties are affected by the COVID-19 pandemic, especially those involved in healthcare provision, financial assistance allocation, and law enforcement. Other sectors such as the economy, education, and religion are also affected. Therefore, the findings from this study will provide useful information to all the related governmental and private agencies, as well as policymakers and researchers.

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The Trend Distribution and Temporal Pattern Analysis of COVID-19 Pandemic using GIS framework in Malaysia

Cited by 4 publications

References 10 publications

The Spatiality of COVID-19 in Kermanshah Metropolis, Iran

The Spatiality of COVID-19 in Kermanshah Metropolis, Iran

The Temporal and Spatial Analysis of Corona Pandemic in Jordan using the Geographic Information System: An Applied Geographical Study

Exploratory Spatial Data Analysis (Esda) on Covid-19 Cases in Malaysia

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