Gis And Remote Sensing: A Review Of Applications To The Study Of The Covid-19 Pandemic

Kieu, Quoc-lap; Nguyen, Tien-thanh; Hoang, Anh-huy

doi:10.24057/2071-9388-2021-054

Cited by 5 publications

(8 citation statements)

References 96 publications

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“…It was concluded that the population that emigrated from Wuhan was the main infection source in other cities and provinces (24). After the COVID-19 pandemic rapidly spread across over the world, attempts have been put on the use of geographical analysis to detect the spatio-temporal changes in many countries, especially in the worst-affected countries (25). Using spatial and space-time scan statistics and the Joinpoint analysis, a study in the United States has indicated that higher risks of clustering and incidence of COVID-19 were consistently observed in metropolitan versus rural counties, counties closest to core airports, the most populous counties, and counties with the highest proportion of racial/ethnic minorities (26).…”

Section: Resultsmentioning

confidence: 99%

Geographical Analysis of COVID-19 Epidemiology: A Review

Nguyen

2023

Int J Sci Healthcare Res

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Background: Since coronavirus disease 2019 (Covid-19) emerged in Wuhan city and rapidly spread throughout China in December 2019, many methods have been proposed for COVID-19 studies. Methods: In this study, we reviewed the geographical analysis-based methodological approaches in COVID-19 epidemiological studies. Three different issues related to applications of geographical analysis in the COVID-19 epidemiology are presented under three sub-sections; namely (1) assessing the spatial distribution of the COVID-19 pandemic at different scales, (2) WebGIS-based mapping the COVID-19 pandemic, and (3) the assessment of impacts of socio-economic factors on the transmission of the COVID-19 pandemic. A systematic literature search of geographical studies of COVID-19 published in English. Results: It was found that geographical analysis can effectively help to study the COVID-19 epidemiology. Conclusion: The study contributes to current research on the spread and social-economic impacts of the COVID-19 pandemic. Keywords: Geographical analysis, COVID-19, Spatial statistics, Epidemiology, Review.

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Section: Resultsmentioning

confidence: 99%

Geographical Analysis of COVID-19 Epidemiology: A Review

Nguyen

2023

Int J Sci Healthcare Res

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“…It is, therefore, an advanced technique as remote sensing in the study of COVID-19 pandemic plays an important role in the fight against the COVID-19 pandemic.Remote sensing is the process of detecting and monitoring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance (typically from satellite or aircraft). Remote sensing allows acquiring information about the Earth's surface without actually being in contact with it (5). Satellite remote sensing data was used widely by government, humanitarian, and private bodies during the pandemic (6).…”

Section: Introductionmentioning

confidence: 99%

Applications Of Remote Sensing In The Study Of COVID-19 Pandemic – A Review

Nguyen¹,

Bui²,

Ngo³

2023

IJHMR

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The global outbreak of the COVID-19 pandemic has spread worldwide, affecting almost all countries and territories. Various social-economic and environmental factors influence the outbreak and spread of the epidemic. Many modern techniques have been widely employed to study the COVID-19 pandemic. This paper aims to give an overview of applications offered by remote sensing techniques to study the COVID-19 pandemic through summarising a total of 55 scientific papers. Three different issues related to the COVID-19 pandemic is presented under three sub-sections; namely (1) applications of remotely sensed images on monitoring environmental changes and (2) the analysis of social and economic impacts caused by the COVID-19 pandemic, and (3) the use of remote sensing in studies of the epidemiology of SARS-CoV-2. The findings of this study provide important insights into how to apply such an advanced techniques as remote sensing in the fight against the COVID-19 pandemic. The varied applications of remote sensing affirms the value of this advanced technique to the study of small-to-large scale disasters in general and of the COVID-19 pandemic in particular.

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“…A crucial tool for analysing the spatial pattern of spatial objects is a spatial statistic. (5). In accordance with Tobler's First Law of Geography, epidemiological research have effectively used commonly used statistics for spatial autocorrelation analysis, such as global spatial statistics (Moran's I, Getis-Ord G* and Geary's C) and local indicators of spatial association (LISA) (6)(7)(8)(9) in general, and in the investigation of COVID-19's transmission (10)(11)(12) and hand-foot-andmouth disease (13,14) in particular.…”

Section: Introductionmentioning

confidence: 99%

Identification of infectious disease spatial clusters based on local Moran’s I statistic: A case study of dengue hemorrhagic fever

Thi-Tuyet-Mai Nguyen,

Thi-Quynh Nguyen,

Thi-Hien Cao

2023

World J. Biol. Pharm. Res.

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Background: One of the most prevalent tropical illnesses that impact people is dengue. Dengue and dengue hemorrhagic fever (DF/DHF) have become much more common within the past few decades. The purpose of this study is to use the local Moran's I statistic to identify any spatial clustering of dengue hemorrhagic fever in Ho Chi Minh City, Vietnam, during the months of June through July of 2023. Methods: The data distribution was first examined using descriptive statistics. The spatial clustering of dengue hemorrhagic fever over these four months was then examined using the global Moran's I statistic, Moran's I scatterplot, and local Moran's I statistic. More precisely, using the local Moran's I statistic, dengue hemorrhagic fever clusters (high-high and low-low) and geographical outliers (low-high and high-low) were found in Ho Chi Minh City. Results: It was discovered that DHF infection rates in Ho Chi Minh City likely to rise gradually between June and July of 2023. High-high spatial clustering of DHF infection rates was primarily found in urban areas and the city centre, despite the fact that this pattern has rapidly changed. Conclusions: The results of this investigation showed that Ho Chi Minh City has statistically significant spatial clusters of DHF. The findings of this investigation further show that local Moran's I statistic is validated in the context of studying the spatial clustering of infectious diseases in general and DHF in particular. The research findings offer valuable insights into the knowledge of the dissemination of DHF.

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Gis And Remote Sensing: A Review Of Applications To The Study Of The Covid-19 Pandemic

Cited by 5 publications

References 96 publications

Geographical Analysis of COVID-19 Epidemiology: A Review

Geographical Analysis of COVID-19 Epidemiology: A Review

Applications Of Remote Sensing In The Study Of COVID-19 Pandemic – A Review

Identification of infectious disease spatial clusters based on local Moran’s I statistic: A case study of dengue hemorrhagic fever

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