Spatiotemporal pattern of Covid-19 outbreak in Turkey

Aral, Neşe; Bakır, Hasan

doi:10.1007/s10708-022-10666-9

Cited by 6 publications

(5 citation statements)

References 67 publications

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“…The spatial situation of an attribute value across the entire region can be reflected by spatial autocorrelation ( 18 ). Within the study area, the method incorporates location and eigenvalues.…”

Section: Methodsmentioning

confidence: 99%

Spatial age-period-cohort analysis of hepatitis B risk in Xinjiang from 2006 to 2019

Wang

Xie

et al. 2023

Front. Public Health

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ObjectiveThe objective of this study was to investigate the spatio-temporal distribution and epidemiological characteristics of hepatitis B in 96 districts and counties of Xinjiang and to give useful information for hepatitis B prevention and treatment.MethodsBased on the incidence data of hepatitis B in 96 districts and counties of Xinjiang from 2006 to 2019, the global trend analysis method was used to characterize the spatial variability of the disease, and the spatial autocorrelation and spatio-temporal aggregation analysis were used to explore the spatial clustering of hepatitis B and to identify high-risk areas and periods. The Integrated Nested Laplace Approximation (INLA)-based spatial age-period-cohort model was established to further explore the influence of age, period, birth queue effect, and spatial distribution on the incidence risk of hepatitis B, and sum-to-zero constraint was adopted to avoid the issue of model unrecognition.ResultsThe risk of hepatitis B in Xinjiang is increasing from west to east and from north to south, with spatial heterogeneity and spatio-temporal scanning statistics yielding five clustering areas. The spatial age-period-cohort model showed two peaks in the average risk of hepatitis B, at [25,30) years old and [50,55) years old, respectively. The mean risk of hepatitis B incidence fluctuated up and down around 1 with time, and the average risk of disease by birth cohort displayed an increasing-decreasing-stabilizing trend. Taking age, period, and cohort effect into consideration, it was found that the areas with a high risk of hepatitis B are Tianshan District, Xinshi District, Shuimogou District, Changji City, Aksu City, Kashi City, Korla City, Qiemo County and Yopurga County in Xinjiang. According to the spatio-temporal effect item, it was found that there are unobserved variables affecting the incidence of hepatitis B in some districts and counties of Xinjiang.ConclusionThe spatio-temporal characteristics of hepatitis B and the high-risk population needed to be taken into attention. It is suggested that the relevant disease prevention and control centers should strengthen the prevention and control of hepatitis B among young people while paying attention to middle-aged and older adult people, and strengthening the prevention and monitoring of high-risk areas.

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Section: Methodsmentioning

confidence: 99%

Spatial age-period-cohort analysis of hepatitis B risk in Xinjiang from 2006 to 2019

Wang

Xie

et al. 2023

Front. Public Health

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“…Most recently, when assessing the effect of covid-19 lockdown on surface urban heat island for different land use /cover types using Landsat 8 OLI/TIRS images, it was found that for New Delhi, Hyderabad, and Mumbai, the mean land surface temperature decreases by 5°C, 1.9°C, and 0.26°C, respectively, in April 2020 (after lockdown) in comparison with April 2019 (38). In addition, environmental changes and impacts of the COVID-19 pandemic using remote sensing has been also successfully monitored and assessed in many COVID-19 badly-affected countries such as China (39,40), Italy (41), and India (42) etc…”

Section: Monitoring Environmental Changes and Impacts Of The Covid-19...mentioning

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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“…(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. In keeping with this notion, popular statistics for geographical auto-correlation analysis, including global spatial statistics, have been effectively applied in infectious disease epidemiological studies (6-9) like the hand, foot, and mouth disease and COVID-19.…”

Section: Introductionmentioning

confidence: 99%

“…In keeping with this notion, popular statistics for geographical auto-correlation analysis, including global spatial statistics, have been effectively applied in infectious disease epidemiological studies (6-9) like the hand, foot, and mouth disease and COVID-19. For instance, the research of COVID-19 dissemination has made extensive use of these spatial information (10)(11)(12). More specifically, a study on spatial analysis and hotspots identification of COVID-19 utilising GIS (March and April, 2020) was successfully completed using spatial statistics (15) whereas Anselin local Moran's I indices and hot spot analysis were subsequently used to precisely identify high-and low-risk COVID-19 clusters worldwide.…”

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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Spatiotemporal pattern of Covid-19 outbreak in Turkey

Cited by 6 publications

References 67 publications

Spatial age-period-cohort analysis of hepatitis B risk in Xinjiang from 2006 to 2019

Spatial age-period-cohort analysis of hepatitis B risk in Xinjiang from 2006 to 2019

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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