Relationships between socio-demographic structure and spatio-temporal distribution patterns of COVID-19 cases in Istanbul, Turkey

Yılmaz, Merve; Hamurcu, Aslı Ulubaş

doi:10.1080/12265934.2022.2063160

Cited by 5 publications

(5 citation statements)

References 29 publications

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“…Using Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) methods, the study investigates relationships between COVID-19 intensity and factors such as gender, household size, population density, and education level. Findings indicate the significance of these factors in influencing exposure to COVID-19 and highlight the potential use of the study's outcomes for decision-making and control measures in densely populated urban areas [20].…”

Section: Literature Reviewmentioning

confidence: 85%

Temporal Analysis Of COVID-19 Cases And Recovery Trends In Panvel City: A Spline Curve Approach

Patil,

Jadhav,

Pagare

et al. 2024

JAZ

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Section: Literature Reviewmentioning

confidence: 85%

Temporal Analysis Of COVID-19 Cases And Recovery Trends In Panvel City: A Spline Curve Approach

Patil,

Jadhav,

Pagare

et al. 2024

JAZ

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“…Bandwidth is determined by minimizing the sum of squares of error between the predicted and actual values. It establishes statistical relationships between dependent and explanatory variables in spatial bandwidth [90]. In the MGWR model, each predictor variable has its bandwidth.…”

Section: Spatial Analysismentioning

confidence: 99%

Exploring the Relationships between Land Surface Temperature and Its Influencing Determinants Using Local Spatial Modeling

2023

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In recent years, a growing body of research has investigated the factors influencing land surface temperature (LST) in different cities, employing diverse methodologies. Our study aims to be one of the few to examine the socio-environmental variables (SV) of LST with a holistic approach, especially in primate cities in developing countries, which are particularly vulnerable to the impacts of climate change. In this context, the study preliminarily identifies the SV of LST while investigating the most vulnerable areas related to extreme LST at the neighborhood level. The combined 11 variables are analyzed using spatial modeling methods (GWR and MGWR). The MGWR model outperforms the GWR model with an adjusted R2 of 0.96. The results showed that: (1) the 65+ population is negatively associated with LST in 95% of neighborhoods; the socioeconomic index–LST relationship is negative in 65% of neighborhoods. (2) In 90% of the neighborhoods where the relationship between LST and the built environment ratio is positive, the socioeconomic level decreases while household size increases in 98% of the neighborhoods. (3) In 62% of the neighborhoods where the relationship between the 65+ population and LST is negative, the relationship between the socioeconomic level and LST is negative. This study aids decision-makers and planners in managing urban resources to reduce extreme LST exposure region by region and recommending multiscale policies to control determinant influences on LST.

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“…Spatial regression methods, such as GWR, were used to address non-stationarity. Ganasegeran et al [ 28 ] and Yilmaz and Ulubaş Hamurcu [ 29 ] investigated the spatial relationship between socio-demographic determinants and COVID-19 in Malaysia and Turkey using GWR. They concluded that gender, household size, the GINI coefficient [ 28 , 29 ], and population density are significant determinants of COVID-19 occurrence.…”

Section: Introductionmentioning

confidence: 99%

“…Ganasegeran et al [ 28 ] and Yilmaz and Ulubaş Hamurcu [ 29 ] investigated the spatial relationship between socio-demographic determinants and COVID-19 in Malaysia and Turkey using GWR. They concluded that gender, household size, the GINI coefficient [ 28 , 29 ], and population density are significant determinants of COVID-19 occurrence. Han et al [ 30 ] investigated the effect of air pollution and meteorological factors on incidence rates using the generalized linear mixed effect model and GWR.…”

Section: Introductionmentioning

confidence: 99%

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis

et al. 2023

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There are different area-based factors affecting the COVID-19 mortality rate in urban areas. This research aims to examine COVID-19 mortality rates and their geographical association with various socioeconomic and ecological determinants in 350 of Tehran’s neighborhoods as a big city. All deaths related to COVID-19 are included from December 2019 to July 2021. Spatial techniques, such as Kulldorff's SatScan, geographically weighted regression (GWR), and multi-scale GWR (MGWR), were used to investigate the spatially varying correlations between COVID-19 mortality rates and predictors, including air pollutant factors, socioeconomic status, built environment factors, and public transportation infrastructure. The city's downtown and northern areas were found to be significantly clustered in terms of spatial and temporal high-risk areas for COVID-19 mortality. The MGWR regression model outperformed the OLS and GWR regression models with an adjusted R2 of 0.67. Furthermore, the mortality rate was found to be associated with air quality (e.g., NO2, PM10, and O3); as air pollution increased, so did mortality. Additionally, the aging and illiteracy rates of urban neighborhoods were positively associated with COVID-19 mortality rates. Our approach in this study could be implemented to study potential associations of area-based factors with other emerging infectious diseases worldwide.

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Relationships between socio-demographic structure and spatio-temporal distribution patterns of COVID-19 cases in Istanbul, Turkey

Cited by 5 publications

References 29 publications

Temporal Analysis Of COVID-19 Cases And Recovery Trends In Panvel City: A Spline Curve Approach

Temporal Analysis Of COVID-19 Cases And Recovery Trends In Panvel City: A Spline Curve Approach

Exploring the Relationships between Land Surface Temperature and Its Influencing Determinants Using Local Spatial Modeling

The COVID-19 Mortality Rate Is Associated with Illiteracy, Age, and Air Pollution in Urban Neighborhoods: A Spatiotemporal Cross-Sectional Analysis

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