Geospatial modelling of COVID19 mortality in Oman using geographically weighted Poisson regression GWPR

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 8, 2025

The year 2020 witnessed the arrival of global COVID-19 pandemic, which became most devastating public health disaster in last decade. Understanding underlying spatial variations consequences particularly mortality, is crucial for plans and policies. Nevertheless, few studies have been conducted on key determinants mortality how these might vary geographically across developing nations. Therefore, this research aims to address gaps by adopting Geographically Weighted Poisson Regression (GWPR) model investigate heterogeneity Oman. findings indicated that local GWPR performed better than Ordinary Least Square (OLS) model, relationship between risk factors cases varied at a subnational scale. parameter estimates revealed elderly populations, respiratory diseases, population density were significant predicting cases. variable was influential regressor, followed diseases. formulated policy recommendations will provide decision-makers practitioners with related pandemic so future interventions preventive measures can mitigate high fatality risks.

Language: Английский

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Multiscale Geographically Weighted Regression in the Investigation of Local COVID-19 Anomalies Based on Population Age Structure in Poland

International Journal of Environmental Research and Public Health, Journal Year: 2023, Volume and Issue: 20(10), P. 5875 - 5875

Published: May 19, 2023

A growing number of various studies focusing on different aspects the COVID-19 pandemic are emerging as continues. Three variables that most commonly used to describe course worldwide confirmed SARS-CoV-2 cases, deaths, and vaccine doses administered. In this paper, using multiscale geographically weighted regression, an analysis interrelationships between administered were conducted. Furthermore, maps local R2 estimates, it was possible visualize how relations explanatory dependent vary across study area. Thus, influence demographic factors described by age structure gender breakdown population over performed. This allowed identification anomalies in pandemic. Analyses carried out for area Poland. The results obtained may be useful authorities developing strategies further counter

Language: Английский

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Spatial Variations in Perceptions of COVID-19 in Relation to Socio-Economic Vulnerability in Gauteng, South Africa

Published: Jan. 25, 2024

This study sought to spatially characterise and explain the differences of peoples’ perceptions on impact COVID-19 based socio-economic disparities in Gauteng, using choropleth mapping Geographically Weighted Regression (GWR). Results indicate that respondents from relatively vulnerable municipalities like Merafong, Mogale City Lesedi reported life being worse, information scant, overall despondency high since COVID-19. These are areas fall under High Very categories terms Socio-economic Risk Index. GWR results, however, did not show a explanatory power variables se-lected for research, R2 values. For instance, residual satisfaction with after was lowest (-0.5 0.5) less affluent districts Rand West Sedibeng. Residual changes were also southern parts same districts, other low values almost evenly distributed throughout province variable ‘Government scant’. Although overestimation underestimation existed, most falling between -1.5 -0.5 across province. In sum, findings point complexity factors characterising social risk vulnerability. Additionally, negative sentiments expressed by people more locations emphasise need targeted interventions government cushion residents continued impacts

Language: Английский

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Identification and Management of Epidemic Hazard Areas for Urban Sustainability: A Case Study of Tongzhou, China

Sustainability, Journal Year: 2024, Volume and Issue: 16(18), P. 7945 - 7945

Published: Sept. 11, 2024

The global epidemic is relatively stable, but urban pandemics will still exist. This study used sDNA (spatial design network analysis), spatial autocorrelation, and GWR (geographically weighted regression analysis) to identify potentially risky roads, pandemic hazard areas, various infrastructure areas in the Tongzhou District for sustainability. results show that roads at risk during an have high proximity aggregation effects. These are mainly concentrated core area. identification focused on sub-center Yizhuang New Town. paper derives actual using POI (points of interest) data COVID-19 (coronavirus disease 2019) compares with areas. It found do not area completely. In this study, analyses based gridded obtain types develop different control ranges methods. provides new perspectives identifying priority prevention, control, sustainable development.

Language: Английский

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Representative Residential Property Model—Soft Computing Solution

International Journal of Environmental Research and Public Health, Journal Year: 2022, Volume and Issue: 19(22), P. 15114 - 15114

Published: Nov. 16, 2022

Residential properties are a major component of the environment and economy key element for quality human life. Faced with disruptive ideological technological changes in world, real estate analysis has also become research problem many academic centers private institutions. Due to complex nature properties, they one most difficult troublesome subjects analysis. Given rapid advancements competitive automated analytical models, data representative sample selection may prove be very wide-reaching subject. The aim this paper was assessment particular soft computing methods’ (e.g., Self-Organizing Maps, Rough Set Theory) usefulness selecting property model. obtained results confirm that use these methods leads creation model enables more reality-based view uncertainty imprecise residential environment.

Language: Английский

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The Course of the COVID-19 Pandemic in Poland in Relation to the Level of Sustainable Development – Multiscale Geographically Weighted Regression Analysis

Acta Scientiarum Polonorum Administratio Locorum, Journal Year: 2024, Volume and Issue: 23(4), P. 417 - 436

Published: Dec. 23, 2024

Motives: This article explores the relation between course of COVID-19 pandemic and level Sustainable Development Polish counties. First, data was collected to describe in terms Social, Environmental Economical indicators. In second step, using regarding number cases deaths caused by pandemic, a regression model built Multiscale Geographically Weighted Regression (MGWR). Aim: Authors decided create comprehensive Development. approach made it possible analyze relations as well provided an opportunity address individual components model. Results: The values coefficient determination indicate high very fit. MGWR also develop maps local R-Squared values. These maps, exploring spatially varying relationships variables, further allowed identify anomalies phenomenon.

Language: Английский

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The Social Geography of Women’s Attitudes toward Wife-beating in Ethiopia: A Contribution Towards Proper Application of Spatial Statistics

Journal of Geography and Geology, Journal Year: 2023, Volume and Issue: 15(2), P. 16 - 16

Published: Sept. 19, 2023

Spatial statistical measures have been applied to Ethiopia’s Demographic and Health Survey data (EDHS), mostly at the national level. However, there is concern that most applications violate basic principles of statistics regarding autocorrelation, or are not cognizant first law geography which states all things related but near more related. This study investigates local variations in attitudes toward wife-beating Ethiopia with education as main correlate. It does so by using a spatial measure known geographically weighted regression (GWR) appropriate conditions geographic non-stationarity than ordinary least squares (OLS). Equally importantly, it examines appropriateness existing OLS-based studies EDHS data. We found inappropriately OLS despite findings spatially autocorrelated The GWR model showed an association between acceptance educational status. also generated list twelve sampling clusters where women respondents stated was acceptable while admitting having had no formal education, R2s exceeded 0.5 modeling involving 72 nearest neighbors per cluster. An education-focused bi-variate rather multi-variate avoided issues multicollinearity keeping simple its results actionable. Although majority Harari Wereda Kilil, got their name from members ethnic group predominantly Muslim, difficult pinpoint factor set factors can be cited causally associated characteristics placed them on list. makes methodological contributions sociodemographic populations, especially those developing countries such show significant variations. adds literature regression.

Language: Английский

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Application of Geographic Information Systems in the Study of COVID-19 in Morocco

The Open Public Health Journal, Journal Year: 2023, Volume and Issue: 16(1)

Published: Oct. 13, 2023

Introduction: The 2019 coronavirus disease (COVID-19) was first identified as a respiratory that originated in Wuhan, Hubei Province, China. WHO declared the COVID-19 outbreak public health emergency of international concern on 30 January 2020. Morocco reported its case 2 March During week 9-15 2020, took steps to limit spread epidemic. This article describes use spatial data applications epidemiological research Morocco, specifically response Methods: To conduct this study, we relied and analysis provided by Moroccan Ministry Health for study period from May July 2021, well geographical administrative map Kingdom Morocco. Spatial performed using ArcGIS 10.8 QGIS, geographic information processing software. 12 regions territory were presented number cases discrete quantitative variable over time continuous variable. Results: According created GIS, concentration appeared be highest Casablanca Settat region. Depending documented cases, ranked follows: Casablanca-Settat> Rabat-Sale-Kenitra> Marrakech-Safi > Fes-Meknes Tangier-Tetouan-Alhouceima>Oriental>Souss-Massa Béni Mellal-Khenifra> Draa-Tafilalet> Laayoune-Sakia El Hamra >Guelmim-Oued Noun Dakhla-Oued Eddahab. increase major cities due several factors, including demographic, social environmental factors. demonstrated need consider demographic contributions health. Demographic factors helped us understand our environment empirically. Geography improved decision-making accountability. Incorporating context decision-makers impact location strategies goals combat pandemic. Conclusion: areas with high low clusters hotspots. produced maps can serve an excellent management tool control effectively eliminate pandemic, contributing investments surveillance programs.

Language: Английский

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