Desigualdades espaciales de la incidencia de la COVID-19 en relación con factores económicos y sociodemográficos en la Comunidad Autónoma de Madrid (España) DOI Creative Commons
Severino Escolano Utrilla, Andrés Roca-Medina, Diego A. Barrado Timón

et al.

Documents d Anàlisi Geogràfica, Journal Year: 2024, Volume and Issue: 70(3), P. 355 - 382

Published: July 24, 2024

This article models the relationship between incidence of COVID-19 and several socioeconomic factors during second period epidemic (22 June 2020 to 06 December 2020) in Autonomous Community Madrid, Spain. Data collected from Basic Health Zones (BHZs) is adjusted using random forest method, which proves very appropriate for capturing non-linear relationships obtaining accurate robust predictions. The results show that impact examined socio-economic variables on rates was not uniform, levels mean income by neighborhood exerted stronger influence than population density, proportion Spanish population, age or average household size. A complex spatial pattern emerges combination impacts, reflecting relative weights different terms intensity pandemic. information may be considered strategic effective future management health resources.

Language: Английский

The Role of Functional Urban Areas in the Spread of COVID-19 Omicron (Northern Spain) DOI Creative Commons
Olga de Cos Guerra, Valentín Castillo Salcines, David Cantarero

et al.

Journal of Urban Health, Journal Year: 2023, Volume and Issue: 100(2), P. 314 - 326

Published: Feb. 24, 2023

This study focuses on the space-time patterns of COVID-19 Omicron wave at a regional scale, using municipal data. We analyze Basque Country and Cantabria, two adjacent regions in north Spain, which between them numbered 491,816 confirmed cases their 358 municipalities from 15th November 2021 to 31st March 2022. The seeks determine role functional urban areas (FUAs) spread variant virus, ESRI Technology (ArcGIS Pro) applying intelligence location methods such as 3D-bins emerging hot spots. Those help identify trends types problem area, spots, level. results demonstrate that FUAs do not contain an over-concentration cases, coefficient is under 1.0 relation population. Nevertheless, have important drivers upward curve wave. Significant spot are found 85.0% FUA where 98.9% occur. distribution shows spatially stationary linear correlation linked demographically progressive (densely populated, young profile, with more children per woman) well connected by highways railroads. Based this research, proposed GIS methodology can be adapted other case studies. Considering geo-prevention WHO Health All Policies approaches, research findings reveal spatial policymakers tackling pandemic future waves society learns live virus.

Language: Английский

Citations

3

Geodemographic profiles of COVID-19 mortality inside/outside nursing homes. Spatial analysis from microdata in North Spain DOI Creative Commons
Olga de Cos Guerra, Valentín Castillo Salcines, David Cantarero

et al.

Applied Geography, Journal Year: 2023, Volume and Issue: 162, P. 103153 - 103153

Published: Nov. 28, 2023

After two years of the COVID-19 pandemic, there is extensive research on spread virus and geo-statistical analysis spatial patterns. However, from perspective health geography, mortality still under-studied. This aims to provide a geographic profile mortality, in terms space-time evolution relationship with individual contextual variables. To this end, we geocoded daily microdata deceased persons provided by Government Cantabria (in northern Spain) March 1, 2020 31, 2022. The study also took cadastral variables, population records, connections geo-enrichment services accessed through ArcGIS Pro License (ESRI) into account. Using statistics methods, such as 3D bins emerging hot spots, local bivariate relationships, ordinary least squares, propose an exportable scalable methodology help policymakers cope current stage living epidemic virus. Our results suggest that distribution less clustered than contagion shed light differences profiles inside/outside nursing homes, higher age, temporal concentration deaths homes. Spatial regimes showed spots urban metropolitan areas, pattern repetition over time, sporadic accounted for 36.28% only 11.88% area deaths. Despite immunization, periods high meant subsequent increase during Omicron wave, where consecutive 37.50% 51.45% were concentrated. Finally, interesting nuances significant context variables compared explanatory factors cases.

Language: Английский

Citations

3

The role of the socio-economic context in the spread of the first wave of COVID-19 in the Marche Region (central Italy) DOI
Eleonora Gioia, Alessandra Colocci, Cristina Casareale

et al.

International Journal of Disaster Risk Reduction, Journal Year: 2022, Volume and Issue: 82, P. 103324 - 103324

Published: Oct. 4, 2022

Language: Английский

Citations

3

Geographical Analysis of COVID-19 Epidemiology: A Review DOI Open Access

Thi-Quynh Nguyen

International Journal of Science and Healthcare Research, Journal Year: 2023, Volume and Issue: 8(3), P. 220 - 226

Published: Aug. 31, 2023

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

Language: Английский

Citations

1

Desigualdades espaciales de la incidencia de la COVID-19 en relación con factores económicos y sociodemográficos en la Comunidad Autónoma de Madrid (España) DOI Creative Commons
Severino Escolano Utrilla, Andrés Roca-Medina, Diego A. Barrado Timón

et al.

Documents d Anàlisi Geogràfica, Journal Year: 2024, Volume and Issue: 70(3), P. 355 - 382

Published: July 24, 2024

This article models the relationship between incidence of COVID-19 and several socioeconomic factors during second period epidemic (22 June 2020 to 06 December 2020) in Autonomous Community Madrid, Spain. Data collected from Basic Health Zones (BHZs) is adjusted using random forest method, which proves very appropriate for capturing non-linear relationships obtaining accurate robust predictions. The results show that impact examined socio-economic variables on rates was not uniform, levels mean income by neighborhood exerted stronger influence than population density, proportion Spanish population, age or average household size. A complex spatial pattern emerges combination impacts, reflecting relative weights different terms intensity pandemic. information may be considered strategic effective future management health resources.

Language: Английский

Citations

0