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1.
JAMA Netw Open ; 4(6): e2113818, 2021 06 01.
Artículo en Inglés | MEDLINE | ID: covidwho-1274645

RESUMEN

Importance: Limited information on the transmission and dynamics of SARS-CoV-2 at the city scale is available. Objective: To describe the local spread of SARS-CoV-2 in Valencia, Spain. Design, Setting, and Participants: This single-center epidemiological cohort study of patients with SARS-CoV-2 was performed at University General Hospital in Valencia (population in the hospital catchment area, 364 000), a tertiary hospital. The study included all consecutive patients with COVID-19 isolated at home from the start of the COVID-19 pandemic on February 19 until August 31, 2020. Exposures: Cases of SARS-CoV-2 infection confirmed by the presence of IgM antibodies or a positive polymerase chain reaction test result on a nasopharyngeal swab were included. Cases in which patients with negative laboratory results met diagnostic and clinical criteria were also included. Main Outcomes and Measures: The primary outcome was the characterization of dissemination patterns and connections among the 20 neighborhoods of Valencia during the outbreak. To recreate the transmission network, the inbound and outbound connections were studied for each region, and the relative risk of infection was estimated. Results: In total, 2646 patients were included in the analysis. The mean (SD) age was 45.3 (22.5) years; 1203 (46%) were male and 1442 (54%) were female (data were missing for 1); and the overall mortality was 3.7%. The incidence of SARS-CoV-2 cases was higher in neighborhoods with higher household income (ß2 [for mean income per household] = 0.197; 95% CI, 0.057-0.351) and greater population density (ß1 [inhabitants per km2] = 0.228; 95% CI, 0.085-0.387). Correlations with meteorological variables were not statistically significant. Neighborhood 3, where the hospital and testing facility were located, had the most outbound connections (14). A large residential complex close to the city (neighborhood 20) had the fewest connections (0 outbound and 2 inbound). Five geographically unconnected neighborhoods were of strategic importance in disrupting the transmission network. Conclusions and Relevance: This study of local dissemination of SARS-COV-2 revealed nonevident transmission patterns between geographically unconnected areas. The results suggest that tailor-made containment measures could reduce transmission and that hospitals, including testing facilities, play a crucial role in disease transmission. Consequently, the local dynamics of SARS-CoV-2 spread might inform the strategic lockdown of specific neighborhoods to stop the contagion and avoid a citywide lockdown.


Asunto(s)
COVID-19/epidemiología , Áreas de Influencia de Salud/estadística & datos numéricos , Brotes de Enfermedades/estadística & datos numéricos , Transmisión de Enfermedad Infecciosa/estadística & datos numéricos , Características de la Residencia/estadística & datos numéricos , Adulto , Anciano , Anciano de 80 o más Años , COVID-19/transmisión , Estudios de Cohortes , Femenino , Geografía , Humanos , Incidencia , Masculino , Persona de Mediana Edad , Factores de Riesgo , SARS-CoV-2 , España/epidemiología
2.
Scand J Urol ; 55(3): 184-191, 2021 Jun.
Artículo en Inglés | MEDLINE | ID: covidwho-1207211

RESUMEN

INTRODUCTION: The first case of COVID-19 in Sweden was diagnosed in late January 2020, the first recommendations against the spread of the virus were released in mid-March, and the peak of the first wave of the pandemic was reached in March-June. The aim of this cross-sectional study was to assess the short-term effects of the first wave of the COVID-19 pandemic on prostate cancer (PCa) diagnosis, staging, and treatment. MATERIALS AND METHODS: Data in the National Prostate Cancer Register (NPCR) of Sweden on newly diagnosed PCa cases and on the number of diagnostic and therapeutic procedures performed between 18 March 2020 and 2 June 2020 were compared with those in the corresponding time periods in 2017-2019, as reported until January 31 of the year after each study period. RESULTS: During the study period in 2020, 36% fewer PCa cases were registered in NPCR compared with the corresponding time period in previous years: 1458 cases in 2020 vs a mean of 2285 cases in 2017-2019. The decrease in new PCa registrations was more pronounced in men above age 75 years, down 51%, than in men aged 70-75, down 37%, and in men below age 70, down 28%. There was no decrease in the number of radical prostatectomies and number of radical radiotherapy courses increased by 32%. CONCLUSIONS: During the peak of the first phase of the COVID-19 pandemic, the number of men diagnosed with PCa in Sweden decreased by one third compared with previous years, whereas there was no decrease in the number of curative treatments.


Asunto(s)
COVID-19/mortalidad , Atención a la Salud/estadística & datos numéricos , Neoplasias de la Próstata/diagnóstico , Neoplasias de la Próstata/terapia , Factores de Edad , Anciano , Áreas de Influencia de Salud/estadística & datos numéricos , Estudios Transversales , Humanos , Masculino , Prostatectomía/estadística & datos numéricos , Neoplasias de la Próstata/patología , Radioterapia/estadística & datos numéricos , Sistema de Registros , SARS-CoV-2 , Suecia/epidemiología
3.
Int J Health Geogr ; 19(1): 36, 2020 09 14.
Artículo en Inglés | MEDLINE | ID: covidwho-757061

RESUMEN

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing the coronavirus disease 2019 (COVID-19) pandemic, has infected millions of people and caused hundreds of thousands of deaths. While COVID-19 has overwhelmed healthcare resources (e.g., healthcare personnel, testing resources, hospital beds, and ventilators) in a number of countries, limited research has been conducted to understand spatial accessibility of such resources. This study fills this gap by rapidly measuring the spatial accessibility of COVID-19 healthcare resources with a particular focus on Illinois, USA. METHOD: The rapid measurement is achieved by resolving computational intensity of an enhanced two-step floating catchment area (E2SFCA) method through a parallel computing strategy based on cyberGIS (cyber geographic information science and systems). The E2SFCA has two major steps. First, it calculates a bed-to-population ratio for each hospital location. Second, it sums these ratios for residential locations where hospital locations overlap. RESULTS: The comparison of the spatial accessibility measures for COVID-19 patients to those of population at risk identifies which geographic areas need additional healthcare resources to improve access. The results also help delineate the areas that may face a COVID-19-induced shortage of healthcare resources. The Chicagoland, particularly the southern Chicago, shows an additional need for resources. This study also identified vulnerable population residing in the areas with low spatial accessibility in Chicago. CONCLUSION: Rapidly measuring spatial accessibility of healthcare resources provides an improved understanding of how well the healthcare infrastructure is equipped to save people's lives during the COVID-19 pandemic. The findings are relevant for policymakers and public health practitioners to allocate existing healthcare resources or distribute new resources for maximum access to health services.


Asunto(s)
Áreas de Influencia de Salud/estadística & datos numéricos , Infecciones por Coronavirus/epidemiología , Recursos en Salud/estadística & datos numéricos , Neumonía Viral/epidemiología , Betacoronavirus , COVID-19 , Accesibilidad a los Servicios de Salud/organización & administración , Capacidad de Camas en Hospitales/estadística & datos numéricos , Humanos , Illinois , Unidades de Cuidados Intensivos/estadística & datos numéricos , Pandemias , SARS-CoV-2 , Factores Socioeconómicos , Análisis Espacial , Ventiladores Mecánicos/provisión & distribución
4.
Health Place ; 65: 102406, 2020 09.
Artículo en Inglés | MEDLINE | ID: covidwho-733839

RESUMEN

The increasing inequality in spatial accessibility to hospitals in developing countries has been attracting attention from researchers and politicians. The situation seems to be worse in growing megacities where more than 10 million people live and rapid urban sprawl has caused serious problems with the supply of health and public transport services. The recent global COVID-19 pandemic calls for particular attention to be afforded to the matter of equal access to basic medical facilities and services for people across different neighborhoods. Although some studies have already been undertaken into the subject of health-focused inequality in the cities of developing countries, the spatial inequity in hospital accessibility has rarely been discussed to date. In this paper, I aim to provide new evidence by considering Beijing as a case study. With the results of my analysis, I show that low-income neighborhoods have experienced lower levels of accessibility not only to high-tier hospitals (secondary and tertiary hospitals) but also to primary healthcare services (primary hospital and neighborhood clinics). The rate at which high-income neighborhoods access secondary and tertiary hospitals is approximately 4 times and 1.5 times as high as that of low-income neighborhoods. Low-income face nearly twice the travel time of those from high-income neighborhoods to reach the nearest primary hospital or neighborhood clinics. Suburban neighborhoods have less access to medical services than neighborhoods that are located in the central urban areas. It seems that the rapid urban sprawl has been worsening spatial inequality in the context of access to medical services in the growing megacity of Beijing. Equal access to healthcare services should be prioritized in future policy discussions, especially in relation to the urban growth management of megacities in developing countries in order to ensure that fair and inclusive urbanization processes are undertaken. Equal access to healthcare services would also be widely beneficial in the context of managing the COVID-19 pandemic.


Asunto(s)
Áreas de Influencia de Salud/estadística & datos numéricos , Infecciones por Coronavirus/epidemiología , Accesibilidad a los Servicios de Salud , Hospitales/estadística & datos numéricos , Pandemias , Neumonía Viral/epidemiología , Factores Socioeconómicos , Beijing , Betacoronavirus/aislamiento & purificación , COVID-19 , Ciudades , Humanos , Características de la Residencia , SARS-CoV-2 , Transportes
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